Gramener Image Recognition and Intel AI Saving Antarctic Penguins – Intel on AI – Episode 35

In this episode of Intel on AI host Amir Khosrowshahi and Melanie Mitchell talk about the paradox of studying human intelligence and the limitations of deep neural networks. Melanie is the Davis Professor of Complexity at the Santa Fe Institute, former professor of Computer Science at Portland State University, and the author/editor of six books and numerous scholarly papers in the fields of artificial intelligence, cognitive science, and complex systems, including Complexity: A Guided Tour and Artificial Intelligence: A Guide for Thinking Humans.  In the episode, Melanie and Amir discuss how intelligence emerges from the substrate of neurons and why being able to perceive abstract similarities between different situations via analogies is at the core of cognition. Melanie goes into detail about deep neural networks using spurious statistical correlations, the distinction between generative and discriminative systems and machine learning, and the theory that a fundamental part of the human brain is trying to predict what is going to happen next based on prior experience. She also talks about creating the Copycat software, the dangers of artificial intelligence (AI) being easy to manipulate even in very narrow areas, and the importance of getting inspiration from biological intelligence. Academic research discussed in the podcast episode: Gödel, Escher, Bach: an Eternal Golden Braid Fluid Concepts and Creative Analogies: Computer Models Of The Fundamental Mechanisms Of Thought A computational model for solving problems from the Raven’s Progressive Matrices intelligence test using iconic visual representations A Framework for Representing Knowledge On the Measure of Intelligence The Abstraction and Reasoning Corpus (ARC) Human-level concept learning through probabilistic program induction Why AI is Harder Than We Think We Shouldn’t be Scared by ‘Superintelligent A.I.’ (New York Times opinion piece)

3 Nov 202137min

In this episode of Intel on AI host Amir Khosrowshahi and Bruno Olshausen talk about neuroscience and the future of computing. Bruno is a professor at Berkeley with appointments in the Helen Wills Neuroscience Institute and School of Optometry. He is also the director of the Redwood center for Theoretical Neuroscience, which brings the fields of physics, mathematics, engineering, and neuroscience together to study how networks of neurons in the brain process information. In the episode, Bruno and Amir discuss research about recording large populations of neurons, hyperdimensional computing, and discovering new types of engineering principles. Bruno talks about how in order to understand intelligence and its underpinnings, we have to understand the origins of intelligence and perceptual psychology outside of mammalian brains. He points to the sophisticated visual system of jumping spiders as inspiration for developing systems that use low energy in a small form factor. By better understanding the origins of perception and other biophysical structures, Bruno theorizes the artificial intelligence field may evolve beyond image recognition tasks of current neural networks. Bruno and Amir close the episode by talking about the elementary units of computation, the idea of “listening to silicon” as proposed by Carver Mead, neuromorphic computing, and what the future of research might hold. Academic research discussed in the podcast episode: Spatially Distributed Local Fields in the Hippocampus Encode Rat Position Beyond inspiration: Three lessons from biology on building intelligent machines The Chinese Room Argument Digital tissue and what it may reveal about the brain Principles of Neural Design (Bruno calls this a “must read”) Experiencing and Perceiving Visual Surfaces Analog VLSI Implementation of Neural Systems OIM: Oscillator-based Ising Machines for Solving Combinatorial Optimisation Problems

29 Sep 202143min

In this episode of Intel on AI host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times Best Selling Author, passes the hosting mantle to Amir Khosrowshahi, Intel Vice President. The two talk about lessons learned from guests across Season 2 of the podcast and what the AI of tomorrow might be. Abigail shares about some exciting next steps for her. Amir discusses his background studying neurobiology and theoretical physics, his research in computational neuroscience and mammalian visual systems at UC Berkeley, his work at Intel following the acquisition of Nervana, and his plans for hosting Season 3 of the podcast. Follow Abigail on Twitter: twitter.com/abigailhingwen Follow Amir on Twitter: twitter.com/khosra

8 Mars 202124min

In this episode of Intel on AI guest US Congresswoman Robin Kelly talks with host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times best-selling author, about artificial intelligence (AI) and the United States government. Congresswoman Kelly talks about how she became involved in AI policy, introducing a bipartisan resolution to create a national AI strategy with Will Hurd (R-Texas), and educating other Congress members about the field. The two also talk about the importance of training new talent in order for America to stay competitive in a global market and why ethics in AI is crucial when considering regulation. Follow Congresswoman Kelly on Twitter: twitter.com/reprobinkelly Follow Abigail on Twitter: twitter.com/abigailhingwen

18 Feb 202117min

In this episode of Intel on AI guest Aviv Regev, Executive Vice President of Genentech Research and Early Development, talks with host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times best-selling author, about biomedicine and artificial intelligence (AI). The two discuss Aviv’s work on circuitry in cells, the future of experimental biology, why increasing the diversity of data is key to creating algorithms that can find patterns in genomic variants, and how strengthening global networks will help society better prepare for the next pandemic. Hear more from Aviv in a special episode of Genentech’s science podcast “Studying the Symphony of Cells.” Follow Genentech on Twitter: twitter.com/genentech Follow Abigail on Twitter: twitter.com/abigailhingwen Learn more about Intel’s work in AI: intel.com/ai

11 Feb 202143min

In this episode of Intel on AI guest Terah Lyons, Executive Director of Partnership on AI, talks with host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times best-selling author, about her previous work as Policy Advisor to the United States Chief Technology Officer Megan Smith in President Barack Obama’s Office of Science and Technology Policy, her thoughts on the role policymakers should play in the field of artificial intelligence (AI), and the ongoing efforts of the Partnership on AI. The two discuss how organizations can align their values and prioritize incentives around developing AI that helps workers, the importance of measuring such outcomes, and why practical frameworks for AI can help people outside the field better understand the benefits of AI. Follow Terah on Twitter: twitter.com/terahlyons Follow Abigail on Twitter: twitter.com/abigailhingwen Learn more about Intel’s work in AI: intel.com/ai

13 Jan 202135min

In this episode of Intel on AI guest Colin Murdoch, Senior Business Director at DeepMind, talks with host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times best-selling author, about text-to-speech system WaveNet, the recent breakthrough with AlphaFold, the potential for artificial intelligence to solve energy challenges, and how Google adopts cutting-edge research into a number of services. The two also discuss examples like AlphaGo, GraphNet, advancements in Android products, and what the future of artificial general intelligence might look like. Follow DeepMind on Twitter: twitter.com/DeepMind Follow Abigail on Twitter: twitter.com/abigailhingwen Learn more about Intel’s work in AI: intel.com/ai

23 Dec 202036min

In this episode of Intel on AI guest Alice Xiang, Head of Fairness, Transparency, and Accountability Research at the Partnership on AI, talks with host Abigail Hing Wen, Intel AI Tech Evangelist and New York Times best-selling author, about algorithmic fairness—the study of how algorithms might systemically perform better or worse for certain groups of people and the ways in which historical biases or other systemic inequities might be perpetuated by algorithmic systems. The two discuss the lofty goals of the Partnership on AI, why being able to explain how a model arrived at a specific decision is important for the future of AI adoption, and the proliferation of criminal justice risk assessment tools. Follow Alice on Twitter: twitter.com/alicexiang Follow Abigail on Twitter: twitter.com/abigailhingwen Learn more about Intel’s work in AI: intel.com/ai

16 Dec 202035min