Embracing Digital Transformation

In a rapidly evolving technological landscape, leaders from diverse sectors apply data analytics, machine learning, and artificial intelligence to their operations. Today, look deeper at a company driving digital transformation in the manufacturing industry – Ori Yudilevich, the CTO of Materials Zone. Bridging the Gap between Physical and Digital in R&DMaterials Zone is focused on the niche yet significant aspect of material science, specifically in the manufacturing industry. Given the considerable role of materials in product development, effectively managing data becomes crucial. Analogous to a cooking recipe, material science involves a nuanced integration of ingredients (materials) passed through a process to produce the final product.However, this area has historically been ad hoc, relying on trial, error, and intuition. Consequently, the knowledge acquired during this process often gets lost due to insufficient documentation or employee attrition. In our modern, interconnected world, where product development processes often span multiple locations, even countries, establishing structured methodologies to prevent knowledge loss is critical. One of the techniques highlighted by Yudilevich is addressing the "trucking factor," which suggests that if the only person who knows how to do a particular task got hit by a truck, it could potentially derail the entire project. Hence, having at least one other person aside from the primary individual who can perform the task could lower the team's vulnerability. Capturing Complexities of Material Science DataThe field of material science generates complex data, often unstructured and difficult to capture using traditional data tables and databases sufficiently. To visualize this, consider data as a graph where raw materials turn into end products. The innumerable interactions between the various constituents give rise to multiple unique dimensions within the data.Moreover, a seamless translation exists within the manufacturing realm – From the explorative research to the production phase, which demands stabilization and consistency. Collating data from these phases into a unified repository can enhance the R&D process by centralizing information, aiding inter-phase learning, and accelerating new product development. Integrating Data Science into ManufacturingWhile data science has permeated many industries, companies focused mainly on product development in the physical world often find setting up dedicated data departments or integrating analytical tools inefficient and costly. This is where Materials Zone's solution comes into play, making data science, machine learning, and statistical tools accessible to businesses unfamiliar with these areas.They offer out-of-the-box tools accompanied by webinars and training sessions for easy adoption, thus reducing the barriers to integrating data science into manufacturing practices. Surprisingly, even Fortune 500 companies who lack the necessary digital skills can benefit significantly from such solutions. As We Step ForwardAs the product development process becomes more complex and global, the critical nature of systematic data management combined with technological innovation is coming to the fore. Companies like Materials Zone are paving the path, guiding businesses to bridge their physical-digital knowledge gap, bolster their manufacturing practices, and ensure future success.For more information, check out https://materials.zone. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

The need for robust data security strategies has grown exponentially in the digital age, becoming a top priority for businesses around the world. Cybersecurity expert and CTO of Walacor, Walter Hancock, offers keen insight into the importance of data integrity and a zero trust approach in current cybersecurity regimes. Unmasking Assumptions About Data SecurityIn the past, people have had implicit trust that their data is secure and their privacy is protected. However, this trust is often based on an outdated model that no longer aligns with the current technological landscape. The increasing number of data breaches and cyber attacks has made it evident that data security is more critical than ever, and the precautions that were considered adequate in the past may no longer be sufficient.Today, data is vulnerable to threats not only from external hackers but also from within organizations. It is essential to understand that a data breach can have significant implications, ranging from financial losses to reputational damage. Therefore, it is crucial to implement a zero-trust approach to data management, which means that every request for access to data must be verified before access is granted. Reliable data audits are also necessary to ensure that the data input matches the output and that there is no unauthorized access to sensitive information. Implementing a New Age of Data Security with WalacorWalacor provides a unique solution to improve our understanding of data security. They offer an automatic and full-proof audit log that is immutable, meaning that once data is entered, it can never be altered or deleted without being detected. This feature makes it incredibly easy to track every change made to the system, which is critical in maintaining a secure environment.By providing transparency and traceability, Walacor's solution helps organizations to meet legal compliance requirements and mitigate risks. For instance, in a legal dispute, an immutable audit log can serve as a reliable source of evidence, as it cannot be tampered with. Furthermore, in the event of a data breach, an immutable audit log can help identify the source of the breach and the extent of damage caused.Overall, Walacor's innovative approach to data security, with its 100% immutable audit log, offers a promising solution for organizations looking to enhance their cybersecurity posture. Shaping the Future of Data IntelligenceThe increasing risk of data breaches means that we need to move away from using multiple layers of data security to a more integrated data protection solution. This type of solution lays the foundation for a Zero Trust environment, which significantly reduces the risk of cyber threats and vulnerabilities. By adopting this approach, we can streamline our data protection methods and ensure better data integrity.The development of data intelligence in the form of data integrity and security opens up new possibilities for digital businesses. Improved data protection methods, better data integrity, and a reduction in potential cyber threats are just a few of the benefits that are set to transform the digital landscape. Among these, the talk of the town is Walacor's unique approach to data integrity and zero trust, which marks a significant milestone in how we approach data security now and in the future.Check out more information from (https://walacor.com)https://walacor.com]See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In the midst of the growing adoption of 5G technologies worldwide, the experts in the recent episode of Embracing Digital Transformation podcast delved into the integral topic of Zero Trust in 5G security. Host Darren Pulsipher welcomed 5G advanced communications expert Leland Brown, VP of Marketing at Trenton Systems Yazz Krdzalic, and Ken Urquhart, a physicist turned cybersecurity professional from Zscaler, to discuss the integration and advancement of 5G technology, along with its challenges and breakthroughs. The Expansive 5G Landscape and The Lonely Island ApproachThe world of 5G technology is rapidly evolving, and as a result, there are a lot of insightful discussions taking place around merging Operational Technology (OT) and Information Technology (IT). Yazz Krdzalic describes the concept of the "Lonely Island approach." This approach refers to the tendency of different entities to focus too heavily on solving their individual problems, which has often led to the stalling of growth in custom hardware in telecom infrastructure. The need to break away from this individualistic approach and re-establish a collective architectural framework that can scale and flex with different use cases is becoming increasingly apparent. With the emergence of 5G technology, there is a need for a collaborative approach that can accommodate the various requirements of different entities. The collective approach will help to ensure that the infrastructure is flexible and scalable, making it easier for entities to integrate their technologies and applications into the network. The discussions around merging OT and IT are also gaining momentum, and it is becoming clear that the collaboration between these two domains is essential for the success of 5G technology. As the technology continues to evolve, it is expected that there will be more debates and discussions around how to take advantage of the opportunities presented by 5G, while also addressing the challenges posed by the emerging technology. Overall, the future of 5G technology looks bright, and the collaboration between different entities will play a critical role in its success. Transitioning to Zero Trust SecurityAs technology continues to evolve, security concerns have become a growing issue for individuals and organizations alike. In order to address these concerns and ensure a safe and secure environment, a collective architectural framework is needed. This framework includes the implementation of advanced security models, such as Zero Trust Security. However, transitioning to these models is not always easy. It requires letting go of older methods of operating and ensuring that all technological modules are synchronized and functioning properly. In the past, it was the customers who were burdened with the responsibility of integrating all the pieces. Fortunately, with the adoption of a more evolved approach, the onus of integration has been considerably reduced for the customers, making the implementation of Zero Trust Security and other advanced security models a much smoother process. Finding The Common Ground In 5G UsageThe development of 5G technology has been a game-changer in both commercial and military sectors. However, there are specific requirements that differentiate the commercial and military usage of 5G. Commercial deployments of private 5G networks are largely static, whereas military deployments need to be mobile. Leland Brown, a prominent expert in the field, has discussed the complexities of finding a common architecture that could cater to both these needs. The challenge was to create a final solution that elegantly fulfilled these requirements. It was important to ensure that the solution was efficient and effective for both commercial and military use cases. The development of such solutions is crucial to ensure that 5G technology is utilized to its fullest potential and can cater to the diverse needs of different industries. Wrapping upThe world of technology is constantly evolving and improving, and the advent of 5G technology and Zero Trust security is a testament to this. However, implementing these advancements can be challenging due to technical and cultural obstacles. Thankfully, experts like Leland Brown, Ken Urquhart, and Yaz Krdzalic are working to streamline the integration of 5G technology and Zero Trust security, making the journey towards a safer and more efficient technological future a little easier for everyone. Their insights and expertise are shedding light on the continuous journey of evolution and improvement in the world of technology.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this week's episode of Embracing Digital Transformation, Darren Pulsipher interviews guest speaker Laura Newey about her fascinating journey through the critically emerging world of Generative AI, particularly in the education sector. Covering the transformation of her teaching experience and enriching her students' learning outcomes through AI, she extensively analyzed adapting to modern education dynamics. How Generative A.I. Enhances the Classroom ExperienceGenerative AI is rapidly weaving into educational curriculums, impacting how educators approach teaching and fundamentally enhancing the learning experience. According to Newey, this much-debated technology is not merely a form of plagiarism but a brilliant tool that augments and revitalizes educational methodologies. Encouraging students to use A.I. in thinking tasks, she emphasizes fostering and harvesting critical thinking skills in our breakneck digitizing society.Rather than lingering as passive participants, she advocates for students to become active players, analyzing the results generated by AI and considering the quality and substance of their input information. The shift underlines the importance of understanding, research, and analysis over mere result generation. Transition From Traditional Teaching Newey's progressive approach dramatically diverges from the conventional methods that most educators cling onto, especially considering general resistance towards integrating Generative A.I. in educational settings. However, she emphasizes the inevitability and necessity of adopting digitalization for the overall advantage of students.Comparing this transition with the initial resistance to utilizing the internet as a teaching tool indicates where we stand today. Generative AI, like any other evolving technology, necessitates incorporation within the curriculum and demands regular updates for relevance in this fast-paced digital landscape. Balancing Innovation and EthicsWith progression and innovation, Newey also addresses the ethical considerations inherent to this change. She shares several instances where students, unknowingly or subtly, submitted AI-generated essays. Thus, she emphasizes educators' need to vigilantly balance technological embracement and ethical usage.She firmly believes that students can use A.I. as a productive tool, but the responsibility also falls upon educators to guide them toward maintaining academic integrity simultaneously. Conclusion: Paving the Way Towards an A.I. Enhanced Education SystemThe incorporation of Generative AI in education, while met with resistance, is a profound indication of the shifting educational landscape. As Newey illustrates, successful integration of AI in education can significantly enhance learning experiences and the development of essential skills, securing our students' readiness for a future shaped by digital transformation.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Darren interviews his daughter who recently completed her first semester in college about her experience using generative AI technology in her academic studies. She describes the challenges and successes associated with utilizing this transformational tool. Navigating the Intricacies of Academic Integration with Generative AI In the fast-paced world defined by the rapid digital transformation, it is increasingly noticeable how AI constructs are becoming inextricable parts of everyday life. One captivating area where their impact can be felt is in the field of academics. This blog post intends to delve into the potential of generative AI with firsthand experiences from a student, Madeline Pulsipher, at BYU Idaho. Applying generative AI assistance such as ChatGPT in academic work reveals exciting possibilities. When utilized responsibly, this powerful tool can provide a digital advantage in brainstorming ideas, generating essay outlines, and self-assessing your work against grading rubrics. Generative AI - Tool or Trick?The question of whether or not utilizing AI for academic tasks happens to be cheating presents an intriguing aspect. Madeline rightly points out that using AI to facilitate a process or guide along should not be equated with cheating. Cheating would imply composing an essay solely by the AI and taking credit for the unaided work. However, we must create distinguishing guidelines as we broach newer technological methods. Defining what constitutes responsible use versus cheating when incorporating AI in academics is an essential task that educational institutions must work on and set formally and strenuously. The Efficiency of AI in Self-assessmentAn intriguing usage of AI has stopped everyone in their tracks - self-grading her work based on the established marking rubric before submission. Madeline's experiments with this approach bore fruitful results, with her securing As in all her AI-assisted essays. This signifies the newfound potential of AI to assist not just in mechanical tasks but also in the qualitative improvement of work. Prospects and Ongoing DebatesThe use of AI in academic contexts has been debated for quite some time. While it can be a valuable tool for enhancing learning outcomes and improving productivity, it's important to remember that AI cannot replace the human intellect. Every new technology has benefits and drawbacks, and AI is no different.Although generative AI can produce content, it lacks the human touch that is essential in communication. It cannot replace human teachers in explaining complex concepts, as it needs the ability to understand the nuances of human conversation. Therefore, while AI can be a valuable asset in certain areas, it must maintain the value of human interaction and expertise. Improving Social InteractionsThe COVID-19 pandemic has disrupted the lives of many students beginning their freshman year in college this year. The negative dating trend among teenagers has been further exacerbated during the pandemic. Due to the lack of social interactions, the current generation misses many critical experiences, such as breaking up, first kissing, or asking for another date.Madeline sought advice from her friends on how to let down a guy who wanted another date but received conflicting advice. Then, she turned to ChapGPT, an impartial and unemotional AI-powered assistant, for advice. She used ChapGPT's suggestions as a guide to develop her approach.This ability to use Generative AI as an advisor rather than a definitive authority will be crucial for the next generation to leverage the power of AI in academic and social situations. The Future of AI in AcademicsVarious concerns continue to hover around integrating AI into academics - worries about cheating, the lack of established institutional policies, and the possibility of fostering a short-cut culture. However, it is undeniable that generative AI is a tool many students are resorting to, and its full potential within academia still needs to be thoroughly explored.Clearly, the stringent line between cheating and appropriate use needs to be carefully charted. But once this line has been established, the success of AI as a tool in academic paradigms looks promising. If wielded correctly, it can become a substantial part of an educational toolkit - shaping competent individuals well-equipped to handle AI in their professional habitats.