Machine Learning Street Talk (MLST)

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Machine Learning Street Talk (MLST) episodes

April 02, 2023 #112 AVOIDING AGI APOCALYPSE - CONNOR LEAHY
Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5
In this podcast with the legendary Connor Leahy (CEO Conjecture) recorded in Dec 2022, we discuss various topics related to artificial intelligence (AI), including AI alignment, the success of ChatGPT, the potential threats of artificial general intelligence (AGI), and the challenges of balancing research and product development at his company, Conjecture. He emphasizes the importance of empathy, dehumanizing our thinking to avoid anthropomorphic biases, and the value of real-world experiences in learning and personal growth. The conversation also covers the Orthogonality Thesis, AI preferences, the mystery of mode collapse, and the paradox of AI alignment.
Connor Leahy expresses concern about the rapid development of AI and the potential dangers it poses, especially as AI systems become more powerful and integrated into society. He argues that we need a better understanding of AI systems to ensure their safe and beneficial development. The discussion also touches on the concept of "futuristic whack-a-mole," where futurists predict potential AGI threats, and others try to come up with solutions for those specific scenarios. However, the problem lies in the fact that there could be many more scenarios that neither party can think of, especially when dealing with a system that's smarter than humans.
https://www.linkedin.com/in/connor-j-leahy/https://twitter.com/NPCollapse
Interviewer: Dr. Tim Scarfe (Innovation CTO @ XRAI Glass https://xrai.glass/)
TOC:
The success of ChatGPT and its impact on the AI field [00:00:00]
Subjective experience [00:15:12]
AI Architectural discussion including RLHF [00:18:04]
The paradox of AI alignment and the future of AI in society [00:31:44]
The impact of AI on society and politics [00:36:11]
Future shock levels and the challenges of predicting the future [00:45:58]
Long termism and existential risk [00:48:23]
Consequentialism vs. deontology in rationalism [00:53:39]
The Rationalist Community and its Challenges [01:07:37]
AI Alignment and Conjecture [01:14:15]
Orthogonality Thesis and AI Preferences [01:17:01]
Challenges in AI Alignment [01:20:28]
Mechanistic Interpretability in Neural Networks [01:24:54]
Building Cleaner Neural Networks [01:31:36]
Cognitive horizons / The problem with rapid AI development [01:34:52]
Founding Conjecture and raising funds [01:39:36]
Inefficiencies in the market and seizing opportunities [01:45:38]
Charisma, authenticity, and leadership in startups [01:52:13]
Autistic culture and empathy [01:55:26]
Learning from real-world experiences [02:01:57]
Technical empathy and transhumanism [02:07:18]
Moral status and the limits of empathy [02:15:33]
Anthropomorphic Thinking and Consequentialism [02:17:42]
Conjecture: Balancing Research and Product Development [02:20:37]
Epistemology Team at Conjecture [02:31:07]
Interpretability and Deception in AGI [02:36:23]
Futuristic whack-a-mole and predicting AGI threats [02:38:27]
Refs:
1. OpenAI's ChatGPT: https://chat.openai.com/
2. The Mystery of Mode Collapse (Article): https://www.lesswrong.com/posts/t9svvNPNmFf5Qa3TA/mysteries-of-mode-collapse
3. The Rationalist Guide to the Galaxy https://www.amazon.co.uk/Does-Not-Hate-You-Superintelligence/dp/1474608795
5. Alfred Korzybski: https://en.wikipedia.org/wiki/Alfred_Korzybski
6. Instrumental Convergence: https://en.wikipedia.org/wiki/Instrumental_convergence
7. Orthogonality Thesis: https://en.wikipedia.org/wiki/Orthogonality_thesis
8. Brian Tomasik's Essays on Reducing Suffering: https://reducing-suffering.org/
9. Epistemological Framing for AI Alignment Research: https://www.lesswrong.com/posts/Y4YHTBziAscS5WPN7/epistemological-framing-for-ai-alignment-research
10. How to Defeat Mind readers: https://www.alignmentforum.org/posts/EhAbh2pQoAXkm9yor/circumventing-interpretability-how-to-defeat-mind-readers
11. Society of mind: https://www.amazon.co.uk/Society-Mind-Marvin-Minsky/dp/0671607405
2 hr 41 min
April 01, 2023 #111 - AI moratorium, Eliezer Yudkowsky, AGI risk etc
Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5
Send us a voice message which you want us to publish: https://podcasters.spotify.com/pod/show/machinelearningstreettalk/message
In a recent open letter, over 1500 individuals called for a six-month pause on the development of advanced AI systems, expressing concerns over the potential risks AI poses to society and humanity. However, there are issues with this approach, including global competition, unstoppable progress, potential benefits, and the need to manage risks instead of avoiding them.
Decision theorist Eliezer Yudkowsky took it a step further in a Time magazine article, calling for an indefinite and worldwide moratorium on Artificial General Intelligence (AGI) development, warning of potential catastrophe if AGI exceeds human intelligence. Yudkowsky urged for an immediate halt to all large AI training runs and the shutdown of major GPU clusters, calling for international cooperation to enforce these measures.
However, several counterarguments question the validity of Yudkowsky's concerns:
1. Hard limits on AGI
2. Dismissing AI extinction risk
3. Collective action problem
4. Misplaced focus on AI threats
While the potential risks of AGI cannot be ignored, it is essential to consider various arguments and potential solutions before making drastic decisions. As AI continues to advance, it is crucial for researchers, policymakers, and society as a whole to engage in open and honest discussions about the potential consequences and the best path forward. With a balanced approach to AGI development, we may be able to harness its power for the betterment of humanity while mitigating its risks.
Eliezer Yudkowsky: https://en.wikipedia.org/wiki/Eliezer_Yudkowsky
Connor Leahy: https://twitter.com/NPCollapse (we will release that interview soon)
Gary Marcus: http://garymarcus.com/index.html
Tim Scarfe is the innovation CTO of XRAI Glass: https://xrai.glass/
Gary clip filmed at AIUK https://ai-uk.turing.ac.uk/programme/ and our appreciation to them for giving us a press pass. Check out their conference next year!
WIRED clip from Gary came from here: https://www.youtube.com/watch?v=Puo3VkPkNZ4
Refs:

