Eye On A.I.

Jacki Morie, a senior XPRIZE advisor, talks about the ANA Avatar XPRIZE, a competition focused on creating a physical avatar system that will seamlessly transport human skills and experience to distant locations. The four-year competition is in its final stretch.

Aaron Patzer, founder of the personal finance app MINT and more recently founder of the AI-based healthcare company Vital, talks about keeping customer data private and the promise, giving emergency room patients information with AI and finding friendly solutions to anxiety-producing problems.

Rohit Prasad, Amazon's Senior Vice President and Head Scientist for Alexa, speaks about the development of conversational AI and virtual assistants and the merging of IoT sensor data into ambient intelligence - AI that is always present and immediately accessible.

Ken Washington, who leads Amazon's consumer robotics team, talks about the company's compact wheeled robot called Astro. Ken talked about Astro's evolution, it's popular and possible use cases, and what might be in store in the future.

Almammon Rasool Abdali, a machine-learning engineer and PhD student in Baghdad, is one of the more prominent members of Iraq's small but growing deep learning community. We talked about his work, which involves vision systems to detect violence, and about the state of artificial intelligence research and teaching in the country generally.

Ma Yanjun, General Manager of the AI Technology Ecosystem at Baidu, talks about how Baidu's PaddlePaddle stacks up against other AI frameworks, about Baidu's development of large language models and the direction of AI research in China more generally.

Oriol Vinyals, who leads DeepMind's deep learning team, talks about AlphaCode, his group's code-writing language model, and DeepMind's winding road toward artificial general intelligence.

Tom Denton, a software engineer in Google's bioacoustics group, talks about new algorithms to separate individual bird songs from the cacophony of the forest - and gives some examples. The Eye on AI podcast is sponsored by ClearML, the MLOps solution.

Andrew Ng, founder of Google Brain, Coursera and Landing AI, talks about his vision of data-centric AI, MLOps and the future of supervised vs unsupervised learning. The Eye on AI podcast is sponsored by ClearML.

Tom Siebel, founder and CEO of C3.ai talks about AI projects including military target acquisition and precision healthcare while musing about the dark side of our technological future. The Eye on AI podcast is sponsored by Clear.ML

Max Bileschi, a software engineer at Google Research, talks about his team's application of convolutional neural networks to predict the function of amino acid sequences in a protein. Eye on AI is sponsored by Clear.ML.

Pushmeet Kohli, the head of DeepMind's AI for Science and one of the brains behind AlphaFold, the machine learning system that is helping solve the protein folding problem. The episode is sponsored by Clear.ML, an open-source MLOps solution.

Currently the largest AI system in the world is China's WuDao 2.0, a sparse, multimodal, large language model with 1.75 trillion parameters. Tang Jie, a professor at China's Qinghua University, who leads the WuDao team, talks about how the model was built, why it is unique and what his team plans for the future.

Connor Leahy, one of the minds behind Eleuther AI and its open-source large language model, GPT-J, talks about the building such models and their implications for the future.

Robert O. Work, former Deputy Secretary of Defense and recently co-chairman of the National Security Commission on AI, talks about competition between the US and China to integrate AI into their military capabilities.

Stephen DeAngelis, head of Enterra Solutions, reminds us that so-called Old-Fashioned AI continues to be a powerful tool. He talked about leveraging knowledge bases, inference engines and symbolic logic to make decisions about large dynamic systems.

Daniel Ho, associate director of Stanford's Institute for Human-Centered Artificial Intelligence talks about the proposed National AI Research Resource, an effort to expand the data and compute available to academic researchers, leveling the playing field with researchers in private companies.

Andrew Feldman, one of the founders and CEO of Cerebras Systems, talks about the company's wafer-scale computer chip optimized for machine learning and about the network of chips that company has built that has as much computing power as a human brain.

Adobe's head of research, Gavin Miller, talks about AI-enhanced creativity, guarding against manipulation of visual media and his own AI-enabled robot snakes.

Seth Dobrin, chief AI officer at IBM, talks about the company's tools to increase the trustworthiness, fairness and explainability of AI models.

This week, I talk to Ron Schmelzer and Kathleen Walch, founders of Cognilytica, a research, advisory, and education firm focused on artificial Intelligence. We talked about the rise of MLOps, data labeling, unsupervised learning and what it will take to get us to human-level artificial general intelligence.

This week I talk to the inimitable Ben Goertzel, about his non-profit foundation, SingularityNET, his work with the robotic head, Sophia, his talking Philip K. Dick avatar, his work in medical AI, his frustration over Big Tech's dominance of AI research and his own quest for AGI.

AI commentator and investor Kaifu Lee talks about his book AI 2041 in which he considers possible futures for humanity if deep learning applications develop as planned.

NSCAI staff Justin Lynch, Ryan Carpenter and Lance Lantier talk about how the 1986 Goldwater Nichols Act that reorganized the US military inspired the commission's recommendations to reorganize the Department of Defense to drive adoption of emerging and disruptive technology capabilities.

