729: Universal Principles of Intelligence (Across Humans and Machines), with Prof. Blake Richards
Dr. Blake Richards discusses the world of AI and human cognition this week. Learn about the essence of intelligence, the ways AI research informs our understanding of the human brain, and discover the potential future scenarios where AI and humanity might intersect.
This episode is brought to you by Gurobi, the Decision Intelligence Leader, and by CloudWolf, the Cloud Skills platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.
In this episode you will learn:
• Blake's research and his take on intelligence [09:56]
• How we can evaluate progress in artificial general intelligence [15:54]
• Blake's thoughts on biomimicry [20:57]
• Why Blake thinks the fears regarding AI are overdone [25:38]
• The most effective strategies to mitigate AI fears without hindering innovation [35:31]
• What steps can we take to ensure that AI supports human flourishing [45:23]
• The importance of interpreting neuroscience data through the lens of ML [55:08]
• Backpropagation, gradient descent and the brain [1:17:32]
Additional materials: www.superdatascience.com/729
Hierarchical and Continual RL with Doina Precup - #567
Today we’re joined by Doina Precup, a research team lead at DeepMind Montreal, and a professor at McGill University. In our conversation with Doina, we discuss her recent research interests, including her work in hierarchical reinforcement learning, with the goal being agents learning abstract representations, especially over time. We also explore her work on reward specification for RL agents, where she hypothesizes that a reward signal in a complex environment could lead an agent to develop attributes of intuitive intelligence. We also dig into quite a few of her papers, including On the Expressivity of Markov Reward, which won a NeruIPS 2021 outstanding paper award. Finally, we discuss the analogy between hierarchical RL and CNNs, her work in continual RL, and her thoughts on the evolution of RL in the recent past and present, and the biggest challenges facing the field going forward.
The complete show notes for this episode can be found at twimlai.com/go/567
David Rolnick on how machine learning can help tackle climate change
While the world’s temperature rises, there are scores of scientists working around the globe to study causes and solutions. One scientist in particular, David Rolnick, has stood out as a pioneer of machine-learning in the fight against climate change.
David successfully built a broader movement including others like Andrew Ng, Yoshua Bengio, Demis Hassabis, and Jennifer Chayes to champion the amazing possibilities that exist at the intersection of AI and the climate. He organized the first-ever ever AI event at the United Nations Climate Change Conference. He was named a top innovator by the MIT Technology Review -- all before the age of 30.
He sits down with Pieter to discuss his landmark paper on the applications of ML to climate change looking at use cases like weather simulations, ecological monitoring, and predicting natural resource depletion.
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| Host: Pieter Abbeel | Executive Producers: Alice Patel & Henry Tobias Jones | Audio Production: Kieron Matthew Banerji | Title Music: Alejandro Del Pozo
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Robot as Threat
When a robot goes bad, who is responsible? It’s not always clear if the user or the manufacturer is liable when a robot leaves the lot. Human behavior can be complex—and often contradictory. Asking machines to interpret that behavior is quite the task. Will it one day be possible for a robot to have its own sense of right and wrong? And barring robots acting of their own accord, whose job is it to make sure their actions can’t be hijacked?
AJung Moon explains the ethical ramifications of robot AI. Ryan Gariepy talks about the levels of responsibility in robotic manufacturing. Stefanie Tellex highlights security vulnerabilities (and scares us, just a little). Brian Gerkey of Open Robotics discusses reaching the high bar of safety needed to deploy robots. And Brian Christian explores the multi-disciplinary ways humans can impart behavior norms to robots.
If you want to read up on some of our research on robots as threats, you can check our all our bonus material over at redhat.com/commandlineheroes. Follow along with the episode transcript.
Sensory Prediction Error Signals in the Neocortex with Blake Richards - #331
Today we continue our 2019 NeurIPS coverage, this time around joined by Blake Richards, Assistant Professor at McGill University and a Core Faculty Member at Mila. Blake was an invited speaker at the Neuro-AI Workshop, and presented his research on “Sensory Prediction Error Signals in the Neocortex.” In our conversation, we discuss a series of recent studies on two-photon calcium imaging. We talk predictive coding, hierarchical inference, and Blake’s recent work on memory systems for reinforcement lea
AI4Good: Canadian Lab Empowers Women in Computer Science - Ep. 103
Doina Precup is applying Romanian wisdom to the gender gap in the fields of AI and computer science.
The associate professor at McGill University and research team lead at AI startup DeepMind spoke with AI Podcast host Noah Kravitz about her personal experiences, along with the AI4Good Lab she co-founded to give women more access to machine learning training.
Growing up in Romania, Precup attended a high school that specialized in computer science and a technical university. She didn’t experience gender disparity in these learning environments.
“If anything, programming was considered a very good job for women, because you did not need to be working in the fields,” she explained.
It made the gap in Canadian universities and companies even more noticeable. At McGill, Precup saw that female students were hesitant to speak up or pursue graduate studies.
Together with Angelique Mannella, CEO of AM Consulting and an Amazon employee, Precup was inspired to start the AI4Good Lab in 2017.
Episode 24 - Climate Change and AI
A few months ago at the recent international conference on machine learning, a workshop and research paper launched a movement to use machine learning in addressing climate change. The response was huge and has given birth to the bones of an organization climate change.ai. This week I talked to David Rolnick, a postdoc at U Penn and Priya, Donti, a Phd student at Carnegie Mellon, about how the group came together and about how the organization is developing.
Classical Machine Learning for Infant Medical Diagnosis with Charles Onu - TWiML Talk #112
In this episode, part 4 in our Black in AI series, i'm joined by Charles Onu, Phd Student at McGill University in Montreal & Founder of Ubenwa, a startup tackling the problem of infant mortality due to asphyxia. Using SVMs and other techniques from the field of automatic speech recognition, Charles and his team have built a model that detects asphyxia based on the audible noises the child makes upon birth. We go into the process he used to collect his training data, including the specific methods they used to record samples, and how their samples will be used to maximize accuracy in the field. We also take a deep dive into some of the challenges of building and deploying the platform and mobile application. This is a really interesting use case, which I think you’ll enjoy. Join the #MyAI Discussion! As a TWiML listener, you probably have an opinion on the role AI will play in our lives, and we want to hear your take. Sharing your thoughts takes two minutes, can be done from anywhere, and qualifies you to win some great prizes. So hit pause, and jump on over twimlai.com/myai right now to share or learn more. Be sure to check out some of the great names that will be at the AI Conference in New York, Apr 29–May 2, where you'll join the leading minds in AI, Peter Norvig, George Church, Olga Russakovsky, Manuela Veloso, and Zoubin Ghahramani. Explore AI's latest developments, separate what's hype and what's really game-changing, and learn how to apply AI in your organization right now. Save 20% on most passes with discount code PCTWIML at twimlai.com/ainy2018. The notes for this show can be found at twimlai.com/talk/112. For complete contest details, visit twimlai.com/myai. For complete series details, visit twimlai.com/blackinai2018.