Statement from the listed authors of Stochastic Parrots on the “AI pause” letterTimnit Gebru, Emily M. Bender, Angelina McMillan-Major, Margaret Mitchell
https://www.dair-institute.org/blog/letter-statement-March2023
Eliezer Yudkowsky on Lex: https://www.youtube.com/watch?v=AaTRHFaaPG8
Pause Giant AI Experiments: An Open Letter
https://futureoflife.org/open-letter/pause-giant-ai-experiments/
Pausing AI Developments Isn't Enough. We Need to Shut it All Down (Eliezer Yudkowsky)
https://time.com/6266923/ai-eliezer-yudkowsky-open-letter-not-enough/
27 min
March 23, 2023 #110 Dr. STEPHEN WOLFRAM - HUGE ChatGPT+Wolfram announcement!
HUGE ANNOUNCEMENT, CHATGPT+WOLFRAM! You saw it HERE first!
YT version: https://youtu.be/z5WZhCBRDpU
Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5
Stephen's announcement post: https://writings.stephenwolfram.com/2023/03/chatgpt-gets-its-wolfram-superpowers/
OpenAI's announcement post: https://openai.com/blog/chatgpt-plugins
In an era of technology and innovation, few individuals have left as indelible a mark on the fabric of modern science as our esteemed guest, Dr. Steven Wolfram.
Dr. Wolfram is a renowned polymath who has made significant contributions to the fields of physics, computer science, and mathematics. A prodigious young man too, Wolfram earned a Ph.D. in theoretical physics from the California Institute of Technology by the age of 20. He became the youngest recipient of the prestigious MacArthur Fellowship at the age of 21.
Wolfram's groundbreaking computational tool, Mathematica, was launched in 1988 and has become a cornerstone for researchers and innovators worldwide. In 2002, he published "A New Kind of Science," a paradigm-shifting work that explores the foundations of science through the lens of computational systems.
In 2009, Wolfram created Wolfram Alpha, a computational knowledge engine utilized by millions of users worldwide. His current focus is on the Wolfram Language, a powerful programming language designed to democratize access to cutting-edge technology.
Wolfram's numerous accolades include honorary doctorates and fellowships from prestigious institutions. As an influential thinker, Dr. Wolfram has dedicated his life to unraveling the mysteries of the universe and making computation accessible to all.
First of all... we have an announcement to make, you heard it FIRST here on MLST! ....
Intro [00:00:00]
Big announcement! Wolfram + ChatGPT! [00:02:57]
What does it mean to understand? [00:05:33]
Feeding information back into the model [00:13:48]
Semantics and cognitive categories [00:20:09]
Navigating the ruliad [00:23:50]
Computational irreducibility [00:31:39]
Conceivability and interestingness [00:38:43]
Human intelligible sciences [00:43:43]
58 min
March 20, 2023 #109 - Dr. DAN MCQUILLAN - Resisting AI
YT version: https://youtu.be/P1j3VoKBxbc (references in pinned comment)
Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5
Dan McQuillan, a visionary in digital culture and social innovation, emphasizes the importance of understanding technology's complex relationship with society. As an academic at Goldsmiths, University of London, he fosters interdisciplinary collaboration and champions data-driven equity and ethical technology. Dan's career includes roles at Amnesty International and Social Innovation Camp, showcasing technology's potential to empower and bring about positive change. In this conversation, we discuss the challenges and opportunities at the intersection of technology and society, exploring the profound impact of our digital world.
Interviewer: Dr. Tim Scarfe

[00:00:00] Dan's background and journey to academia
[00:03:30] Dan's background and journey to academia
[00:04:10] Writing the book "Resisting AI"
[00:08:30] Necropolitics and its relation to AI
[00:10:06] AI as a new form of colonization
[00:12:57] LLMs as a new form of neo-techno-imperialism
[00:15:47] Technology for good and AGI's skewed worldview
[00:17:49] Transhumanism, eugenics, and intelligence
[00:20:45] Valuing differences (disability) and challenging societal norms
[00:26:08] Re-ontologizing and the philosophy of information
[00:28:19] New materialism and the impact of technology on society
[00:30:32] Intelligence, meaning, and materiality
[00:31:43] The constraints of physical laws and the importance of science
[00:32:44] Exploring possibilities to reduce suffering and increase well-being
[00:33:29] The division between meaning and material in our experiences
[00:35:36] Machine learning, data science, and neoplatonic approach to understanding reality
[00:37:56] Different understandings of cognition, thought, and consciousness
[00:39:15] Enactivism and its variants in cognitive science
[00:40:58] Jordan Peterson
[00:44:47] Relationism, relativism, and finding the correct relational framework
[00:47:42] Recognizing privilege and its impact on social interactions
[00:49:10] Intersectionality / