Intel on AI

In this Intel on AI podcast episode: Enterprises today have exploding volumes of data which is growing the scale and complexity of data centers and often result in unplanned IT downtime. This disrupts mission-critical operations, causes loss of data, and impairs application services. Atul Gupta, the Head of Alliances at Digitate, joins the Intel on AI podcast to talk about how the ignio platform helps IT rapidly identify and remediate outages in minutes. He talks about how ignio blends AI, ML and advanced Deep learning to quickly resolve issues and preempt incidents when possible. He also emphasizes how ignio binds together disparate but interconnected business applications, processes, and the underlying infrastructure to drive smart decisions and perform actions autonomously. Atul explains how the Digitate team worked with Intel AI to use the Intel Distribution of OpenVINO toolkit to optimize some of their workloads and achieved incredible performance improvements. He also expresses how being a part of the Intel AI Builders program has been an excellent and productive experience for the Digitate team. To learn more, visit: digitate.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Creating, maintaining and deploying data models that allow businesses to gain actionable insights can require a lot of time and effort due to the vast amount of data to process. Also, machine learning optimization is a resource-intensive process and can be a challenge to accomplish in an industry where achieving fantastic results at speed is the final goal. Carlos Pazos, Product Marketing Manager at SparkCognition, joins the Intel on AI Podcast to show how the SparkCognition Darwin platform is transforming the way that data models are built in the enterprise world. He explains that automated machine learning (AutoML) enables even non-technical users to make use of science and drives organizations to scale the operationalization of ML models. The SparkCognition Darwin platform uses neuroevolution to custom build model architectures creating models in less time than traditional methods and enabling the rapid prototyping of scenarios and insights. Carlos also discusses how using Intel tools like the Intel Message Parsing Interface (Intel MPI) has allowed SparkCognition to provide greater performance to their end users. Also, how the Intel AI Builders program has provided an immense amount of development and marketing guidance to SparkCognition. To learn more, visit: sparkcognition.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Counting and identifying characteristics of crowds can provide organizations with a lot of valuable insights. Yet challenges like image distortion, density, and different camera angles can make analyzing images accurately very challenging. Ganes Kesari, Co-founder and Head of Analytics at Gramener, joins the Intel on AI podcast to discuss how Gramener has created a crowd counting solution that can overcome those challenges and produce a very rapid and accurate analysis of images. He talks about how Gramener has utilized this solution for several AI for good projects including a joint effort with Microsoft to count Antarctic penguin colonies. Ganes explains how their solution used convolutional neural networks (CNNs) using density-based estimations to deliver a more accurate penguin count than traditional manual counting methods. He also emphasized how benchmarking the solution on Intel AI technology and the Intel Optimization for PyTorch helped Gramener achieve comparable performance at a potentially lower computational cost. In addition to AI for good projects, Ganes also outlines how this same solution can also be utilized for other enterprise opportunities like drug discovery and how Gramener will continue to collaborate with Intel to provide better optimizations and performance for its customers. To learn more, visit: gramener.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Accurately answering clinical and billing questions by reading patient records, which can be hundreds of pages long, is a challenge even for human experts. While traditional rule-based or expression-matching techniques work for simple fields in templated documents, it's harder to infer facts based on implied statements, the absence of certain statements, or a combination of other facts. David Talby, Acting CTO at John Snow Labs, joins us to talk about how the John Snow Labs Healthcare AI Platform and Spark NLP project are helping revolutionize the healthcare industry by addressing such workloads at a very high level of accuracy using state-of-the-art deep learning techniques applied to natural language processing (NLP). He discusses how NLP in healthcare is particularly challenging because clinical vocabulary and context can be very unique in comparison with other industries. David also explains how NLP is incredibly important for the healthcare industry because the data for many practical AI applications is trapped in text and NLP is needed to extract actionable insights. He illustrates how their solutions can run on-prem or in the cloud and highlights that John Snow Labs was recently recognized by CIO Applications magazine as its 2019 'AI Platform of the Year' winner. To learn more, visit: johnsnowlabs.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Enterprises today are attempting to use Artificial Intelligence (AI) to tackle more and more complex challenges. Yet, many of the AI applications today are unable to cope with optimization and automation challenges in dynamic and complex environments like mobility, logistics, manufacturing and energy. Karim Beguir, Co-Founder & CEO at InstaDeep, joins the Intel on AI podcast to discuss how InstaDeep is helping their customers solve complex decision-making problems that would traditionally have been solved with existing algorithms but that can much better be served with AI and Machine Learning (ML). Some of the use cases that InstaDeep has tackled include working with large car companies to solve issues around ride-sharing and vehicle routing. Another example is how the company has helped customers in supply chain to optimize operations like container loading and bin packing. Karim explains how InstaDeep utilizes reinforcement learning which allows the algorithm to learn from itself and can model, simulate, and solve a problem without needing to have data from a customer in the first place. He talks about how collaborating with the Intel AI Builders program has enabled InstaDeep to develop solutions that provide better efficiency and savings to their customers. Karim also shares his vision for the future of an AI-first world and how InstaDeep is helping startups and companies around the world develop and utilize AI to improve their organizations and communities. To learn more, visit: instadeep.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Colorectal cancer is the one of the most common cancers worldwide, and in about half of patients it can spread to the liver and lead to greater complications. Traditional manual examinations of tumors are time-consuming and subjective for radiologists. Yet, using AI for this workload can be complicated because biomarkers, DNA, and genomic data are enormous and require lots of compute, storage and software to analyze. Saurabh Gupta, Director Advanced Analytics & Artificial Intelligence Product Management at SAS, joins us to talk about how SAS is working with the Amsterdam University Medical Center (UMC) on medical imaging analysis to identify if patients are candidates for surgery based upon the size and growth of lesions. He talks about how Amsterdam UMC using SAS AI-trained models running on Intel processors was able to analyze MRI images and with much greater accuracy identify patients who respond well to chemotherapy and become candidates for surgery. Saurabh highlights how SAS is not just simply a software vendor but also provides many tools that gives its customers a platform to do powerful AI analysis with the SAS software that they know and trust. He also talks about how important it is for SAS customers to be able to develop their solutions on Intel architecture because they already have the skills and architecture needed to address the workloads they have. To learn more, visit: SAS.com/ai Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: There is a massive amount of insight to be gained by studying brick and mortar customer behavior. Yet capturing, labeling, and analyzing that data can be a very complicated and compute intensive activity. Dan Klein, Chief Data Officer at Valtech, joins the Intel on AI podcast to discuss how Valtech's project VOID (Visual Object Identification) uses Intel® NUCs and the Intel developer stack to capture retail customer data like customer locations, face metadata, and apparel metadata to provide incredible real time insights for retail organizations. He talks about how powerful this technology can be to help retailers better analyze and cater to their customers in real-time but also how sensitive capturing individual information can be from a privacy and bias standpoint. Dan highlights how Valtech is proactively working to build their training data sets to include a diverse set of individuals of different genders and ethnic backgrounds to fight discrimination and bias in their analysis. He addresses the importance of ensuring individual privacy and fighting gender and racial bias in AI analytics and highlights that building a strong and diverse team at Valtech provides the foundation for this effort. To learn more, visit: valtech.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: There are many individuals (makers) creating artificial intelligence (AI) enabled solutions and many of which may help drive AI to the next level. Yet, there is a challenge for makers when moving from an inexpensive board used for development to large scale production that requires much more specialization and infrastructure. Aling Wu, the AI and IoT Alliance Director at AAEON, joins the Intel on AI Podcast to discuss how the AAEON UP Board Computer Board family for Professional Makers helps bridge the gap from maker market to large scale production. She highlights how AAEON works directly with makers to take their design and actually produce and ship in volume production in 6-12 month period of time. Aling also discusses how AAEON provides makers with easy shopping solutions for development boards with UP shop and a forum where makers can discuss and refine their solution called UP Community. She talks about how important AI on the edge is for the development of the AI industry and how AAEON uses Intel's broad portfolio of technologies including FPGAs (Field Programmable Gate Array) and Intel Core process to achieve performance on the edge. To learn more, visit: aaeon.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: As artificial intelligence (AI) technologies rapidly advance many companies would like to take advantage of the potential of AI but can't because they do not have the resources or skills for modeling and engineering. Yuan Shen, Founder and CEO of OneClick.AI, joins Intel on AI to talk about how OneClick enables businesses with no knowledge of AI and coding to solve complex business problems and drive real ROI with only a few clicks. He discusses how the OneClick.ai Automated Deep Learning (AutoDL) platform automates every step of AI model development supporting many different use cases including numeric prediction, classification, forecasting, recommendation, and image object detection. Yuan talks about how OneClick.AI has worked with the Intel AI Builders program to optimize deep learning on Intel Xeon Scalable processors using Intel optimization libraries and how they have been able to see great performance increases due to using those optimizations. To learn more, visit: oneclick.ai Or: builders.intel.com/ai/membership/oneclickai

In this Intel on AI podcast episode: Today athletes are always looking for new ways to analyze and improve their performance through video analysis and sports enthusiasts love to experience sports in new and innovative ways, but 3D capture technology can be difficult to program and expensive to access. Paul Kruszewski, the CEO and Founder of wrnch AI, joins the Intel on AI podcast to talk about the markerless motion capture real-time 3D tracking that wrnch is enabling which is helping to democratize that motion capture technology. He discusses how the wrnch solution can enable any 2D camera to become a motion capture device by using a deep learning trained model that tracks 23 skeletal points to do real-time analysis on human movement. Dr. Paul highlights how this technology can be used not just for sports training and in-home exercise guidance, but can even span many healthcare and even autonomous driving applications. He expresses how wrnch heavily benefits from breadth of hardware options that Intel delivers and how utilizing the Intel OpenVINO toolkit has enabled wrnch solutions to be available to developers around the world to do real-time AI on Intel Architecture. To learn more, visit: wrnch.ai Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Regular inspection of underground water and sewage pipelines is essential in the water utility industry to prioritize maintenance tasks and avoid pipe leakage, breakage, and blockage, which might result in property damage or safety hazards. Traditional inspection with videos being captured by a remotely operated rover and then manually analyzing footage is cumbersome, time-consuming, and error prone. Sundar Varadarajan, Consulting partner for AI/ML at Wipro Technologies, joins the Intel on AI podcast to discuss how Wipro is using artificial intelligence (AI) to automatically process video scans and identify, grade, and score overall pipe quality. Utilizing the Intel Optimization for TensorFlow and Intel OpenVINO Toolkit, Sundar explains how Wipro enables their customers to perform image inferencing in real time allowing pipeline inspections to be incredibly more efficient, consistent, and accurate. Sundar also talks about how Wipro is working with the Intel AI Builders program to optimize their solutions for the latest Intel technologies and lists several other solutions focused on concrete surface crack detection and medical imaging. To learn more, visit: wipro.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Many large enterprises need more accuracy and atomization for planning and purchasing. Yet, when generating and analyzing such a massive volume of data, the algorithms use an enormous amount of memory and processing can be slow, problematic, and often not calculate correctly at all? Dionisio Agourakis, the CEO at J!Quant, joins the Intel on AI podcast to talk about how J!Quant has a diverse portfolio of products involving deep learning (DL) and time-series prediction for stock optimization, demand forecast, and profit forecast to help their customers. He talks about how J!Quant helps enable a data-driven culture within their customers' decision-making processes in order to stay relevant, profitable and open to new opportunities. Dionisio also discusses a specific use case utilizes the 2nd Generation Intel Xeon Scalable processors to tackle a memory bounded algorithm that a customer had and were able to successfully process the inference using Intel processors and Intel Optimizations for Tensorflow. To learn more, visit: jquant.com.br builders.intel.com/ai/membership/jquant software.intel.com/en-us/frameworks Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Deep neural networks (DNNs), which are arguably the most powerful form of AI today, are difficult to build, run, and explain. Such challenges constitute significant roadblocks for their adoption in their enterprise. Ironically, AI itself can be used to assist data scientists and developers to build and evaluate DNNs. Sheldon Fernandez, CEO of DarwinAI, joins us to talk about how DarwinAI is using this 'AI building AI' method in their Generative Synthesis platform. Sheldon explains how their technology reduces the complexity in designing high-performance deep learning solutions and also facilitates explainable deep learning, which allows a user to understand why a network makes the decisions it does. Finally, he describes a recent analysis conducted by the Intel AI Builders team, where Darwin-generated networks coupled with Intel Optimizations for TensorFlow were able to deliver up to 16.3X performance increase on ResNet50 and up to 9.6X on NASNet workloads. To learn more, visit: darwinai.ca Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Millions of dollars are lost by retailers worldwide each year as a result of out of stock products, overstocking, and shrinkage. Out of stock products also incur other costs, such as the reduced impact of in-store promotions and the time employees use dealing with customer requests about missing items. Ceyhun Burak Akgül, the Co-Founder and CTO of Vispera, joins the Intel on AI podcast to discuss how Vispera image recognition and retail real-time monitoring solutions are enabling businesses to use cameras to track product stocks and customer behavior to analyze and react to better serve the customer and business in real time. He describes the Vispera ShelfSight solution that is powered by the Intel Movidius Neural Compute Stick and optimized using Intel Distribution of OpenVINO Toolkit to allow brick and mortar stores to better compete with the online shopping experiences of today. Ceyhun talks about how the Intel AI Builders program has helped Vispera to better enable and benchmark their systems while helping connect them with potential prospective customers. To learn more, visit: vispera.co Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Justin Norman, Director of Data Science Research and Services at Cloudera, joins the Intel on AI podcast to talk about the challenges that enterprises face when executing AI solutions like scalability, compliance, and security. He illustrates how Cloudera's experience and deep portfolio, including the Cloudera Data Science Workbench, provides the tools and expert guidance needed to help customer's end-to-end transition into an AI first world. Justin highlights how Cloudera Fast Forward Labs is the foundation to provide strategic vision and expertise to facilitate customers in planning and business strategy when utilizing AI. Justin also describes how Cloudera and Intel has had a long strategic partnership working to provide customers both the cutting-edge hardware and software to meet all of their business needs. To learn more about the Cloudera Fast Forward Labs offering, the Cloudera Science Workbench tool, or machine learning, visit: cloudera.com/about/machine-learning.html Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Every customer call is an opportunity to gain information about customer preferences and pain points. Yet capturing and structuring call data can be a very slow, time, and compute intensive process. On this episode of Intel on AI, Yishay Carmiel founder of IntelligentWire (an Avaya Company), comes in to talk about the Avaya Conversational Intelligence platform that is helping to transform customer experiences through improving agent productivity by reducing contact center after-call work. The platform instantly captures and analyzes customer conversations, transcribing spoken words into a machine-readable format while providing instant sentiment analysis and flagging important actions to be taken by the service agent. Yishay explains how the Avaya Conversational Intelligence platform utilizes speech recognition, natural language processing (NLP), and data analysis to provide enterprises with invaluable detail. He also describes how the growing number of contact centers utilizing this type of solution is rapidly growing and the need for real-time insights provided by the Avaya Conversational Intelligence platform is imperative in improving customer experience. To learn more, visit: avaya.