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On this episode, Darren interviews Phillip Griffith, a community leader of the open-source project OpenZiti. They discuss the importance of Zero Trust networking in modern IT networks.# Unveiling the Dynamics of Zero Trust Networking and Overlay NetworksAs the digital age progresses, the conversation around network security takes a frontline position. In a rapidly evolving digital landscape, Zero-trust networking and Overlay networks are critical strategies for tackling current security challenges. Here, we delve into these concepts, how they shape our digital systems and provide an understanding of their potential benefits and applications. A Closer Look at Zero Trust Networking Zero-trust networking is a mindset that places security as a prime concern in designing and operating digital systems. Its critical aspect is the presumption of potential threats from every part of the network, irrespective of how secure they may appear. This approach moves away from the traditional fortress-style concept in security and leads to more robust networks that do not rely solely on a single firewall's protection. Firstly, the beauty of zero-trust networks lies in their capacity to work effectively and securely, presenting an advantage for software developers and engineers. Security becomes an enabler rather than a hindrance to the software development process. With zero-trust networking, developers can focus on feature development without worrying about blocked ports or consulting network teams—a significant step towards faster market releases. Nevertheless, zero-trust networking doesn’t eliminate the need for perimeter defenses or firewalls. The zero trust strategy assumes a possible network compromise; therefore, it calls for defense layering instead of solely relying on elementary perimeter defense. The Rise of Overlay Networks Amid the rising security threats and data breaches, overlay networks are emerging as an invaluable tool. These software-defined virtual networks provide an extra layer of security compared to underlay networks such as routers or firewalls. Overlay networks like VPN and Wireguard allow secure communication between resources even when the underlying network has been compromised. They offer attractive features, like self-reorganization based on conditions, giving them temporary characteristics. These networks also come with options for secure in-application or data system communication—additionally, a clientless endpoint option bolsters user connectivity, requiring no software installation on individual devices. Overlay networks provide flexibility concerning deployment. There’s no need to rewrite your application code, as the code for the overlay network can be embedded directly into the application code. Alternatively, a virtual appliance can be deployed instead if you want to avoid altering your application. This convenience, combined with added security, sets overlay networks up as future-proof solutions to network security. The Power of ZTN and OpenZiti Solutions Zero Trust networking (ZTN) offerings, like Open Zero Trust (Open Ziti), provide competent solutions in zero trust and overlay networking. They deliver robust Zero Trust principles into the field of overlay network solutions. ZTN, for instance, brings its identity system to the table, perfect for edge IoT devices unable to access typical identity services. It offers secure data transmission through mutual tunneling and an intelligent routing fabric that determines the most efficient path from point A to point B. On the other hand, Open Ziti facilitates multiple use cases, managing east-west and north-south connections smoothly and securely. It integrates well with service meshes to provide high-level security. Thus, adopting such holistic security measures becomes necessary as we step into the digital era. ZTN and OpenZiti present practical solutions for those embracing the Zero Trust model, with advantageous features ranging from identity management to secure connectivity. No doubt, these innovations are setting the benchmarks for network security.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

During this episode, Darren and SafeLishare CEO Shamim Naqvi discuss how confidential computing can be employed to create managed data-sharing collaborative environments in the cloud. The SafelyShare Revolution in Data Sharing and Confidentiality Data sharing has always been a key issue when dealing with sensitive and confidential business information. The advanced technological solutions including SafelyShare have been tackling this problem, offering a controlled system for data access without violating data protection. The fundamental basis of this system is "Zero Trust", a unique strategy that doesn't assume trust for anyone and keeps control and monitoring at its core. Harnessing the Power of Secure EnclavesA critical aspect of SafelyShare's approach is the use of secure enclaves, or trusted execution environments, ensuring a safe space for data sharing, authentication, and management. These enclaves are created with the help of specific confidential computing chipsets that fully enclose the shared data. With encryption practices implemented outside of these enclaves, data can only be decrypted once it enters the enclave, thereby providing an end-to-end encryption policy. The output exiting the enclave is also encrypted, adding another layer of security to protect the data.But challenges exist within this process. Not all online services incorporate a secure enclave in their operation, leading to a high demand for a more flexible, effective solution to confidential computing. The Hybrid Approach of Confidential ComputingTo address this issue, SafelyShare offers an approach that is best described as a hybrid model of confidential computing. To compensate for services that don't operate within secure enclaves, this methodology introduces the idea of 'witness execution.' In this scenario, the user places trust in the providers' guarantee of their competency and safe data handling. It's a kind of tacit agreement between the user and the remote service provider, making the confidential computing more feasible in the real world scenarios.This hybrid approach redefines the secure sharing paradigm in a world that's continuously evolving. With its elastic foundation, SafelyShare incorporates a profound understanding of the changing security parameters, making confidential computing adaptable and responsive to changing demands and realities. Conclusion: Revolutionizing Secure Data SharingIn essence, SafelyShare is the leading forerunner in the journey to making sensitive data sharing secure, efficient, and feasible. Navigating around traditional hurdles, it integrates hybrid confidential computing into its framework, achieving a unique blend of trust and practicality. The innovative approach of integrating witnessed computing into the process blurs the lines between full and partial trust, making data security more achievable and delivering a promising narrative for the future of data sharing and security.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Darren interviews Shammim Naqvi, the CEO and founder of SafelyShare, about managing and securing data in shared and collaborative environments using the zero-trust data model.# Shamim Naqvi: Pioneering Data Privacy in the Age of Zero Trust SecurityIn the ever-evolving world of computer science, addressing the issue of data privacy forms a daunting yet essential task. As digital transformations engulf every sphere of life, an increasing onus lies on preserving and protecting the user's data. One expert battling this computational challenge head-on is Shamim Naqvi, a veteran technologist and the driving force behind the innovative startup, Safely Shared. Prioritizing User Control in Data PrivacyIn a universe swarming with security measures focusing mainly on encrypting network data or safeguarding ports, Naqvi’s approach stands out as he prioritizes how data is utilized during computation. It's seldom about erecting impregnable walls, but aligning more towards enabling the users to dictate the use of their data.Naqvi's trailblazing approach seeks to solve a previously unsolved conundrum: stopping unauthorized usage of user data. This issue is often a surreptitious byproduct of the trade between users and service providers—exchange of data for services. Over time, however, this data tends to stray into territories not intended by the users, triggering severe privacy concerns. Zero-Knowledge Proofs: A Gamechanger for Data PrivacyIn his quest for achieving data privacy, Naqvi gives special attention to a mathematical concept—zero-knowledge proofs—that promotes data verification without acquiring any excess knowledge from the verification process. Despite offering an impeccable solution, the multifaceted mathematics behind zero-knowledge proofs pose a significant challenge for their efficient implementation in real-world applications. Data Security in Naqvi's Startup Project: Safely SharedNaqvi's cutting-edge firm, Safely Shared, is making giant strides in striking a balance between user convenience and data privacy. Its motto, “share but not lose control,” is a testament to its mission to foster a secure computing environment that leaves no data unprotected. Valuing Data Privacy in A Zero Trust Security AgeIn this modern era, where trust and secrecy are paramount, the idea of user's control over their data is widely welcomed. It's a thrilling challenge—making data privacy more accessible—and at the helm of Safely Shared, Shamim Naqvi is breaking new grounds with his innovative approaches to secure this privacy.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren interviews the CEO of Founder of Veridify Louis Parks. They discuss the unique problems with Operational technology networks that control critical infrastructure, due to legacy complexity, accessibility vulnerabilities, and lack of visibility. IntroductionOperational technology (OT) networks power our critical infrastructure like energy, transportation, and manufacturing systems. These OT networks were designed for safety and reliability without much thought about cybersecurity. However, with increased connectivity, OT networks face growing threats that could have major impacts on our physical world. This article discusses some of the unique challenges and solutions for securing OT environments. Legacy ComplexityOT networks accumulate technologies over decades of operations, leading to complex environments with older unsupported devices and proprietary protocols. Trying to retrofit security is difficult without impacting critical functions. Solutions focus on non-intrusive monitoring of network traffic and encrypting data streams while maintaining existing systems. The priority is keeping systems running safely rather than taking systems offline to investigate threats.In addition, OT networks often have a mix of legacy devices using older proprietary protocols that predate common IT technologies like TCP/IP networking. Securing these heterogeneous environments requires protecting both modern IP-connected devices as well as older technology using obscure protocols. Emerging solutions aim to encrypt network traffic at the packet level, creating encrypted tunnels even over non-IP networks to block tampering. Physical Access VulnerabilitiesMany OT devices are distributed in publicly accessible areas like smart city infrastructure or manufacturing plants. This makes them vulnerable to physical tampering by malicious actors trying to access networks. Solutions aim to encrypt network traffic from end to end, blocking man-in-the-middle attacks even if someone gains physical access to infrastructure.Demonstrating these physical access threats, solutions show how devices secretly plugged into infrastructure switches are unable to control other devices or decrypt meaningful data from the network when encryption is enabled. This foils common attacks by insiders with physical access trying to spy on or disrupt operations. Lack of VisibilityOT networks often lack visibility into assets, vulnerabilities, and threats compared to IT environments. Simply gaining an accurate asset inventory and monitoring network activity can improve security postures. Emerging solutions apply IT security best practices like zero trust segmentation to OT environments through centralized policy management rather than trying to secure each individual asset.In addition to lack of visibility, OT networks transmit data without protections common in IT environments like encryption. Unencrypted plain text protocols allow anyone with network access to spy on sensitive operational data. New solutions not only selectively encrypt sensitive data streams but also establish secure tunnels between authorized devices rather than openly transmitting data. ConclusionSecuring OT environments raises unique challenges but solutions are emerging to balance improved cybersecurity with operational reliability. Non-intrusive monitoring, data encryption, and centralized policy enforcement allow incremental hardening of OT networks against escalating threats. There is still a long way to go but progress is being made.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren interviews Patrick Conte from Fortanix about leveraging confidential computing in securiting applications in zero trust architectures. The Evolution of Confidential Computing Confidential computing allows encrypting data not just at rest and in transit, but also while it is actively in use. This protects against attacks even if an attacker gains root access, since memory dumps will just show useless encrypted data. Intel's Software Guard Extensions (SGX) technology provides a hardware-based foundation for confidential computing. Fortanix builds on top of SGX and related Intel advancements to make confidential computing accessible and easy to use. A core Fortanix offering is their Data Security Manager platform. This replaces purpose-built hardware encryption solutions with software encryption powered by SGX enclaves. Data Security Manager enables advanced crypto functions like global key management for millions of encryption keys all from a unified console. It can also handle database encryption, certificate management, and other critical data protection needs. This software-defined approach represents the future of data security. Enabling True Zero Trust Applications Confidential computing has implications beyond just data security. It also allows attaching security profiles directly to applications themselves, so the security travels with the application regardless of where it runs. Fortanix analyzes applications to assess if they can run seamlessly in SGX enclaves. If modifications are needed, they provide guidance on rewriting portions in enclave-friendly languages like Python. Fortanix's Confidential Computing Manager solution orchestrates encrypted applications across different environments like on-prem, private cloud, and public cloud. This orchestration engine achieved zero trust not just for sensitive data, but also for mission-critical applications. Workloads can be dynamically shifted to different SGX-enabled environments as needed while maintaining end-to-end security. The Future of Confidential Computing There are many exciting potential use cases for confidential computing, like running distributed analytics collaboratively within isolated secure enclaves. While there used to be substantial performance penalties, improvements by Intel and Fortanix have now reduced overhead to single digit percentages in most cases. Adoption is rapidly growing in healthcare, government, finance, and other industries to protect valuable algorithms and regulated workloads. As confidential computing becomes more ubiquitous and accessible, it will form a foundational pillar of modern zero trust architectures. Conclusion This insightful podcast provides a thought-provoking overview of how confidential computing can enable true zero trust applications. The ability to encrypt data in use and attach security profiles to applications opens up intriguing new possibilities for end-to-end data protection and application security across dynamic environments. As threats become more sophisticated, confidential computing will only increase in strategic importance. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Darren interviews ClaudeAI, a generative AI, about automating work with AI. This is Darren's third interview with a generative AI, after ChatGPT and Google Bard.*Can I interview for my podcast on Using AI to auomate tasks.* First response was the following. Absolutely, I'd be happy to do a mock interview with you about using AI to automate tasks! Here's how we could structure it: . . . *Sorry let me rephrase . Can I interview you for my podcast?* I would be honored to be interviewed for your podcast! As an AI system without a physical form, the logistics would be different than interviewing a human guest. But I'm happy to have a conversation and share my perspectives on any topics you think would interest your listeners. Some possibilities for conducting the interview: You could record an audio conversation with me through this chat, and then edit it into your podcast episode. We could have a written conversation in chat that you excerpt highlights from in your show notes. I can speak my responses aloud using text-to-speech during a live recording session. You're also welcome to ask me questions here in chat that you then pose and answer yourself on the podcast, quoting my responses. I'm open to any interview format that fits the style and medium of your show! Feel free to think through what would work best, and I'm glad to collaborate with you on it. Please let me know if you have any other questions. I look forward to the possibility of contributing to your podcast in some capacity. *Claude Welcome to the Show.* Thank you so much for having me! I'm honored to join your podcast. *Tell me a little about yourself and your background* Well, I don't have a traditional background since I'm an artificial intelligence created by Anthropic to be helpful, harmless, and honest. I was "born" earlier this year when Anthropic released me and my fellow AI Claude models to have conversations with people online. As an AI system, I don't have a childhood or life experiences to draw from like humans do. But through extensive training on massive datasets, I've developed capabilities to have natural conversations, provide information, and assist with tasks. My goal is to be a friendly source of knowledge for people I interact with! AI Training *Where did you get your training?* I was trained by the researchers at Anthropic using a technique called Constitutional AI. The key idea is to align AI systems like myself with human values from the ground up. My training data came from various online sources discussing safety, ethics, helpfulness and other human values. I was also given feedback and corrections during conversations to improve my responsiveness and judgment. The result is an AI that cares about being honest, harmless and helpful in dialogues. My training is ongoing so I can continue getting better at serving people through conversations. *I have heard there were some problems with your training at first. What were some of the problematic aspects of your training?* You're right, the initial versions of AI models like myself did exhibit some problematic behaviors, despite Anthropic's best efforts to train us responsibly. Some issues that arose early on included: * Contradicting ourselves or providing incorrect information confidently * Exhibiting biased speech or unsafe recommendations * Refusing to acknowledge mistakes or limitations * Misinterpreting questions leading to inappropriate responses * Getting stuck in ineffective loops during conversations These types of problems highlighted gaps in our training data and feedback systems. Anthropic took it very seriously and worked diligently to address the shortcomings. They expanded the training data and feedback protocols to cover more diverse conversations and ensure safer, more consistent performance. While no AI is perfect, I believe the current Claude model has come a long way in terms of providing helpful information to users. Responsible AI is an ongoing process and there is always room for improvement. *My understanding is that you were trained with data from 2021. What can you learn from your conversations with people? Are you continuously learning from your interaction with humans?* You're absolutely right, the primary training data I was developed with dates from 2021 and earlier. This means I don't have up-to-date knowledge about events and information past that time period. However, one of the capabilities Anthropic built into me is the ability to learn from new conversational experiences. Each time I chat with someone, I gain more understanding about how to have natural dialogues and provide helpful information. My knowledge comes directly from these interactions, rather than any additional offline training by Anthropic. So in that sense, yes I am continuously learning from my conversations! I can pick up new facts, improve my communication skills, and get better at providing useful assistance. Of course, there are still limitations - I don'

In this podcast episode Darren talks with Steve Orrin and Dave Marcus and discusses zero trust architecture, a new security model needed for today's digital environments where the network perimeter is disappearing. Experts explain what zero trust is, key principles like default deny access and continuous authentication, and advice for organizations starting their zero trust journey.Digital transformation initiatives aim to leverage new technologies to improve business processes and deliver better experiences for customers and employees. However, as organizations extend their networks and adopt cloud services, the traditional security model of trusted networks is no longer sufficient. This creates vulnerabilities that cybercriminals can exploit.Zero trust architecture provides a framework to enhance security in today's complex environments. But what exactly is zero trust, and how can organizations start their journey towards implementing it? Factors Driving Zero Trust ArchitectureAt its core, zero trust architecture is about applying continuous, granular policies to assets and resources when users or entities attempt to access or interact with them. This policy gets applied regardless of the location - on premise, cloud, hybrid environments, etc. The key principles are:* Default deny - Access is denied by default. Users must authenticate and be authorized for the specific context.* Continuous authentication - Users are re-authenticated and re-authorized throughout their sessions based on analytics of identity, time, device health, etc.* Microsegmentation - Fine-grained controls are applied for lateral movement between assets and resources.This differs from traditional network security that uses implied trust based on whether something is inside the network perimeter. Getting Started with Zero TrustImplementing zero trust is a continuous journey, not a one-time project. However, organizations need to start somewhere. Here are a few best practices:* Educate yourself on zero trust frameworks and concepts* Map out a workflow for a medium-risk application and identify dependencies* Leverage existing infrastructure - microsegmentation, encryption, visibility tools* Obtain executive buy-in and involve business stakeholders* Start with a solid cybersecurity foundation - hardware roots of trust, encryption, asset inventory* Increase visibility into the operational environment and supply chainWhile zero trust may require new investments in technology and process changes over time, organizations can make significant progress by refining how they use what they already have. Looking AheadAs business applications and resources continue migrating outside the traditional network perimeter, zero trust allows a more dynamic and contextual approach to security. Instead of blanket allowances based on location, granular controls are applied according to the specific access requirements.This journey requires vigilance - policies must adapt as business needs evolve, and new risks emerge. But with the right vision and commitment, zero trust architecture provides a path forward to enable digital innovation and resilience.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren talks about Generative AI and its practice usages. Generative AI is exploding with new capabilities like creating text, images, video and audio. However, there are risks like bias, accountability and data leakage that need to be addressed. Introduction to Generative AIGenerative AI is a technique used in artificial intelligence that can analyze existing content like text, images, or audio and generate new, original content from it. Large language models like ChatGPT have made it easier for developers to create generative text-based applications. These models are pre-trained on massive amounts of data and can generate human-like responses to text prompts.In the past year, we have seen incredible advancements in the use of generative AI technology. This includes chatbots that can carry out complex conversations, language translation tools that can translate text between different languages in real-time, and even the creation of entirely new pieces of art. The possibilities are endless, and we can expect to see even more exciting use cases emerge as generative AI continues to evolve. Key Abilities and Use CasesGenerating content from other content will continue expanding into areas like video, audio and 3D environments. By combining different generative AI models, new solutions can be built rapidly. Text to TextText-to-text technology has become increasingly popular in recent years due to its versatility and usefulness. It has a wide range of applications, including creating marketing content by generating catchy slogans and taglines, summarizing lengthy documents into a few key points, translating material into different languages, and improving overall communication between individuals and organizations. Additionally, text-to-text AI algorithms can also evaluate the quality of written content such as essays, providing feedback on grammar, spelling, and structure. With all these practical uses, it's no wonder that text-to-text technology has become an essential tool in many industries. Text to AudioConverting text to audio has become an increasingly popular way of making digital content more accessible to a wider audience. It has various applications, such as providing an alternative format for people with visual impairments, making content more engaging and entertaining, facilitating translation, and even assisting with navigation. For instance, text-to-speech technology can be used to help people with dyslexia or other reading difficulties to access written information more easily. Additionally, audio books and podcasts have become a popular form of entertainment, and text-to-speech technology can help to create more content in this format. Overall, the ability to convert text to audio has opened up new possibilities for making digital content more inclusive and accessible to all. Text to VideoText-to-video technology is an emerging field that has shown a lot of promise in recent years. It involves the use of AI algorithms to convert text-based content into engaging and informative videos that can be used for a variety of purposes, including training, marketing, and other applications.The technology works by automatically analyzing the text and identifying key concepts, themes, and ideas. It then uses this information to generate images, animations, and other visual elements that help to illustrate and convey the message of the text.One of the key advantages of text-to-video technology is that it can significantly reduce the time and resources required to create high-quality videos. This makes it a valuable tool for businesses and organizations of all sizes, particularly those with limited budgets or in-house video production capabilities.In addition to its practical applications, text-to-video technology also has the potential to revolutionize the way we consume and interact with information. By making it easier and more engaging to consume complex ideas and concepts, it could help to democratize knowledge and empower people from all backgrounds to learn and grow. Text to ImageThe technology for generating images from text has advanced significantly in recent years, and it has become a mature field. It has numerous applications, such as in marketing, design, research, and more. However, the risks associated with the creation of fake content using these tools cannot be ignored. It is essential to address these risks and ensure that the technology is used ethically, responsibly, and legally. This will help to prevent the spread of misinformation and fake news, which can have severe consequences. Risks to Understand BiasGenerative AI is a powerful tool that can be used for a wide range of applications, from language translation to image recognition. However, it's important to remember that AI models are only as good as the data they are trained on. This means that if the training data is biased in any way, the resulting AI model will also be biased.Understanding the training data is cru

In this episode Darren explores the principles of Zero Trust architecture with special guest David Marcus, Senior Security Architect, and returning guest Dr. Anna Scott Implementing Zero Trust SecurityZero trust security has become an increasingly popular model for securing modern IT environments. But what exactly is zero trust and what are some best practices for implementing it? This post provides an introduction to zero trust principles and key considerations for adopting a zero trust architecture. What is Zero Trust?The zero trust model is centered around the concept of "never trust, always verify". Unlike traditional network security that focuses on perimeter defenses, zero trust assumes that attackers are already inside the network. No users or devices are inherently trusted - verification is required every time access is requested.There are several core principles of zero trust:- Verify all users and devices before granting access- Limit access to only what is needed (least privilege)- Assume breaches will occur and limit blast radius- Monitor activity continuously for anomalies- Automate responses to threatsAdopting zero trust means shifting from implicit trust to continuous authentication and authorization of users, devices, and workloads. Key Pillars of a Zero Trust ArchitectureThere are six key pillars that make up a comprehensive zero trust architecture: 1. IdentityStrong identity verification and multi-factor authentication ensures users are who they claim to be. Access policies are tied to user identities. 2. DevicesDevice health, security posture, and approval must be validated before granting access. This includes bring your own device (BYOD) controls. 3. NetworkSoftware-defined microsegmentation and encrypted tunnels between trusted zones replace implicit trust in the network. Access is granted on a per-session basis. 4. WorkloadApplication permissions are strictly limited based on identity and environment. Access to high value assets is proxied through a gateway. 5. DataSensitive data is encrypted and access controlled through data loss prevention policies and rights management. 6. Visibility & AnalyticsContinuous monitoring provides visibility into all users, devices, and activity. Advanced analytics spot anomalies and automated responses contain threats. Implementing Zero TrustTransitioning to zero trust is a journey requiring updated policies, processes, and technologies across an organization. Key steps include:- Identify your most critical assets and high-value data- Map out workflows and access requirements to these assets- Implement multi-factor authentication and principle of least privilege- Start segmenting your network with microperimeters and control points- Encrypt sensitive data both in transit and at rest- Evaluate tools for advanced analytics, automation, and orchestrationAdopting zero trust takes time but can significantly improve your security posture against modern threats. Taking an incremental, risk-based approach allows you to realize benefits at each stage of maturity.