NSCAI staff Christie Lawrence and Rama Elleru talk about how intellectual property protections play an unexpected role in guiding US innovation and contribute to the global competition with China for dominance in AI.

NSCAI staff Tess Deblanc-Knowles and Mike Garris talk about the steps the US government needs to take to foster AI innovation in the years ahead.

NSCAI staff Paul Leka and Christie Lawrence talk about forming an international emerging technology coalition to strengthen and coordinate the use of emerging technology for democratic ends.

NSCAI staff Mike Garris and Mike Jackson spoke about what needs to be done to lay the foundations for an AI-infused national security going forward.

NSCAI staff Aristotle Vainikos and Parker Wild spoke about the commission's recommendations for establishing public-private innovation hubs around the country that can encourage and tap the entrepreneurial potential between the coasts and expand the participation of private enterprise in national security.

NSCAI staff Mike Jackson and Darren Wright talk about the commission's recommendations for bringing the intelligence community up to speed with AI. They spoke about the organizational changes needed and the culture shift required to ensure that the intelligence community is integrating AI in its work.

NSCAI staff David Kumashiro and Courtney Barno talked about the commission's recommendations on democratizing AI for the warfighter and enabling bottom-up AI innovation.

NSCAI staff Kevin McGuinness and Raina Davis talked about the commission's recommendations for increasing public visibility about the government's AI needs and lowering the barrier to entry for companies that want to help meet those needs.

NSCAI staff Chris Rice and Courtney Barno talk about what the US has to do to get up to speed on its AI military capabilities by 2025 in order to outpace our competitors, particularly China.

NSCAI staff Justin Lynch, Lance Lantier and Shaantam Chawla, talked about educating the warfighter for the AI era. They spoke about what kind of training warfighters need to effectively integrate AI, from commanders to infantry men and women and how that integration will change the nature of warfare and the military's perception of itself in the years ahead.

Ylli Bajraktari, executive director of the National Security Commission on AI, talked about what he considers the most important recommendations in the commission's final report and about the need for Congress and the White House to act swiftly to counter China's concerted efforts to beat the US in deploying this critical technology around the world.

This week, I talk to Cade Metz, the New York Times' lead reporter on artificial intelligence, about his new book, "Genius Makers, the Mavericks Who Brought AI to Google Facebook and the World." The book focuses on some of the personalities and companies responsible for the current wave of AI innovation and touches on some of the controversies swirling around the new technology today.

Kent Walker, who oversees the Google's AI ethics and responsible AI innovation, talks about how Google reviews AI systems for trust and safety and the outlook for safe AI going forward.

Daeil Kim, cofounder of AI.Reverie, talks about the role that synthetic data can play in training AI models.

Alan Aspuru Guzik, a professor at the University of Toronto, talks about his work in new materials discovery with machine learning and building a fully automated materials lab that can synthesize molecules discovered in a computer.

Director of the Pentagon's Joint AI Center, Lieutenant General Michael S. Groen talks about improving war fighting and the challenge of China.

David Yi and Yohan Lee from Riiid Labs, the leading startup applying machine-learning to education, talk about making personalized instruction available to anyone in the world with an internet-connected device. They spoke about the family of algorithms behind their system and the recently concluded Riiid AIEd Challenge, a Kaggle competition that engaged more than 3,400 teams across the world in developing knowledge tracing algorithms.

Turing award winner Yoshua Bengio and his colleague Julian Serban, co-founder of Korbit, an AI ed-tech startup with the aim of democratizing education, talk about enhancing education through the application of deep learning systems that can track student behavior predict their performance and deliver strategies to both improve performance and prevent students from losing interest.

Geoff Hinton has lived at the outer reaches of machine learning research since an aborted attempt at a carpentry career a half century ago. He spoke to me about his work In 2020 and what he sees on the horizon for AI.

Chris Darby, CEO of the CIA-backed tech investment company In-Q-Tel, talks about the commission's recommendation that AI for national security be extended to biotechnology, and that bio-data be considered an instrument of national power.

Eric Horvitz, chief research scientist at Microsoft and a commissioner on the National Security Commission on AI, talks about ensuring interoperability of AI systems with US allies and working to make all AI systems reliable.

An open-source compiler called TVM helps data scientists optimize their model's performance on specific hardware.

NSCAI commissioner Steve Chien, technical supervisor of the artificial intelligence group at NASA's Jet Propulsion Laboratory, talks about the growing demand for AI solutions in space, from coordinating an increasing number of earth-orbiting objects to protecting critical communication satellites from attack.

This week, NSCAI commissioner Jose-Marie Griffiths talks about her line of effort's recommendations to increase STEM related educational funding by $8 billion in order to prime the pump for an AI ready workforce and to make a variety of bureaucratic changes that will open AI related career pathways for government employees.

Jason Matheny, a commissioner at the National Security Commission on AI and head of Georgetown University's Center for Security and Emerging Technology, talks about coordinating AI developments with NATO and making India the focus of the US's Indo-Pacific AI strategy to counter China.

Alex Ratner, an assistant professor at the University of Washington and a cofounder and CEO of Snorkel AI, talks about programmatically labeling training data for supervised learning models.