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: When doing big data analysis and developing AI models businesses start by capturing very accurate, well defined, and structured data to be able to train their models. Yet, gathering and structuring all of that information can be very difficult and time consuming. Thoran Rodrigues, Founder and CEO of BigData Corp, joins the Intel on AI Podcast to talk about how BigData Corp. is capturing, aggregating, and structuring information from millions of websites to help companies exploit the full potential of data. He also talks about how the company provides API solutions that allow their customers to extract real-time insight from those large amounts of data for use cases spanning e-commerce, financial services, document authentication, and more. Thoran expresses how important software optimizations are to enable BigData Corp to scale their business and more efficiently use infrastructure resources which translates to fast and consistent services for their customers. To learn more, visit: bigdatacorp.com.br Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: There is growing need for digital health solutions to improve accessibility and affordability of medical resources to add value for care providers and improve healthcare outcomes for patients. Xuefeng Zhang, the Chief Marketing Officer of Huiying Medical Technology (HYHY), joins the Intel on AI podcast to talk about how HYHY is working with Intel to help bring new digital health solutions to communities in need throughout China. He specifically discusses the Pink Ribbon campaign where Intel's Data Center Group collaborated with HYHY to apply Intel AI technology to boost the accuracy and speed of breast cancer detection. This project helped enable many healthcare providers across China improve their time and accuracy of breast cancer diagnoses. Xuefeng also illustrates how the Intel Optimization for Tensorflow and the Intel Distribution of OpenVINO toolkit has helped HYHY achieve incredible performance for their lung nodule computerized tomography (CT) scan analysis solution. This has enabled hundreds of hospitals across China to utilize this impactful AI solution on their existing hardware. You can learn more about the Intel AI Builders member HYHY by visiting: builders.intel.com/ai/membership/huiying-medical en.huiyihuiying.com/ Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Phil Hummel, Senior Principal Engineer at Dell EMC, joins the Intel on AI Podcast to talk about the new Dell EMC Ready Solution for AI with Intel featuring Nauta. He illustrates how enterprises today want to take advantage of AI to leverage massive amounts of data to help differentiate their business. Yet, deploying AI solutions can often be very complex and costly to integrate into an existing infrastructure. Phil describes how Dell EMC Ready Solutions for AI provide a simplified path to AI-powered applications and greater TCO with an easy-to-set-up solution. The recently announced Ready Solution, Deep Learning with Intel, is powered by Dell EMC servers and networking, new 2nd Generation Intel Xeon Scalable processors, and Nauta, Intel's recently released open source platform for distributed deep learning training. Phil tells us how this new solution can be a game changer for many different use cases and help enterprises get a leg up when deploying AI. To learn more, visit: DellEMC.com/ReadyForAI Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Enterprises want to deploy conversational virtual assistants but often the technology to do the necessary natural language processing (NLP), graphing for knowledge compilation, and ingestion can be very complex and create a barrier for adoption. Abhi Sharma, a Machine Learning Engineer at Avaamo, joins the Intel on AI Podcast to describe how the Avaamo conversational AI platform enables enterprises to easily deploy high-impact conversational assistants in many different industries and verticals. He shows how Avaamo helps enterprises avoid the traditional cold start program — and because the platform is optimized for Intel Xeon Scalable processors, businesses can achieve high-performance at scale with the existing architecture they already have. Abhi also illustrates how many of the libraries and frameworks that the Avaamo solution is built upon are so fine-tuned to work on Intel Architecture that Avaamo sees incredible performance when running their AI on Intel hardware. To learn more, visit: avaamo.ai Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Dr. Jonathan Hall, Scientific Lead at Presagen, joins the Intel on AI podcast to discuss how Presagen is using artificial intelligence to aid clinician embryo selection for in vitro fertilization (IVF) procedures. Presagen's solution Life Whisperer is a non-invasive cloud based tool that uses AI to analyze images of patient embryos to generate an instant report on the embryo viability. This report enables clinicians to make an incredibly informed decision on which embryos to implant into the IVF patient and has shown to greatly increase the success of IVF procedures. Dr. Hall expresses how important this can be for people who are seeking reproduction assistance through IVF by saving patients time, money, and emotional stress. He also discusses how working with Intel and using a custom version of the Intel Optimization for PyTorch gives the Presagen solution a large speed boost to help make the image analysis even faster. To learn more, visit: presagen.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Tens of Millions of patients every year spend countless hours and billions of dollars on medical scans. Also, medical scans like PET (positron emission technology) or MRI (magnetic resonance imaging) scans can take a long time to conduct and can be very uncomfortable for patients. Enhao Gong, Founder and CEO of Subtle Medical, joins the Intel on AI podcast to share how SubtlePET technology powered by artificial intelligence is enhancing PET image quality significantly, enabling hospitals to provide faster and more efficient PET exams, and helping patients and health care providers save time and money. He talks about how SubtlePET technology utilizes the Intel Distribution of OpenVINO Toolkit to accelerate inference workloads and enables their technology to seamlessly integrate with the existing infrastructure that many hospitals already use. SubtlePET recently received FDA 510k clearance and CE Mark approval which is just the beginning for Subtle Medical and their mission to make medical imaging faster, safer, and smarter. To learn more, visit: subtlemedical.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Sumit Sanyal, Founder and Chief Revenue Officer at Minds.ai, joins Intel on AI to discuss the Minds.ai Netrin Molecular Property Predictor (MPP) and how Minds.ai is driving drug discovery with deep learning. He describes how the minds.ai solution enables pharmaceutical companies to replace traditional labor and time intensive wet lab tests instead using graph convolutional deep neural networks (GCNNs) to make predictions about molecules and target proteins that may be useful in medications. This is revolutionizing the drug discovery industry by accelerating and reducing the cost of molecule testing. Sumit also talks about how minds.ai has been utilizing the Intel Math Kernel Library (MKL) and Intel Xeon Scalable processors to help drive their incredibly fast neural network training. He highlights how using Xeon processors is incredibly efficient in comparison to graphics processing units (GPU) and expresses how helpful the Intel MKL has been for Minds.ai. To learn more, visit: minds.ai Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Vinod Prasad, General Manager & Lead Architect at Wipro Technologies, joins Intel on AI to discuss Wipro medical imaging solutions powered by Intel Architecture and optimizations. He discusses how the medical industry faces many challenges today including the sometimes difficult and time consuming process of diagnosis of patient chest X-rays. Vinod highlights how Wipro is working to help healthcare providers save time and resources while also improving the patient experience. He describes how Wipro is automating medical image segmentation, analysis, and captioning using deep learning (DL) neural networks running on Intel architecture and optimizations. Utilizing Intel technologies like Intel Distribution of OpenVINO toolkit has enabled Wipro to provide their customers with very efficient and cost effective image analysis solutions on premise and at the edge. To learn more, visit: wipro.com And: builders.intel.com/ai/social-hub/podcast/medical-imaging-wipro-intel Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: FPGA (field-programmable gate array) technology can offer a very high level of flexibility and performance, with low latency. Yet, with software writing thresholds, limited performance optimization, and difficult power control, FPGA solutions can also be challenging to implement. Bob Anderson, General Manager of Sales for Strategic Accounts at Inspur, joins Intel on AI to talk about the Inspur TensorFlow-supported FPGA Compute Acceleration Engine (TF2). Bob illustrates how the TF2 helps customers more easily deploy FPGA solutions and take advantage of the customization and performance of FPGAs for AI inference applications. He also describes how the TF2 is especially suitable for image-based AI applications with high real-time requirements. To learn more, visit: inspursystems.