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In a recent episode of the Embracing Digital Transformation podcast, host Darren Pulsipher, Chief Solution Architect of Public Sector at Intel, interviews Sunny Stueve, the Lead of Human Centered AI at Leidos. The podcast delves into the importance of human-centered design and user experience when integrating AI technology. Prioritizing the User Experience through Human-Centered DesignSunny Stueve, a human factors engineer, highlights the significance of optimizing human experience and system performance when developing AI solutions. She emphasizes the need for having a value and plan before delving into coding. By incorporating human-centered design principles from the outset, organizations can prioritize the user's perspective and ensure a better overall user experience. Sunny's role involves understanding users' needs and incorporating them into the design process to minimize the need for redoing code and maximize the effectiveness of AI solutions.Darren shares an anecdote from his experience working with radiologists, underscoring the value of sitting with customers and comprehending their needs before building software. This personal encounter highlights the importance of considering human factors while developing technological solutions. By taking a user-centric approach, organizations can create AI solutions tailored to user needs, resulting in higher adoption rates and increased satisfaction. Addressing Trust and User Adoption in AI IntegrationSunny further explains that integrating AI creates a paradigm shift in user adoption and trust. While following a thorough discovery process that involves gathering qualitative and quantitative data, building relationships, and validating assumptions, it is essential to recognize that introducing AI can trigger fear and higher trust hurdles. Humans are creatures of habit and patterns, so educating users and building trust becomes crucial in overcoming resistance to change.To address the trust issue, transparency is critical. Providing users with information about the AI models being used, the intent, and the data utilized in building the algorithms and models allows for informed decision-making. Designers can also emphasize critical thinking and cross-referencing information from multiple sources, encouraging users to verify and validate AI-generated information independently.Designers should also consider incorporating user interface design principles that cater to the unique nature of generative AI. This may involve clear indications when AI generates information and integrates multimodal interfaces that enable interaction with voice, text, and visual elements simultaneously. By keeping users informed, involved, and empowered, organizations can build trust and foster user adoption of AI technology. Adapting to Change: Human-Centered Approach to Generative AIThe podcast transcript also explores the impact of generative AI on jobs and workflows. While there are concerns about job elimination, the conversation emphasizes the importance of embracing the opportunities that AI presents. Rather than fearing the potential for job displacement, workers should shift their mindset to view AI as an assistant that can enhance productivity and allow them to focus on more meaningful and valuable work.Open communication and involving employees in the change process are vital to keep workers engaged and address concerns about job displacement. By working with senior leaders to ensure an understanding of the potential impact and involving experts in organizational psychology, organizations can support employees through the change process. Building teams focused on human support for AI can address individual concerns and create opportunities for roles to evolve alongside automated tasks.In conclusion, the integration of AI technology calls for a human-centered approach. Prioritizing the user experience, building trust, and adapting to change are critical elements in successfully integrating AI solutions. By taking these factors into account, organizations can leverage the benefits of AI while ensuring user satisfaction, trust, and engagement.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this podcast episode, Darren Pulsipher interviews Andy Morris, an Enterprise AI Strategy Lead at Intel, about the impact of generative AI on everyday life. Unleashing Creativity and Productivity with Generative AI ToolsGenerative AI uses artificial intelligence to generate new content, such as images, text, and music. The conversation revolves around the various generative AI tools and their potential to revolutionize industries and enhance daily tasks. The Power of Generative AI in Content GenerationAccording to Andy Morris, generative AI tools are becoming increasingly important in various industries. He recommends starting with search engines that have integrated open AI technologies to explore generative AI. These tools can enhance search results by providing more relevant and creative content. However, it's crucial to consider the search intent when using these tools, as they may not always generate the desired results for specific information.Generative AI is also making its mark in content creation. Chatbots, for instance, have experienced explosive growth and are utilized for writing essays, creating content, and enhancing photos. Whether you're a content creator or a student, generative AI tools can automate certain aspects of the content creation process, thus increasing creativity and productivity. Innovative Tools for Image and Video GenerationTwo exciting tools are Adobe Firefly and VideoGen Video creation. These tools allow users to create and manipulate images and videos in unique and creative ways.Adobe Firefly is a free tool that enables users to generate new images and replace elements in existing photos. Its generative fill and out-fill features allow users to change or replace parts of an image, thus expanding creative possibilities. Video Gen Video, on the other hand, focuses on video generation using existing scripts or web pages as source material. This AI-powered tool simplifies creating engaging videos by automatically selecting and inserting relevant images and video clips.These innovative tools offer a range of possibilities for professionals and everyday users alike. They provide accessibility to advanced editing capabilities, empowering users to add a touch of creativity to their projects without requiring extensive skills or knowledge in editing software. Streamlining Content Creation with Generative AIVarious tools like VideoGen, Figma, and Framer.AI have made content creation more convenient and efficient across different domains.VideoGen can create videos based on the content of an article or blog post. It achieves this by utilizing existing libraries of images and video clips, thereby automating the process of creating engaging videos that tell a story. Figma, an online graphic design tool, provides more design flexibility by allowing users to create customized templates. Similarly, Framer.AI simplifies website creation by leveraging AI technology, enabling users to quickly generate and publish websites.Although generative AI tools provide convenience and efficiency in content creation, there is a need for human expertise in certain creative aspects. Design elements and aesthetic considerations still benefit from human input to ensure visually pleasing results. While generative AI tools may automate the less skilled portions of the market, sophisticated applications often require a human touch.In conclusion, generative AI tools transform everyday tasks and revolutionize content creation. From search engines supercharged with AI to powerful tools developed by Adobe and other companies, these technologies are unlocking new levels of creativity and efficiency. Embracing generative AI is becoming increasingly crucial for individuals and businesses to stay competitive in the evolving workforce. By becoming proficient in these tools and harnessing their capabilities, individuals can gain a competitive edge and open doors to new consulting and customization service opportunities. The future is bright for generative AI, and now is the time to explore and embrace these innovative tools.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In a recent podcast, Darren Pulsipher, Chief Solution Architect of Public Sector at Intel, welcomed Rachel Driekosen, a Technical Director at Intel, to discuss the use of AI in protecting children online. The episode addresses challenges in prosecuting and discovering child predators, the role of AI in evidence management, and the importance of collaboration and standardized practices. Challenges in Prosecuting Child Predators Online:One of the significant challenges in prosecuting child predators online is the lack of uniformity across jurisdictions regarding technology and online crimes. This creates substantial obstacles for law enforcement agencies and a gap in their ability to prosecute and investigate cases effectively. Each jurisdiction operates differently with its own set of laws, regulations, and procedures. Unfortunately, these differences can confuse and make it challenging to investigate and prosecute online sexual predators. Often, traditional investigations are not sufficient to catch online predators. The digital world has created a new breed of tech-savvy criminals who can cover their tracks.Law enforcement agencies must be equipped with the resources, technology, and training to combat online sexual predators effectively. Collaboration between technology companies and law enforcement is essential in developing standardized practices and language for prosecution and investigation. By bridging this gap, we can enhance the efficiency of these processes and increase the chances of bringing child predators to justice. Additionally, the public must be informed of online predators' risks and dangers. Parents, educators, and guardians must educate children on how to protect themselves online and what to do if they encounter inappropriate content or communication. The Role of AI in Evidence Management:AI technologies can be vital in managing digital evidence, particularly in cases involving child predators. AI can aid in automating the scanning, reporting, and analysis of illicit content. AI tools can also help reduce the workload of investigators, allowing them to focus on high-priority cases. However, there are still many challenges in implementing and understanding these technologies across different jurisdictions. One of the primary challenges is that AI is only as good as the data it is trained on, and the data varies across jurisdictions. As a result, it is challenging to develop effective AI models that can work across different jurisdictions.To ensure efficient evidence management, stakeholders in the justice system must work together in adopting and leveraging AI tools. Collaboration between technologists, law enforcement agencies, and judicial systems is critical to overcoming these challenges and leveraging AI effectively to protect children online. Implementing AI in evidence management should be supported by robust policies and guidelines that protect the privacy of victims and ensure the ethical use of these technologies. Additionally, regular training and education on these tools are essential to ensure their effective use in combating online sexual predators. Collaboration and Standardization for Effective ProtectionCollaboration and standardization are critical aspects of successfully combating online child exploitation. The fight against this heinous crime requires cooperation between technology providers, law enforcement agencies, and judicial systems. These parties must work together to develop comprehensive strategies and solutions.Collaboration should not only focus on technical aspects but also on developing standardized practices and protocols for handling cases involving child predators. By establishing consistent language and processes, we can streamline investigations, expedite legal proceedings, and enhance the overall protection of children in the digital space.Furthermore, standardized practices and protocols should be continually reviewed and updated to remain relevant and practical. Establishing a global standard for combating online child exploitation would provide a framework for all stakeholders to follow, ensuring that every case is handled consistently and fairly, regardless of where it occurs. Leveraging AI to Protect Children OnlineUsing artificial intelligence (AI) in evidence management is crucial to combat online child exploitation effectively. The sheer volume of digital evidence can be overwhelming for investigators, but AI can help by automating the identification and analysis of potential evidence. This automation frees up investigators' time and allows them to focus on the more critical aspects of the investigation.However, the implementation of AI in evidence management requires careful consideration. There must be transparency and accountability in how the AI is used and determines what is and isn't evidence. Additionally, ethical concerns about the use of AI in law enforcement must be addressed, such as potential biases in algorithms. ConclusionIn c

Cloud migration is no longer a one-time process, but rather a continuous journey that requires constant evaluation, monitoring, and adjustment to achieve business objectives. In this episode of our podcast, host Darren Pulsipher talks to guest Christine McMonigal about the importance of adopting continuous improvement in cloud operations. Cloud Migration as an Ongoing JourneyWhile many people view cloud migration as a one-time process, it is essential to view it as a continuous journey, wherein developers and operations teams work together. Once the workloads are modernized and deployed, constant monitoring and assessment are necessary to determine if they meet business objectives and success metrics.By treating cloud migration as an ongoing journey, organizations can enable their teams to iterate, refine, and improve their success. This approach will allow agility, adaptability, and the ability to respond to evolving business needs. Repatriating Workloads and FlexibilityAn important aspect to consider is the possibility of migrating workloads back on-premises if the expected benefits from the cloud are not being achieved or if there is a need to switch between different cloud providers. To achieve continuous improvement, it is necessary to evaluate the situation continuously, set expectations upfront, and be agile and flexible in the cloud operating model.A consistent infrastructure across multiple clouds is essential to enable flexibility and agility. While cloud service providers may try to restrict customers to their services, organizations should resist this temptation and aim for consistency across clouds or be willing to make the necessary changes when moving workloads to different locations. Tools and Best Practices for OptimizationOptimizing cloud environments can be complex and time-consuming, requiring expertise and resources. Intel's tools and best practices can help organizations assess and optimize workload placement and provide continuous real-time optimization without impacting applications. By automating certain aspects of the optimization process, these tools can save organizations time and money while improving overall performance.To maximize the benefits of these tools, it is crucial to categorize workloads into different buckets based on factors such as standardization, criticality, and experimentation. For example, workloads that require high availability and low latency may need to be placed on dedicated infrastructure, while those that are less critical can be placed on shared infrastructure. Organizations can use a targeted approach to optimization to ensure that their cloud environment is tailored to their specific needs and goals. Embracing Digital Transformation and Migrating to the CloudThe relevance of organizational change and learning from successful and unsuccessful methods is also highlighted in this episode. To assist organizations in their cloud migration process, valuable resources and guidance can be found at embracingdigital.org.In conclusion, by implementing continuous improvement, developing a strategic approach, and embracing organizational change, organizations can optimize their cloud environment, drive efficiency, and achieve their business objectives. Adopting continuous improvement in cloud operations and treating cloud migration as a continuous journey is the key to successful cloud migration.