All Episodes
BI 029 Paul Humphreys & Zac Irving: Emergence & Mind Wandering
Paul, Zac, and I discuss the philosophy of emergence, the neuroscience and philosophy of mind wandering and spontaneous thought, and how both of these may fit in the realm of artificial intelligence and consciousness. Plus, we talk about the role of philosophy in neuroscience and AI, and more.
BI 028 Sam Gershman: Free Energy Principle & Human Machines
Sam and I talk about the Free Energy Principle and how it relates to the Bayesian Brain Hypothesis, all under the realm of predictive coding. We also discuss some of the ingredients currently missing from deep learning approaches if we want machines to learn and think more like humans.
BI 027 Ioana Marinescu & Konrad Kording: Causality in Quasi-Experiments
Ioana, Konrad, and I talk about ways causality can be inferred using data from quasi-experiments, the role economics and econometrics has played, causality in AI, some of the ins and outs of marriage in academia, and plenty more.
BI 026 Kendrick Kay: A Model By Any Other Name
Kendrick and I discuss his models that predict how the human brain responds to pictures of faces and words, how we make decisions about those pictures, and how our brain gears up for such tasks. We also discuss models in general- what they are, how we should judge them, and so on, plus a few of his other projects and…. wait for it… lots more.
BI 025 John Krakauer: Understanding Cognition
John and I discuss how understanding behaviors first will improve understanding how brains generate those behaviors, the state of neuroscience, plus the role of philosophy in science, lots of resources along those lines, and lots more.
BI 024 Tim Behrens: Cognitive Maps
Tim and I discuss his work suggesting grid cell-like coding could provide a map for us to navigate abstract concepts in our minds – a cognitive map. We talk about the discovery of place cells and grid cells and the work suggesting they contribute to spatial navigation. We also touch on how Tim’s work is related to meta-reinforcement learning (a la Matt Botvinick, see episode 21), and how grid cell codes might contribute to AI systems moving forward.
BI 023 Marcel van Gerven: Mind Decoding with GANs
Marcel and I discuss his recent work using generative adversarial networks to decode brain activity to reconstruct images people saw, his work to restore vision to blind humans by stimulating early visual cortex, general AI, and even — shutter — consciousness a bit.
BI 022 Melanie Mitchell: Complexity, and AI Shortcomings
Melanie and I talk about the limitations of artificial intelligence in its current deep learning state (a la her New York Times Op-Ed), what AI needs to proceed toward general AI, what complexity is and how it relates to the fields of AI and neuroscience, and plenty more.
BI 021 Matt Botvinick: Neuroscience and AI at DeepMind
Matt and I discuss his neuroscience and AI research at DeepMind, including how AI benefits from neuroscience, his work on meta-reinforcement learning to create systems that learn more efficiently, how meta-reinforcement learning might be implemented in a neural circuit involving the prefrontal cortex and the dopamine system, how theory of mind might be implemented in machines to help them understand each other and to help us understand them, and a lot more.
BI 020 Anna Wexler: Stimulate Your Brain?
Anna and I discuss home and DIY use of neurotechnology- specifically transcranial direct current stimulation (tDCS) and electroencephalography (EEG) products marketed to improve cognition. We talk about who uses these products and for what (enhancement or self-treatment), how they get marketed, and the possibilities for how they may get regulated.
BI 019 Julie Grollier: Spintronic Neuromorphic Nano-Oscillators!
Julie and I discuss her work using spintronic nano-devices to implement bio-inspired computing and neural networks in hardware. We talk about neuromorphic chips in general, their history, how they could solve the energy efficiency problem, where it’s all headed, some of the physics behind her nano-oscillators, and more.
BI 018 Dean Buonomano: Time in Brains and AI
Dean and I talk about how time and duration is encoded in the brain, how he implemented timing and sequences using short-term synaptic plasticity, in neuronal cultures, and in recurrent neural networks. We also discuss the subjective nature of time, consciousness, and how time might be implemented in future general AI.
BI 017 Jeff Hawkins: Location, Location, Location
Jeff and I discuss his new framework to understand how our cortex functions by building models of complete objects in all the cortical columns throughout the cortex. We also talk about his book On Intelligence, and I get his take on a number of other topics.
BI 016 Ryota Kanai: Artificial Consciousness
Ryota and I discuss his two goals – to implement the functions of consciousness, and to figure out how to measure whether a given system (human, AI, etc) has consciousness. We also talk about his paper implementing curiosity and empowerment as intrinsic motivation in a reinforcement learning AI agent. Plus much more.
BI 015 Terrence Sejnowski: How to Start a Deep Learning Revolution
Terry and I talk about his new book, The Deep Learning Revolution, about the past, present, and future of deep learning. Plus his super-popular online course Learning How To Learn with Barbara Oakley.
BI 014 Konrad Kording: Regulators, Mount Up!
Konrad and I discuss his work automatically detecting potential image fraud in scientific papers, his take on consciousness, and plenty more.
BI 013 Dileep George: Vicarious Robot AI
Dileep and I talk about how his company, Vicarious, aims to create general artificial intelligence for robots, using tons of inspiration from brain structure and function. We also discuss his recent graphical model that, among other things, breaks CAPTCHAs with very few training examples.
BI 012 Niko Kriegeskorte: Black Box, White Box
Niko and I discuss cognitive computational neuroscience as an emerging fusion between cognitive science, computational neuroscience, and artificial intelligence – and how it all fits together. Plus we talk about the conference by that name.