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Leonard Sheiba, the Founder and CEO of Kibernetika, joins Intel on AI to talk about the challenges many organizations face when developing artificial intelligence (AI) solutions especially within an enterprise environment at scale. He points out that AI enabled software components like datasets, models, training, and serving involve continuous validation and retraining to work properly and require maintaining a strict process flow to develop in an enterprise environment. Leonard illustrates how the Kibernetika Machine Teaching Engine is an end-to-end platform that manages the entire AI development workflow from concept through decommission. He describes how their platform can serve many organizations and industry verticals including telecom, healthcare, and nearly any enterprise AI deployment. Lastly, Leonard highlights how the Kibernetika platform runs on Intel Xeon Scalable processors driving the power and efficiency that Kibernetika's customers need. To learn more, visit: kibernetika.ai Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: As the amount of data grows exponentially businesses are looking to leverage artificial intelligence (AI) to make real-time decisions with it. Yoav Einav, Vice President of Product at GigaSpaces, joins Intel on AI to discuss how the GigaSpaces InsightEdge platform is enabling enterprises to truly take advantage of their data utilizing in-memory computing for fast data analytics and extreme transaction processing. He illustrates how in-memory analytics allows customers to run analytics workloads on real-time data which provides low latency, high-throughput transaction, and co-location of applications and analytics to act on time-critical data in real-time. Yoav explains how enterprises in many different verticals including financial services, retail, transportation, telecom, healthcare, and others can greatly benefit from this capability. Also, Yoav talks about how Intel Optane Data Center persistent memory provides the foundation for the GigaSpaces InsightEdge platform driving more memory capacity per server driving smarter, faster insights based on larger and more varied data sets. To learn more, visit: gigaspaces.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Dr. Gourab De, Vice President of the Data Science at DataRobot, joins Intel on AI to talk about how DataRobot is helping developers and data scientist build AI models without having to write a single line of code. The DataRobot automated machine learning platform delivers the power of artificial intelligence beyond advanced programmers who are able to work through complicated code to a whole new enterprise audience that can greatly benefit from AI. Dr. De highlights that many different industry verticals that are utilizing the DataRobot platform including banking, healthcare, retails, manufacturing and many more. He also discusses how the DataRobot platform utilizes Intel Xeon Scalable processors as a powerful hardware foundation to deliver optimized performance for organizations in pursuit of low latency and scalability – two key performance features to support the AI-driven enterprise. For more information, visit: datarobot.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: For this Intel on AI podcast episode we are joined by Vinod Iyengar, Vice President of Data Science Transformations at H2O.ai. Vinod highlights some of the challenges that enterprises face today when implementing AI deployments and how H2O.ai is empowering organizations to overcome those hurdles. He discusses how H2O.ai platforms leverage the performance of Intel Xeon Scalable Processors as well as important optimizations like Intel Math Kernel Library (Intel MKL) and Intel Data Analytics Acceleration Library (Intel DAAL) to bring rapid insights to their customers. Also collaborating on Project Blue Danube and Intel AI Builders, Vinod illustrates how together, Intel and H2O.ai are accelerating AI for everyone and helping to democratize AI. For more information, visit www.h2o.ai/. Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Ben Vigoda, the founder and CEO of Gamalon, joins the Intel on AI team to talk about how Gamalon is driving the cutting edge of artificial intelligence and machine learning. He highlights their concept of how idea learning or Bayesian Program Synthesis models can enable enterprises to implement incredible understanding of text-based customer communications. Ben describes how Gamalon's Idea Learning technology learns rapidly and accurately from sparsely labeled training data and enables data scientists to simply enter a series of queries to build a decision tree on the fly based on the text. For more information, visit: gamalon.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Dr. David Ellison, the Senior Artificial Intelligence Data Scientist in the HPC Business Unit at Lenovo joins Intel on AI to discuss the Lenovo Intelligent Computing Orchestration (LiCO). Dr. Ellison explains how LiCO accelerates artificial intelligence (AI) training and traditional high performance computing (HPC) deployment by providing a single software solution that simplifies resource management and the use of a cluster environment. He discusses an exciting real-world deployment where data scientists use LiCO to help analyze satellite images of crop fields to drive drought prevention and increase food security. Another deployment Dr. Ellison highlights is the use of LiCO to help evaluate assembly line product quality implementing computer vision to detect product defects or damage in real time. Dr. Ellison also talks about the great collaboration that Lenovo and Intel are doing through the Intel AI Builders program leveraging