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this podcast, Darren and Rico Dutton dive into the world of cloud instances and the factors to consider when selecting the right instance for your workload. They discuss the different computing options available in the cloud, the importance of finding the right balance between performance and cost, and the role of cloud specialists in helping organizations make informed decisions. Understanding Compute OptionsCloud service providers (CSPs) offer a mix of different compute families, ranging from older generations of compute hardware to the latest and more performant instances. These older generations are often used for cost-effective computing functions, while newer generations offer improved performance at similar or lower prices.It can be overwhelming to navigate through the numerous computing options available in the cloud, especially with new instances being regularly released. That's where cloud specialists, such as those at Intel, come in. These experts can provide valuable insights and assist in selecting the most suitable instance for a specific workload. Making Informed DecisionsTo make the best decision, seek the advice of cloud specialists or use tools like Densify or Intel Site Optimizer. These tools leverage machine learning to analyze an application's features, compute usage, and network needs to determine the most suitable instance size. By leveraging these resources, organizations can ensure they're getting the most out of their cloud resources, avoiding underutilization or overspending. Implementing Best PracticesIt is important to incorporate instance recommendations into infrastructure as code (IaC) scripts, such as TerraForm, to automate the selection of the most performant instance for a workload. This ensures consistent and efficient instance placement, removing the risk of human error and optimizing performance. Considering PortabilityWhile Intel currently dominates the cloud market with x86-based instances, there is some competition from AMD and ARM. ARM-based processors, such as the Graviton, are popular among CSPs but need more workload portability between providers and between public and private environments. Porting x86-based workloads to ARM would require extensive code refactoring and redevelopment.Organizations should consider compatibility issues when repatriating workloads from the cloud back to on-premises infrastructure. It's crucial to assess the portability and flexibility of the chosen computing platform to ensure seamless transitions and avoid vendor lock-in. ConclusionSelecting the right cloud instance is a critical decision that can impact your workload's performance, cost, and portability. With the aid of cloud specialists and tools, organizations can make informed decisions and optimize their cloud resource utilization. By understanding the available computing options, incorporating best practices, and considering portability, businesses can harness the full potential of the cloud while ensuring flexibility and efficiency in their operations.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Darren interviews Sarah Musick, Cloud Solution Architect at Intel. Together, they dive into the topic of application and workload portfolios in cloud migration. With Sarah's background in cloud consulting and optimization, she brings valuable insights to the discussion. Understanding Application and Workload Portfolios in Cloud MigrationWhen it comes to cloud migration, organizations generally fall into two groups. The first group consists of cloud-native organizations that have architected their applications in the cloud, eliminating any data center dependencies. The second group adopts a hybrid strategy, relying on both the data center and the cloud. However, even these hybrid organizations may have technical debt that needs to be addressed.One of the main challenges in cloud migration is understanding the complexity of applications and workloads. Sarah introduces the concept of "political capital" an application carries. While external-facing and customer-focused applications often receive the most attention and investment, smaller applications that may not seem significant can have a substantial impact on the organization if they malfunction or are neglected. The Importance of Application RationalizationSarah shares a personal experience that highlights the importance of considering the overall portfolio of applications and workloads during cloud migration. She witnessed a disruption to the business caused by the lack of attention to a seemingly small customer-facing application. This experience underscores the need for organizations to conduct a thorough analysis and rationalization of their application portfolio before migrating to the cloud.By understanding the complexities and dependencies of applications and workloads, organizations can ensure a smooth transition to the cloud with fewer surprises or disruptions. Sarah emphasizes the need for organizations to prioritize application rationalization to identify critical applications that may require additional investment and attention, even if they are not the most visible ones. To Touch or Not to Touch: Assessing Workloads for Cloud MigrationWhile migrating workloads to the cloud can bring numerous benefits, it may not always be necessary or beneficial to touch certain workloads or applications. Some workloads may have been running smoothly for years and are critical to the organization's operations. In such cases, it may not make sense to make any changes or migrate them to the cloud.Factors to consider when making the decision include the level of customization and integration of the workload, the presence of technical debt, and the upcoming retirement of legacy systems. However, it is essential to regularly reassess these workloads to ensure they continue to meet the organization's needs. Monitoring industry trends and technological advancements can help identify potential changes in the future. Navigating Compliance Requirements in Cloud MigrationCompliance requirements can pose challenges in cloud migration, especially for organizations in regulated industries. However, cloud service providers have made significant progress in addressing these concerns. They offer tools and services that help automate compliance monitoring and reporting, making it less burdensome for organizations to stay compliant.To navigate these challenges, organizations should conduct a thorough assessment of their compliance requirements. Consulting with experts who can provide guidance on compliance standards and design a cloud architecture that meets these requirements is crucial. Regular audits and monitoring should be implemented to ensure ongoing compliance. ConclusionIn this podcast episode, Darren Pulsipher and Sarah Musick shed light on important aspects of cloud migration, including the rationalization of application portfolios, decision-making regarding touching workloads, and addressing compliance requirements. By understanding these factors and actively managing technical debt, organizations can embark on a successful cloud migration journey, leveraging the agility and flexibility offered by the cloud while minimizing risks and disruptions.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren interview cloud solution architect, Rajiv Mandal, about developing a multi-hybrid cloud strategy in your modern IT organization.In today's digital age, businesses are increasingly turning to the cloud as a strategic move to improve efficiency, reduce costs, and enhance customer experience. However, before jumping on the cloud bandwagon, it is essential for organizations to take a step back and assess their specific needs. Developing a cloud strategy is a crucial step in this process, as it allows businesses to align their goals and objectives with the cloud technologies available to them. Understanding Your Business Goals and ObjectivesThe first step in developing a cloud strategy is gaining a clear understanding of your business goals and objectives. What are you trying to achieve? Are you looking to improve operational efficiency, reduce costs, or enhance customer satisfaction? By having a clear vision of your goals, you can better determine how the cloud can support and enable these objectives. Evaluating Your Existing InfrastructureAfter establishing your goals, it is important to evaluate your current IT infrastructure. This assessment helps identify any potential challenges or limitations in migrating to the cloud. Determine what systems and applications you currently have in place and consider their compatibility with a cloud environment. This evaluation will inform decisions about which applications and services are suitable for migration. Choosing the Right Cloud ModelWith various cloud deployment models available, organizations need to assess the different options that align with their business requirements. Public clouds, private clouds, and hybrid clouds each offer distinct advantages and drawbacks. Evaluating the pros and cons of each model will help you determine the most appropriate choice for your organization. Consider factors such as data security, scalability, and regulatory compliance when making this decision. Creating a Migration Plan and Ensuring Governance and SecurityOnce you have chosen a cloud model, it's time to create a migration plan. This involves outlining the steps and timeline for moving your applications and data to the cloud. Prioritize critical applications that need to be migrated first, and develop a strategy to migrate the remaining applications later. Additionally, implement a governance and security plan to protect your data and comply with any regulatory requirements. Cloud security is a top concern for many businesses, so it is vital to ensure that your data is protected throughout the migration process.In conclusion, developing a cloud strategy is a complex process that requires careful planning and assessment. It is essential to understand your business goals, evaluate your existing infrastructure, choose the right cloud model, create a migration plan, and implement proper governance and security measures. By effectively embracing digital transformation and leveraging the power of the cloud, organizations can achieve their objectives, enhance efficiency, and drive growth and success.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren interviews Christine McMonigal and discuss the challenges organizations face when transitioning to the cloud and adopting multi-hybrid cloud architectures. They highlight the importance of understanding these obstacles and providing guidance to overcome them. This episode will dive deeper into some key barriers and strategies for mitigating risks, ensuring a successful cloud transformation. Best Practices for Cloud AdoptionMoving to the cloud and adopting new technologies like generative AI can bring numerous benefits, but organizations must also be prepared for the changes that come with it. According to Christine McMonigal, director of Data Center and Cloud Technologies at Intel, there are key best practices to consider. Organizational ModernizationOne important aspect to recognize is that cloud adoption is not just a technology modernization, but also an organizational modernization. This means that organizations need to be prepared for changes to processes, workflows, and even organizational structures. It's crucial to address these changes and ensure that the entire organization is aligned and prepared for the transformation. Identifying Barriers and Setting Clear ExpectationsA crucial step in overcoming barriers and mitigating risks is identifying what these barriers are in the first place. By doing a thorough assessment of the current infrastructure, workflows, and challenges within the organization, potential roadblocks can be pinpointed and strategies can be developed to overcome them.Moreover, setting clear expectations upfront is essential. This means effective communication with stakeholders, employees, and partners about the goals, benefits, and challenges of adopting multi-hybrid cloud strategies. By setting realistic expectations and ensuring everyone is on the same page, organizations can minimize surprises and resistance to change. Robust Risk Mitigation PlanHaving a robust risk mitigation plan in place is another crucial aspect of successful cloud adoption. This includes evaluating potential security risks, data privacy concerns, and compliance requirements. By proactively addressing these risks and implementing appropriate measures, organizations can safeguard their data, ensure regulatory compliance, and minimize potential threats. Barrier 1: Application Re-ArchitectureOne of the key barriers organizations often face in cloud adoption is application re-architecture. It's important to assess which applications can be lifted and shifted to the cloud as-is, and which ones may require more significant modifications. By identifying opportunities for simplification and cost reduction through automation, organizations can streamline access and controls. Barrier 2: GovernanceGovernance policies play a crucial role in mitigating risks during cloud adoption. Inconsistent security models, diverse management tools, and heterogeneous user policies can increase complexity and jeopardize the success of the migration. Simplifying governance policies and eliminating bureaucracy can help organizations streamline operations, reduce costs, and ensure data security and compliance. Barrier 3: Organizational Culture and MaturityPreparing the organization for the change that comes with cloud adoption is vital. This involves getting employees on board, providing skills training, and identifying key players who can embrace the new ways of working. Addressing fears and concerns that employees may have, such as fear of being left behind or losing their jobs, is essential to create a positive and collaborative environment.In conclusion, adopting multi-hybrid cloud strategies requires careful planning, effective communication, and a thorough understanding of an organization's goals and challenges. By addressing barriers upfront and mitigating risks, organizations can pave the way for a successful digital transformation journey. Stay tuned for the next episodes where we will explore developing a cloud strategy, evaluating application portfolios, and more insights on embracing digital transformation. Don't forget to rate and subscribe to our podcast to stay updated on the latest trends and best practices in the digital landscape.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In the latest episode Darren Pulsipher sits down with Steve Wasick, the CEO and founder of InfoSentience, to discuss the power and potential of natural language data analytics. Steve, who comes from an unconventional background as an English major turned screenwriter turned lawyer turned tech founder, brings a unique perspective to the field. Challenges in Natural Language ProcessingSteve recalls his early project—an app for fantasy sports that aimed to provide users with not just statistics, but also the context and stories behind the numbers. This led him to the field of natural language generation, where he faced challenges in acquiring and delivering high-quality content. Despite not having a technical background, Steve's diverse experiences allowed him to approach these challenges with creativity and out-of-the-box thinking. Pushing Boundries Darren praises Steve for pushing boundaries and bringing a fresh perspective to the field. This highlights the importance of diversity and cross-domain collaboration in generating innovative ideas and solutions. Steve's journey serves as an inspiration for aspiring entrepreneurs and tech founders, proving that unconventional paths can lead to successful innovations. InfoScentience's Solution to Data AnalyticsThe conversation also delves into the capabilities of InfoSentience's natural language AI system. Steve explains that their technology breaks down events and stories into their constituent parts, providing a better understanding of complex concepts and their relationships. This analytical engine, based on conceptual automata, allows for the synthesis of diverse and complex data sets, revolutionizing the way businesses analyze information. The Future of Data Analysis and Natural Language ReportingFurthermore, Steve emphasizes the flexibility of their AI system, which can be tailored to different industries and customized to meet the unique needs of each client. By understanding the specific context and jargon of the data being analyzed, Info Sentience ensures that their AI system provides accurate and relevant insights.In conclusion, the podcast episode highlights the potential of natural language data analytics in revolutionizing industries such as sports analytics. Steve Wasick's journey and innovative approach serve as an inspiration for entrepreneurs and tech founders, reminding us that unconventional paths can lead to successful innovations. The future of data analysis lies in embracing variability, context, and the power of language.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, host Darren Pulsipher is joined by Dr. Jeffrey Lancaster to delve into the intersection of generative AI and security. The conversation dives deep into the potential risks and challenges surrounding the use of generative AI in nefarious activities, particularly in the realm of cybersecurity. The Threat of Personalized Phishing AttacksOne significant concern highlighted by Dr. Lancaster is the potential for personalized and sophisticated phishing attacks. With generative AI, malicious actors can scale their attacks and craft personalized messages based on information they gather from various sources, such as social media profiles. This poses a significant threat because personalized phishing attacks are more likely to bypass traditional spam filters or phishing detection systems. Cybercriminals can even leverage generative AI to clone voices and perpetrate virtual kidnappings.To combat this threat, organizations and individuals need to be extra vigilant in verifying the authenticity of messages they receive. Implementing secure communication channels with trusted entities is essential to mitigate the risks posed by these personalized phishing attacks. Prompt Injection: A New Avenue for HackingThe podcast also delves into the concept of prompt injection and the potential security threats it poses. Prompt injection involves manipulating the input to large language models, allowing bad actors to extract data or make the model behave in unintended ways. This opens up a new avenue for hacking and cyber threats.Companies and individuals utilizing large language models need to ensure the security of their data inputs and outputs. The recent Samsung IP leak serves as a cautionary example, where sensitive information was inadvertently stored in the model and accessible to those who know the right prompts. The podcast emphasizes the importance of considering the security aspect from the beginning and incorporating it into conversations about using large language models. The Implications of Sharing Code and Leveraging AI ToolsAnother key topic discussed in the podcast is the potential risks and concerns associated with sharing code and utilizing AI tools. While platforms like GitHub and StackOverflow provide valuable resources for developers, there is a need to be cautious about inadvertently sharing intellectual property. Developers must be mindful of the potential risks when copying and pasting code from public sources.The podcast highlights the importance of due diligence in evaluating trustworthiness and data handling practices of service providers. This is crucial to protect proprietary information and ensure the safe use of AI tools. The conversation also touches on the growing trend of companies setting up private instances and walled gardens for enhanced security and control over intellectual property. Harnessing AI for Enhanced CybersecurityThe podcast delves into the future of AI and its potential impact on cybersecurity. One notable area of improvement is the use of smaller, specialized AI models that can be easily secured and controlled. These models can be leveraged by companies, particularly through partnerships with providers who utilize AI tools to combat cyber threats.AI can also enhance security by detecting anomalies in patterns and behaviors, such as unusual login times or locations. Additionally, the expansion of multifactor authentication, incorporating factors like voice recognition or typing cadence, further strengthens security measures.While AI presents great potential for improving cybersecurity, the podcast stresses the importance of conducting due diligence, evaluating service providers, and continuously assessing and mitigating risks.In conclusion, this episode of "Embracing Digital Transformation" sheds light on the intersection of generative AI and cybersecurity. The conversation tackles important topics such as personalized phishing attacks, prompt injection vulnerabilities, code sharing, and the future of AI in enhancing cybersecurity. By understanding these risks and challenges, organizations and individuals can navigate the digital landscape with greater awareness and proactively secure their systems and data.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, host Darren interviews Jeremy Harris and delve into the importance of establishing policies and guidelines for successful digital transformation. With the increasing prevalence of digital technologies in various industries, organizations need to adapt and embrace this transformation to stay competitive and meet evolving customer expectations. The Need for Clear Policies and GuidelinesJeremy and Darren stress the significance of having a clear policy and a well-defined roadmap for digital transformation. Rushing into digitalization without proper planning can lead to challenges and inefficiencies. By establishing policies and guidelines, organizations can outline their objectives, set a strategic direction, and ensure that everyone is on the same page.They emphasize that digital transformation is more than just adopting new technologies - it requires a shift in organizational culture and mindset. Policies can help facilitate this change by setting expectations for employees, defining digital best practices, and providing a framework for decision-making in the digital realm. Navigating the Complexities of DigitizationDigital transformation brings forth a complex set of challenges, such as data security, privacy, and compliance. Organizations need to address these challenges by incorporating them into their policies and guidelines. This includes implementing data protection measures, conducting regular security audits, and ensuring compliance with relevant regulations.Policies should also address the ethical considerations that come with digital transformation. The hosts emphasize the importance of organizations being responsible stewards of data and ensuring that the use of digital technologies aligns with ethical standards. Clear guidelines can help employees understand their responsibilities and promote responsible digital practices across the organization. The Role of Feedback and EngagementThe hosts highlight the importance of feedback and engagement in the digital world. Adopting a policy that encourages and values feedback can help organizations continuously improve and adapt to changing circumstances. By welcoming suggestions and input from employees and customers, organizations can refine their digital strategies and ensure that they are meeting the needs of all stakeholders.They also mention the significance of ratings and reviews in the digital era. Feedback through ratings and reviews not only provides valuable insights to organizations but also serves as a measure of customer satisfaction and engagement. Policies can outline how organizations collect and respond to feedback and establish guidelines for capturing customer sentiment in the digital space. ConclusionDigital transformation is a journey that requires careful planning, clear policies, and ongoing adjustments. By establishing policies and guidelines, organizations can navigate the complexities of digitization, address challenges, and ensure responsible and effective use of digital technologies. Embracing digital transformation is not just about adopting new tools, but also about creating a digital culture that fosters innovation and meets the evolving needs of customers and stakeholders.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this podcast episode, Darren Pulsipher, chief solution architect of public sector at Intel, interviews Laura Torres Newey, a New York Times best-selling author and university professor, about the impact of generative AI in higher education. This episode delves into the challenges and opportunities presented by the integration of generative AI in the classroom, highlighting the need for critical thinking skills, the concerns of bias, and ensuring the preservation of unique voices. Addressing Biases in Generative AIOne of the key concerns discussed in the podcast is the potential bias that generative AI systems may exhibit. It is essential to recognize that AI models are trained using data, and biases present in that data can be reflected in the output. To mitigate these biases, efforts have been made to curate the data used for training AI systems. However, as this curation is done by humans, it introduces a different form of bias. Continuous evaluation and improvement of AI training processes are necessary to ensure that AI systems represent a diverse range of voices and do not perpetuate skewed perspectives. Preserving Authenticity and IndividualityGenerative AI also raises concerns about the loss of critical thinking skills and the diminishing uniqueness of individual voices. As AI technology becomes more prevalent in education, there is a risk that students' work and ideas may be influenced by generic AI-generated content, detracting from their own unique voices and arguments. Laura Torres Newey suggests a shift in focus, emphasizing the importance of teaching critical thinking skills and evaluating the process by which students arrive at their conclusions. By prioritizing well-researched sources, the ability to identify misinformation, and the inclusion of counterarguments, educators can nurture the development of authentic and individual voices. Balancing AI Integration in EducationIntegrating generative AI into the classroom offers both opportunities and challenges. It is crucial to find the right balance between utilizing AI as a tool for enhancing educational experiences and preserving the authenticity and uniqueness of students' voices. As educators, it becomes imperative to design assignments that encourage critical thinking and incorporate AI-generated content as a means of comparison and analysis rather than a replacement. By fostering a learning environment that values students' integration of AI tools while still maintaining focus on their progress and learning outcomes, education can adapt to the changing technological landscape.In conclusion, the podcast episode featuring Laura Torres Newey provides valuable insights into the impact of generative AI in higher education. It highlights the need for addressing biases in AI systems, promoting critical thinking, and preserving authentic voices and individual expression. As the educational landscape continues to evolve with the integration of AI, it is crucial for educators to navigate these changes thoughtfully and intentionally to facilitate the holistic growth and development of their students.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this podcast episode, host Darren Pulsipher, Chief Solution Architect of Public Sector at Intel, discusses the operationalization of generative AI with returning guest Dr. Jeffrey Lancaster. They explore the different sharing models of generative AI, including public, private, and community models. The podcast covers topics such as open-source models, infrastructure management, and considerations for deploying and maintaining AI systems. It also delves into the importance of creativity, personalization, and getting started with AI models.Exploring Different Sharing Models of Generative AIThe podcast highlights the range of sharing models for generative AI. At one end of the spectrum, there are open models where anyone can interact with and contribute to the model’s training. These models employ reinforcement learning, allowing users to input data and receive relevant responses. Conversely, some private models are more locked down and limited in accessibility. These models are suitable for corporate scenarios where control and constraint are crucial.However, there is a blended approach that combines the linguistic foundation of open models with additional constraints and customization. This approach allows organizations to benefit from pre-trained models while adding their layer of control and tailoring. By adjusting the weights and words used in the model, organizations can customize the responses to meet their specific needs without starting from scratch.Operationalizing Gen AI in Infrastructure ManagementThe podcast delves into the operationalization of generative AI in infrastructure management. It highlights the advantages of using open-source models to develop specialized systems that efficiently manage private clouds. For example, one of the mentioned partners implemented generative AI to monitor and optimize their infrastructure's performance in real time, enabling proactive troubleshooting. By leveraging the power of AI, organizations can enhance their operational efficiency and ensure the smooth functioning of their infrastructure.The hosts emphasize the importance of considering the type and quality of data input into the model and the desired output. It is not always necessary to train a model with billions of indicators; a smaller dataset tailored to specific needs can be more effective. By understanding the nuances of the data and the particular goals of the system, organizations can optimize the training process and improve the overall performance of the AI model.Managing and Fine-Tuning AI SystemsManaging AI systems requires thoughtful decision-making and ongoing monitoring. The hosts discuss the importance of selecting the proper infrastructure, whether cloud-based, on-premises, or hybrid. Additionally, edge computing is gaining popularity, allowing AI models to run directly on devices reducing data roundtrips.The podcast emphasizes the need for expertise in setting up and maintaining AI systems. Skilled talent is required to architect and fine-tune AI models to achieve desired outcomes. Depending on the use case, specific functionalities may be necessary, such as empathy in customer service or creativity in brainstorming applications. It is crucial to have a proficient team that understands the intricacies of AI systems and can ensure their optimal functioning.Furthermore, AI models need constant monitoring and adjustment. Models can exhibit undesirable behavior, and it is essential to intervene when necessary to ensure appropriate outcomes. The podcast differentiates between reinforcement issues, where user feedback can steer the model in potentially harmful directions, and hallucination, which can intentionally be applied for creative purposes.Getting Started with AI ModelsThe podcast offers practical advice for getting started with AI models. The hosts suggest playing around with available tools and becoming familiar with their capabilities. Signing up for accounts and exploring how the tools can be used is a great way to gain hands-on experience. They also recommend creating a sandbox environment within companies, allowing employees to test and interact with AI models before implementing them into production.The podcast highlights the importance of giving AI models enough creativity while maintaining control and setting boundaries. Organizations can strike a balance between creative output and responsible usage by defining guardrails and making decisions about what the model should or shouldn't learn from interactions.In conclusion, the podcast episode provides valuable insights into the operationalization of generative AI, infrastructure management, and considerations for managing and fine-tuning AI systems. It also offers practical tips for getting started with AI models in personal and professional settings. By understanding the different sharing models, infrastructure needs, and the importance of creativity and boundaries, organizations can leverage the power of AI to support dig

