Universal Principles of Intelligence (Across Humans and Machines), with Prof. Blake Richards

Today's episode is wild! The exceptionally lucid Prof. Blake Richards will blow your mind on what intelligence is, why the "AGI" concept isn't real, why AI doesn't pose an existential risk to humans, and how AI could soon directly update our thoughts.

Blake: 
• Is Associate Professor in the School of Computer Science and Department of Neurology and Neurosurgery at the revered McGill University in Montreal. 
• Is a Core Faculty Member at Mila, one of the world’s most prestigious A.I. research labs, which is also in Montreal. 
• His lab investigates universal principles of intelligence that apply to both natural and artificial agents and he has received a number of major awards for his research. 
• He obtained his PhD in neuroscience from the University of Oxford and his Bachelor’s in cognitive science and AI from the University of Toronto.

Today’s episode contains tons of content that will be fascinating for anyone. A few topics near the end, however, will probably appeal primarily to folks who have a grasp of fundamental machine learning concepts like cost functions and gradient descent.

In this episode, Blake details: 
• What intelligence is.
• Why he doesn’t believe in Artificial General Intelligence (AGI).
• Why he’s skeptical about existential risks from A.I.
• The many ways that A.I. research informs our understanding of how the human brain works. 
• How, in the future, A.I. could practically and directly influence your thoughts and behaviors through brain-computer interfaces (BCIs).

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Llama 2, Toolformer and BLOOM: Open-Source LLMs with Meta’s Dr. Thomas Scialom

Thomas Scialom, PhD is behind many of the most popular Generative A.I. projects including Llama 2, the world's top open-source LLM. Today, the Meta A.I. researcher reveals the stories behind Llama 2 and what's in the works for Llama 3.

Thomas:
• Is an A.I. Research Scientist at Meta.
• Is behind some of the world’s best-known Generative A.I. projects including Llama 2, BLOOM, Toolformer and Galactica.
• Is contributing to the development of Artificial General Intelligence (AGI).
• Has lectured at many of the top A.I. labs (e.g., Google, Stanford, MILA).
• Holds a PhD from Sorbonne University, where he specialized in Natural-Language Generation with Reinforcement Learning.

Today’s episode should be equally appealing to hands-on machine learning practitioners as well as folks who may not be hands on but are nevertheless keen to understand the state-of-the-art in A.I. from someone who’s right on the cutting edge of it all.

In this episode, Thomas details: 
• Llama 2, today’s top open-source LLM, including what is what like behind the scenes developing it and what we can expect from the eventual Llama 3 and related open-source projects.
• The Toolformer LLM that learns how to use external tools.
• The Galactica science-specific LLM, why it was brought down after a few days, and how it might eventually re-emerge in a new form.
• How RLHF — reinforcement learning from human feedback — shifts the distribution of generative A.I. outputs from approximating the average of human responses to excellent, often superhuman quality.
• How soon he thinks AGI — artificial general intelligence — will be realized and how.
• How to make the most of the Generative A.I. boom as an entrepreneur.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Image, Video and 3D-Model Generation from Natural Language, with Dr. Ajay Jain

Today, brilliant ML researcher Ajay Jain, Ph.D explains how a full-length feature film could be created using Stable-Diffusion-style generative A.I. — these models can now output flawless 3D models and compelling video clips.

Ajay:
• Is a Co-Founder of Genmo AI, a platform for using natural language to generate stunning state-of-the-art images, videos and 3D models.
• Prior to Genmo, he worked as a researcher on the Google Brain team in California, in the Uber Advanced Technologies Group in Toronto and on the Applied Machine Learning team at Facebook.
• Holds a degree in Computer Science and Engineering from MIT and did his PhD within the world-class Berkeley A.I. Research (BAIR) lab, where he specialized in deep generative models.
• Has published highly influential papers at all of the most prestigious ML conferences, including NeurIPS, ICML and CVPR.

Today’s episode is on the technical side so will likely appeal primarily to hands-on practitioners, but we did our best to explain concepts so that anyone who’d like to understand the state of the art in image, video and 3D-model generation can get up to speed.

In this episode, Ajay details:
• How the Creative General Intelligence he’s developing will allow humans to express anything in natural language and get it.
• How feature-length films could be created today using generative A.I. alone.
• How the Stable Diffusion approach to text-to-image generation differs from the Generative Adversarial Network approach.
• How neural nets can represent all the aspects of a visual scene so that the scene can be rendered as desired from any perspective.
• Why a self-driving vehicle forecasting pedestrian behavior requires similar modeling capabilities to text-to-video generation.
• What he looks for in the engineers and researchers he hires.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

The (Short) Path to Artificial General Intelligence, with Dr. Ben Goertzel

Today, the luminary Dr. Ben Goertzel details how we could realize Artificial General Intelligence (AGI) in 3-7 years, why he's optimistic about the Artificial Super Intelligence (ASI) this would trigger, and what post-Singularity society could be like.

Dr. Goertzel:
• Is CEO of SingularityNET, a decentralized open market for A.I. models that aims to bring about AGI and thus the singularity that would transform society beyond all recognition.
• Has been Chairman of The AGI Society for 14 years.
• Has been Chairman of the foundation behind OpenCog — an open-source AGI framework — for 16 years.
• Was previously Chief Scientist at Hanson Robotics Limited, the company behind Sophia, the world’s most recognizable humanoid robot.
• Holds a PhD in mathematics from Temple University and held tenure-track professorships prior to transitioning to industry.

Today’s episode has parts that are relatively technical, but much of the episode will appeal to anyone who wants to understand how AGI — a machine that has all of the cognitive capabilities of a human — could be brought about and the world-changing impact that would have.

In the episode, Ben details: 
• The specific approaches that could be integrated with deep learning to realize, in his view, AGI in as few as 3-7 years.
• Why the development of AGI would near-instantly trigger the development of ASI — a machine with intellectual capabilities far beyond humans’.
• Why, despite triggering the singularity — beyond which we cannot make confident predictions about the future — he’s optimistic that AGI will be a positive development for humankind.
• The connections between self-awareness, consciousness and the ASI of the future.
• With admittedly wide error bars, what a society that includes ASI may look like.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.