resources to help drive software optimizations and improve AI workload performance. To learn more, visit: lenovo.com/ai Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: Leveraging the power and potential of artificial intelligence (AI) deployments can be a top priority for many enterprises today. Yet, deploying and managing AI workloads can be incredibly complex and require extensive integration and testing. Senior Director Global Sales Strategist for HPC and AI at Dell EMC, Adnan Khaleel joins Intel on AI a second time to discuss how Dell EMC is making enterprise AI implementation fast and easy with its Dell EMC Ready Solutions for AI. Their new Ready Solutions for machine learning (ML) are built on a foundation of Intel Xeon processors to drive the fast and extensive AI insights for enterprises today and help to reduce the time it takes to implement a new AI solution. Adnan also illustrates how Dell EMC Ready Solutions are well suited for many different industries including financial services, insurance, pharmaceuticals and many more. For more information about Dell EMC and their Ready Solutions for AI, visit: dellemc.com Visit Intel AI Builders at: builders.intel.com/ai

In this Intel on AI podcast episode: we are joined by Gene Saragnese, Chairman of the Board and CEO of MaxQ AI, discussing how Artificial Intelligence (AI) is a critical technology in the healthcare industry today and is rapidly revolutionizing advanced healthcare systems, such as imaging. MaxQ AI is at the forefront of this healthcare transformation developing a suite of bedside, clinical, diagnostic decision-making tools for emergency room care within the acute care space. Gene describes their initial product, the Accipio lx software platform, which is focused on treating head trauma and stroke trained to automatically analyze CT images for intracranial hemorrhage. For more information, visit: maxq.ai Or: builders.intel.com/ai/blog/maxq-ai-deep-learning Visit Intel AI Builders at: builders.intel.com/ai

Radha Basu, CEO and Founder of iMerit, joins Intel on AI to talk about how human-empowered computing will drive the future of AI. iMerit specializes in human driven data annotation, enrichment, and natural language processing which is then utilized to help train AI algorithms across the world. Radha explains her mission of bringing diverse talent from underprivileged communities into the digital workforce to help create needed jobs and empower communities. She also illustrates how iMerit able to deliver enterprise-grade data & digital services globally for companies in machine learning, eCommerce and computer vision in an ethically minded way. To learn more, visit: imerit.net Or: builders.intel.com/ai/membership/imerit Intel AI Builders: builders.intel.com/ai

James Jacobs, Co-Founder & Co-CEO of Ziva Dynamics, joins Intel on AI to talk about the incredible work that Ziva Dynamics does to bring computer-generated characters to life for major films. Ziva Dynamics created an AI-based solution which addresses the huge challenges visual effects (VFX) artists face when building and modeling virtual humans and creatures. James expresses how Ziva's solutions along with Intel Xeon Scalable processors and Intel architecture optimized frameworks enable artists to make cutting edge characters incredibly fast. He highlights the recent feature film The Meg as an excellent use case of Ziva software and Intel technology. To learn more, visit: zivadynamics.com Or: ai.intel.com/ziva-dynamics Intel AI Builders: builders.intel.com/ai

Join Domino Data Labs Director of Product Mac Steele on another edition of Intel on AI. Mac illustrates the workflow challenges that many data scientists face today and how Domino's Data Science Platform enables data science and quantitative research teams to create mature, disciplined, and scalable processes for developing models and algorithms. He also discusses the work that Domino has done on the Intel Distribution for Python and the incredible results that Domino achieved running workloads on the distribution. To learn more, visit: dominodatalab.com blog.dominodatalab.com/intels-python-distribution-is-smoking-fast-and-now-its-in-domino Intel AI Builders: builders.intel.com/ai

Intel on AI: Adnan Kahleel, Senior Director Global Sales Strategist for HPC and AI at Dell EMC, joins hosts Alexis Fink and Emily Hutson on this inaugural episode of the Intel on AI podcast. Adnan discusses how Intel and Dell EMC are working together to power some of the fastest supercomputers on the planet pushing the limits of machine learning and deep learning today. He also highlights Dell EMC's activities at the 2018 SuperComputing Conference and their announcement that the upcoming super computer system called Frontera from the National Science Foundation (NSF) and Texas Advanced Computing Center (TACC) will be supplied by Dell EMC and powered primarily by Intel Xeon processors. For more information about Dell EMC and their work with Intel, visit: dellemc.com For more on AI see: builders.intel.com/ai