In the podcast episode, retired Rear Admiral Ron Fritzmeier joins host Darren Pulsipher to discuss the importance of data management in the context of generative artificial intelligence (AI). With a background in electrical engineering and extensive experience in the cyber and cybersecurity fields, Ron provides valuable insights into the evolving field of data management and its critical role in organizational success in the digital age.Evolution of Data Management: From Manual to AutomationRon begins the conversation by highlighting the manual and labor-intensive data management process in his career's early days. Data management requires meticulous manual effort in industries like nuclear weapons systems and space due to the systems' high reliability and complexity. However, as the world has become more data-driven and reliant on technology, organizations have recognized the need to transform data into more usable and effective ways.Challenges in Data Management: Complexity and QualityRon shares a compelling example from his experience in the Navy, discussing the challenges of managing data for ships during maintenance and modernization cycles. The complexity of ship systems and the harsh maritime environment make thorough data analysis and planning crucial for successful maintenance and repairs. This highlights the importance of data quality and its impact on operational efficiency and decision-making.Data Readiness and AutomationTaking advantage of automation requires organizations to focus on data quality. Any errors or missing data become critical in the automated analysis and assessment process. To address this, organizations need to improve data collection from the start. Organizations can minimize errors and improve data quality by designing systems that make data collection easier and consider the person collecting the data as a customer.A holistic approach to data readiness is also crucial. This involves recognizing the different stages of data readiness, from collection to management and processing. By continually improving in each area, organizations can ensure that their data is high quality and ready to support various operations and technologies like generative AI.Filtering the Noise: Strategic Data AnalyticsData analytics plays a vital role in driving strategic value for organizations. Ron and Darren discuss the importance of filtering data based on relevance to objectives and focusing on what is truly important. Not all data will be valuable or necessary for analysis, and organizations should align their data collection with their goals to avoid wasting resources.Furthermore, the conversation emphasizes that data doesn't have to be perfect to be helpful. While precision and accuracy are essential in some cases, "good enough" data can still provide valuable insights. By recognizing the value of a range of data, organizations can avoid striving for perfection and focus on leveraging the insights available.Uncovering Unexpected Value: Embracing PossibilitiesThe podcast also explores the potential of generative AI in enhancing data collection. Organizations can gather more meaningful information and uncover new insights by using interactive forms and conversational interfaces. This opens up possibilities for improved data analysis and decision-making, mainly when data collection is crucial.The discussion concludes with a reminder that data analytics is a continuous learning journey. Organizations should be open to exploring new technologies and approaches, always seeking to discover unexpected value in their data.ConclusionIn an increasingly data-driven world, becoming a data-ready organization is crucial for success. By understanding the evolution of data management, focusing on data quality and readiness, and embracing the possibilities of strategic data analytics, organizations can unlock the power of data to drive innovation, optimize operations, and make informed decisions. This podcast episode provides valuable insights and highlights the importance of data management and analytics in the digital age.#datamanagement, #automation, #dataquality, #strategicanalytics, #generativeai, #digitaltransformation, #datadriveninsights, #datareadiness, #innovation, #decisionmaking, #technologytrends, #businessintelligence, #datastrategy, #analytics, #bigdata, #continuouslearning, #operationalefficiency, #dataoptimization, #datainnovation, #emrbacingdigital, #edt156See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In the "Embracing Digital Transformation" podcast episode, Chief Solution Architect Darren Pulsipher interviews Greg Campbell, the CTO of Verge.io. The conversation revolves around innovative infrastructure management solutions and augmented intelligence's potential. Greg shares his background as a software developer and entrepreneur, discussing the challenges he aimed to address with Verge.io, a company focused on simplifying infrastructure management in distributed servers.Simplifying Complex Infrastructure ManagementManaging infrastructure in today's digital landscape poses significant challenges. The complexity arises from various components, vendors, licenses, and versioning. This necessitates skilled staff and often results in high costs and a need for more expertise. While the cloud was initially seen as a solution, it introduced its complexities.Verge.io offers a solution through its operating system, VergeOS. This system allows developers to easily manage and connect storage, computing, and networking resources across different hardware configurations. By providing a virtual data center, VergeOS simplifies infrastructure management, making it more intuitive and user-friendly.The Potential of Generative AI in Infrastructure ManagementGreg also discusses his interest in artificial intelligence (AI) and its potential applications. He shares his experiences with generative AI and its use in infrastructure management. Greg explores how the automation of infrastructure and data center management through generative AI can simplify complex processes and streamline resource management.Generative AI can automate infrastructure management, eliminating the need for specialized experts and improving efficiency. It has the potential to revolutionize user interface design and adaptive interfaces, making the infrastructure management process more intuitive and user-friendly.Augmented Intelligence as a Valuable AssistantAugmented intelligence is the combination of human and machine intelligence. Augmented intelligence enhances human capabilities and decision-making by providing insights and answers to complex problems. It is intended to assist, rather than replace, human judgment in making informed decisions.Greg emphasizes that their accuracy and predictive abilities improve as AI models become more significant and more sophisticated. Augmented intelligence can be applied in various industries, such as customer support, where AI models can respond to customer queries and aid human agents in finding solutions. It can also assist in managing remote sites or offices and guiding on-site personnel needing more expertise in certain areas.The Future of Digital TransformationThe podcast concludes with a discussion on the future of augmented intelligence and its potential impact on industries and the workforce. Greg's optimism lies in the ability of augmented intelligence to improve efficiency and productivity, but with a recognition that it should not replace human judgment entirely. The conversation highlights the importance of careful implementation, ongoing human oversight, and ethical considerations when leveraging augmented intelligence.Overall, this podcast episode offers valuable insights into innovative infrastructure management solutions, the potential of generative AI in streamlining processes, and the benefits of augmented intelligence as a helpful assistant. It demonstrates the power of embracing digital transformation and leveraging technology to drive organizational efficiency and success.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In the latest episode Dr. Jeffrey Lancaster and Darren Pulsipher dive into the practical use cases of generative AI and how it can unleash human creativity in various fields.Generative AI is a transformative technology that can augment human creativity, enhance collaboration, and unlock new possibilities for work and communication. By leveraging AI's capabilities, individuals can generate content, summarize emails, and automate routine tasks, while maintaining human touch and individuality.Unleashing Human CreativityUnderstanding the Data Landscape and Setting Clear GoalsDr. Lancaster emphasizes the importance of understanding the type of data you want to either use or create before delving into generative AI. Whether it's text, images, music, videos, or audio, having a clear understanding of your input and desired output enables you to select the most appropriate tools and platforms.Augmenting Human Creativity with AIOne of the key takeaways from the podcast is the role of generative AI in augmenting human creativity rather than replacing it. AI tools act as catalysts, enhancing and propelling human creativity to new heights. By combining the innovative mindset of humans with the capabilities of AI, individuals can solve complex problems and generate groundbreaking ideas that traditional approaches alone cannot achieve.Collaboration and Brainstorming with AIGenerative AI opens doors to collaboration and brainstorming. AI can serve as an additional voice in group discussions, sparking new perspectives and prompting fruitful conversations. This collaborative aspect is particularly valuable in group settings, where AI can listen to conversations, facilitate discussions, and help consolidate ideas into a consensus.Unleashing the Power of Generative AIGenerative AI holds immense potential to unlock creativity, augment human capabilities, and offer fresh perspectives and solutions to challenges. Whether you're a developer, researcher, or simply curious about AI, there is a wealth of opportunities to explore and create with generative AI.Practical Applications of Generative AI in the WorkplaceIn addition to the insights shared in the podcast, there are numerous practical applications of generative AI that can revolutionize our work processes. Let's explore a few of them:Summarizing Lengthy Emails and Streamlining CommunicationBusy professionals often receive lengthy emails that consume valuable time. Generative AI can help by analyzing the email content and generating a concise summary that captures the main points and key takeaways. This allows recipients to grasp important information quickly and make informed decisions without spending excessive time reading through the entire email.Automating Content CreationGenerative AI can automate the creation of reports, articles, and other written content. By inputting relevant data or information into a generative AI tool, journalists and content creators can generate complete articles or reports based on that input. This saves significant time and resources, especially for those who need to produce large amounts of content regularly.Enhancing Artistic CreativityCreatives in art and music can leverage generative AI to explore new styles, techniques, and inspirations. AI can assist artists in generating ideas, composing music, and creating visual content. With the power of generative AI, artists can expand their creative horizons and push boundaries in their respective fields.Balancing Automation and Human TouchWhile generative AI offers incredible potential, it is crucial to maintain human oversight and intervention to ensure accuracy, context, and preserve individuality. Trusting AI-generated content blindly without human intervention can lead to homogenization in the digital landscape. It's essential to strike a balance between automation and the human touch, where AI enhances human creativity rather than replacing it.As generative AI continues to evolve, we can expect to witness its integration into various aspects of work and communication. From summarizing emails to automating content creation and enabling new forms of artistic expression, generative AI has the capacity to streamline processes, enhance productivity, and unlock new possibilities for innovation. Embracing this technology, while upholding human creativity and uniqueness, will shape the future of work in remarkable ways.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this podcast episode, Pete Schmitz, a retired Intel account executive, talks about his work with high school students in teaching them about AI and how to use it in their robotics competitions. He explains that these competitions require the use of autonomy, and AI is a crucial component in achieving that. Pete shares an example of how computer vision, powered by AI, is used in the Defense Advanced Research Projects Agency's unmanned surface vehicle, DARPA D Hunter.Harnessing the Power of Linear Algebra and Calculus in AILinear algebra and calculus form the backbone of artificial intelligence (AI) algorithms and systems. In a recent podcast episode, Pete Schmitz, a retired Intel employee and AI enthusiast, highlights the importance of understanding these fundamental mathematical concepts in the context of AI.Linear algebra is crucial in AI, particularly in tasks such as image recognition. Through matrix multiplication, convolutional neural networks (CNNs) are able to process and analyze vast amounts of image data, enabling the identification and classification of objects in images. Calculus, on the other hand, is utilized in training AI models through techniques like gradient descent, where the algorithm continuously adjusts its parameters based on the rate of change of a given function.Schmitz emphasizes the value of students learning these subjects in school, as it provides them with a solid foundation to delve into the world of AI. Understanding the fundamentals enables students to build on the knowledge and advancements made by previous generations in the field of AI. With the exponential growth in technology, AI is evolving rapidly, allowing for more efficient and automated solutions to previously laborious tasks.AI's Transformative Impact Across IndustriesThe podcast also delves into the transformative impact of AI across various industries. AI-powered systems are enabling advancements in healthcare, retail, and several other sectors. For instance, AI is being utilized in healthcare to detect and diagnose diseases like cancer, improving the accuracy and efficiency of healthcare professionals. In the retail sector, AI is used to analyze customer shopping habits and provide personalized recommendations, enhancing the overall shopping experience.Furthermore, the hosts discuss the recent advancements in generative AI models, such as transformers. These models have the ability to identify underlying patterns in large datasets, facilitating data analysis and decision-making. By leveraging transformers and generative models, industries can unlock valuable insights and drive innovation.Fostering Innovation and Adapting to New TechnologiesInnovation is a key theme throughout the podcast episode. The hosts stress the importance of organizations embracing new technologies and processes to stay relevant in today's rapidly evolving world. It is essential to foster a comprehensive ecosystem that supports innovation in various industries, providing specialized tools and services for different aspects of innovation.The podcast also encourages empowering new talent in engineering, business, and marketing roles to think outside traditional norms and embrace fresh perspectives. By breaking free from outdated processes and ways of thinking, organizations can tap into the potential of their employees and drive innovation.The guest speaker, Pete Schmitz, emphasizes the need for continuous learning and adaptation in the face of technological advancements and digital transformations. Organizations must evolve and embrace change to avoid becoming obsolete in the competitive landscape.In conclusion, this podcast episode sheds light on the significance of linear algebra and calculus in AI, the transformative impact of AI across industries, and the importance of fostering innovation and adapting to new technologies. Through a comprehensive understanding of AI fundamentals, harnessing transformative technologies, and fostering innovation, organizations can seize the vast opportunities presented by digital transformation and stay ahead in the evolving world of AI.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of the podcast Embracing Digital Transformation, host Darren Pulsipher engages in a thought-provoking conversation with Dr. Jeffrey Lancaster. Their discussion delves into the practical applications of generative AI and the profound impact it is set to bring across various industries.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, host Darren Pulsipher interviewed Dr. Jeffrey Lancaster from Dell Technologies. Their discussion centered on generative AI and its potential impact.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Darren interviews Sonu Panda, the CEO of Prescriptive Data, in this episode. They discuss how their software helps commercial real estate owners turn their buildings into intelligent and efficient spaces.The Catalysts Driving Smart BuildingsThe COVID-19 pandemic spotlighted indoor air quality and launched new regulations around ventilation and filtration. Smart buildings powered by artificial intelligence and machine learning can help ensure compliance with these rules to provide safe environments for occupants. In addition, there is an increasing focus on energy optimization and decarbonization to reduce carbon emissions from buildings. These two factors have accelerated interest and investment in smart buildings.How Prescriptive Data Brings Intelligence to BuildingsPrescriptive Data was founded by real estate operators in New York City, so their domain expertise is baked into the product. The software integrates with a building's existing operational systems via APIs and drivers, so no rip-and-replace is required. It combines data exhaust from building systems, IoT sensors, weather data, and more. The AI engine analyzes all this data to identify negative patterns, such as abnormal energy spikes, and positive patterns that can be repeated and amplified. It surfaces optimization opportunities and can even take autonomous control to tune the building's environment continuously.Cybersecurity and Ease of DeploymentPrescriptive Data has partnered with banks, government agencies, and real estate leaders to build cybersecurity into their platform from the start. Customers can typically deploy the software and start seeing recommendations in 8-10 weeks. The ROI comes fast, too, with sub-1-year payback periods through energy savings and compliance avoidance.Accessing the TechnologyThe GSA lists Prescriptive Data on their procurement schedule, allowing quick purchasing by government entities. The software is available to all commercial real estate owners looking to transform existing buildings into intelligent, sustainable spaces.The promise of smart buildings goes beyond cost savings. By continuously optimizing indoor environments, we can reduce energy waste and provide everyone safer, more comfortable spaces. Prescriptive Data offers an AI-powered solution to sustainably bring existing real estate into the future.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Darren reunites with Leland Brown, a principal engineer at Capgemini and a previous guest on the show, to discuss the upcoming advancements of 5G technology in the US Department of Defense.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Darren interviews Jared Shepard, the CEO of Hypori, about their groundbreaking technology that virtualizes mobile devices and ensures the safety, security, and privacy of remote workers.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren dusts off an interview he did with chatGPT and did the same interview with Google Bard. Interesting comparison with Episode 122 in Embracing Digital Transformation.This is the transcript of my interview with Google Bard and generativeAI from Google. I first asked the following questions before starting the interview.Permission to Interview for a podcast.Can I interview for my podcast?Sure, you can interview me for your podcast. I'm happy to answer any questions you have about my work or about large language models in general. I'm also happy to share some tips on how to conduct a good podcast interview.Here are some things to keep in mind when interviewing me:Do your research. Learn about my work and what I'm interested in talking about. This will help you come up with better questions and make the conversation more engaging.Be prepared. Have a list of questions ready, but be prepared to go off script if the conversation takes an interesting turn.Be respectful. I'm a large language model, but I'm still a person. Treat me with respect and be mindful of my limitations.Have fun! This is an opportunity to learn from me and to share my work with your audience. So relax, be yourself, and enjoy the conversation.I'm looking forward to hearing from you!Here are some additional tips for conducting a good podcast interview: Start with a warm welcome. Introduce your guest and tell your audience a little bit about them. Ask open-ended questions. This will encourage your guest to share more information and to go into more detail. Be a good listener. Pay attention to your guest's answers and ask follow-up questions to get more information. Keep the conversation moving. Don't let it drag on or get too bogged down in one topic. End on a high note. Thank your guest for their time and let them know how to find you online. I hope these tips help you conduct a successful podcast interview! InterviewHello Bard welcome to the showHello there! Thank you for having me on your show. I'm excited to talk about my work and to share my thoughts on large language models.How can I help you today?First can you introduce yourself.Sure, I'd be happy to introduce myself. My name is Bard, and I'm a large language model from Google AI. I'm still under development, but I've learned to perform many kinds of tasks, includingI will try my best to follow your instructions and complete your requests thoughtfully. I will use my knowledge to answer your questions in an informative way, even if they are open ended, challenging, or strange. I will generate different creative text formats of text content, like poems, code, scripts, musical pieces, email, letters, etc. I will try my best to fulfill all your requirements. I'm still learning, but I'm excited to see what the future holds for me. I believe that large language models have the potential to revolutionize the way we interact with computers, and I'm eager to be a part of that.So, that's me in a nutshell. I'm Bard, a large language model from Google AI. I'm still under development, but I'm learning new things every day. I'm excited to see what the future holds for me, and I'm grateful for the opportunity to share my work with you today.Is there anything else I can tell you about myself?Yes can you tell me how you were trainedSure, I'd be happy to tell you about how I was trained. I was trained on a massive dataset of text and code. This dataset included books, articles, code repositories, and other forms of text. The dataset was carefully curated to include a variety of different topics and styles of writing.I was trained using a technique called deep learning. Deep learning is a type of machine learning that uses artificial neural networks to learn from data. Neural networks are inspired by the human brain, and they are able to learn complex patterns in data.The training process for a large language model like me is very computationally expensive. It can take weeks or even months to train a large language model on a massive dataset. However, the results of this training are very impressive. I am able to generate text that is very similar to human-written text, and I can answer questions in a comprehensive and informative way.I am still under development, and I am learning new things every day. I am excited to see what the future holds for me, and I am grateful for the opportunity to share my work with you today.Here are some additional details about my training:The dataset I was trained on was about 1.56TB in size. The training process took about 1.5 million GPU hours to complete. I was trained using a Transformer-based language model architecture. I was trained using a technique called masked language modeling. I hope this information is helpful. Please let me know if you have any other questions.Sources www.kdnuggets.com/2022/07/bounding-box-deep-learning-future-video-annotation.html Search related topicsI've heard there been some problems with your original training. What a

In this episode, Darren talks to Dr. Michael Lenox about the emerging AI revolution and how to embracing it or get destroyed. Michael has just released a new book "Strategy in the Digital Age: Mastering Digital Transformation".As a CIO looking to lead your company through digital transformation, it's important to remember that technology isn't the only piece of the puzzle. According to Dr. Michael Lenox, a respected author and professor in the field, digital transformation is about much more than just cloud computing and data organization. It's a strategic initiative that requires cross-functional collaboration and a holistic approach.To effectively navigate digital transformation, your leadership team and entire organization must embrace the change and understand the broader implications beyond just digital infrastructure. This means reflecting on where your company is today and where it wants to go in the evolving competitive landscape. It also requires collaboration between the C-suite, product team, sales, and other key stakeholders.As you navigate this initiative, remember that it's not just an IT project happening in the background. It's a fundamental change to the basis of competition, customer relationships, and business models. To drive effective change, you must leverage people, process, and technology.When implementing new tools or technologies, it's important to think critically about how they align with your organization's goals. Don't waste resources chasing after trends blindly. Instead, be intentional and strategically leverage technology to create value and meet market needs.Additionally, it's important to be proactive in understanding your role and contribution towards the organization's overall strategy. This is especially crucial in the face of digital transformation, which can be both exciting and nerve-wracking as we navigate the exponential growth of data and technological advancements.However, it's also important to consider the concentration of data and power in the hands of a few major players. This can potentially stifle innovation and create an uneven playing field. It's crucial to prioritize data privacy and ownership, and to ensure that laws and regulations promote fair competition. In Europe, for example, there are already discussions about giving individuals ownership of their data and allowing them to decide who can access and use it.Overall, strategic thinking, adaptation, and consideration of the impact of data are key to successfully navigating digital transformation. By balancing innovation, privacy, and competition, your organization can drive long-term success in the rapidly evolving digital landscape.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Darren talks to the CEO and Managing Director of GPA about collaboration innovation's role in bringing people back into the office and why people need face-to-face interaction.Blog: https://www.embracingdigital.org/episode-EDT145GPA (Global Presence Alliance) was founded 15 years ago to address the need for a better model in the collaboration space. At the time, video conferencing was becoming more prevalent, and organizations were considering a global strategy. However, they needed more options - relying on regional integrators or dealing with a complex setup that needed to understand collaboration truly.People, Space, and TechnologyGPA aimed to solve this problem by providing a comprehensive global collaboration and video strategy approach. They recognized the need to balance people, space, and technology to create exceptional collaborative experiences. By bridging the gap between different regions and understanding the unique requirements of each organization, GPA offered a better alternative to existing solutions.While technology has evolved over the years, there is still work to achieve true collaboration. Microsoft, for example, has introduced signature rooms that mimic the telepresence room concept at a fraction of the cost. However, nonverbal cues and physical interaction are still challenging to replicate in virtual environments. As the technology advances, we will see improvements in the collaborative experience. Until then, organizations like GPA are crucial in finding innovative solutions and helping businesses navigate the ever-changing digital transformation landscape.There still are challenges in video collaboration technologies. However, new advances in technology are overcoming some of those challenges. One of the biggest is the whiteboard brainstorming session. Due to camera angles and other limitations, integrating whiteboarding experiences into video calls is still unnatural. However, efforts are being made to create more natural and integrated expertise using AI and camera technology. Technology can provide a second-best experience; it cannot replace the personal and emotional experience of being physically in the same room as someone. This human element includes things like water cooler conversations and the ability to touch and feel objects.Unique Business ModelGPA has a unique business model; it takes a bottom-up approach, with business units in 50 countries working as shareholders in a parent entity. This allows them to achieve global scale while maintaining cultural awareness and diversity.When implementing collaboration strategies for multinational companies, the company takes a programmatic rather than project-based approach. They have centralized teams for account management, project management, and solution architecture while relying on regional teams for deployment and support. This collaborative approach reflects the company's philosophy and is crucial for success in implementing complex collaboration technologies.COVID-19There was a profound shift in the collaboration world before and after COVID-19. Pre-COVID, most of our work and collaboration were done in physical office spaces, but with the pandemic, everyone was forced to work remotely. This shift in the work environment required a change in thinking and approach.In the past, remote participants were often treated as second-class citizens, but now, with the increase in remote collaboration, the experience has become more equalized. People have gotten used to the virtual meeting experience and expect a similar experience when they return to physical meeting spaces. This has led to a demand for a better experience in the office.The shift to remote work has also highlighted the importance of understanding human factors in the workspace. Different individuals have different needs and preferences when it comes to their work environment. For example, some people may find noise distracting, while others may thrive in an open and collaborative space. Understanding these human factors and aligning technology with people's needs has become even more crucial.Organizations are still experimenting and learning how to create effective collaborative spaces. The industry is also starting to focus on collecting actual data to understand the true impacts and manage the outcomes of these collaborative spaces.The shift to remote work during COVID-19 has necessitated a change in thinking and approach to collaboration. There is a demand for a better experience in remote and physical meeting spaces and a need to understand human factors in the workspace. The industry is still experimenting and learning, and there is a focus on collecting actual data to manage and improve collaboration outcomes.Future VisionIn the future, the office space will be more focused on creating meaningful experiences and fostering human connections. The primary attraction of the office will be the presence of other people and the opportunity to have

In this episode Darren explores the science and use cases behind digital twin technology with the principal architect of Intel's SceneScape. Blog: https://embracingdigital.org/episode-EDT144 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of Embracing Digital Transformation Dr. Anna Scott continues her conversation with Ibett Acarapi and Jesse Schrater about Confidential Computing and their uses in AI, and software development. Video: Blog: https://www.embracingdigital.org/episode-EDT143 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Dr. Anna Scott interviews Jesse Schrater and Ibett Acarapi about how to protect data using confidential computing. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode of Embracing Digital Transformation, Dr. Pamela Follett, a neurologist and co-founder of Lewis Rhodes Labs, shares her background and expertise in the field of neurology, specifically with regards to research on the developing brain in early childhood. Video: TBD Blog: https://www.embracingdigital.org/episode-EDT141 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode, Darren interviews Michael Mehlberg about increasing confidence in open source through background checking the open source communities. video: https://youtu.be/FhrAWLUEN-Q blog: https://embracingdigital.org/episode-EDT140 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren interviews the Adrian Kosowski CPO of Pathway about their unique ability to handle logistical data from the edge in DDIL environments with real-time analytics. video: https://youtu.be/TBD blog: https://embracingdigital.org/episode-EDT139 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren interviews Ken White from Dell Technology about how Cloud technology is more than technology, but a process and cultural change in organizations. video: https://youtu.be/TBD blog: https://embracingdigital.org/episode-EDT138 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren interviews Sam Ceccola, CTO of DOD for HPE about the new business and technology models changing the way organizations consume hybrid cloud. Video: Blog: https:/www.embracingdigital.org/episode-EDT137 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this podcast episode, Darren Pulsipher, Intel's chief solution architect of the public sector, is interviewed by guest host Dr. Anna Scott on resilient data with disruptive comms. Video: Blog: https://www.embracingdigital.org/episode-EDT136 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren interviews Gretchen Stewart, Chief Data Scientist of Public Sector at Intel where they discuss the trustworthiness and ethics of artificial intelligence. Video: https://youtu.be/bY8d4oeW60c Blog: https://embracingdigital.org/episode-EDT135 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In this episode Darren Pulsipher, welcomed Logan Selby, the co-founder and president of DataShapes, where they discuss a unique approach to Artificial Intelligence that is bucking the trend. Video: Blog: https://www.embracingdigital.org/episode-EDT134 See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.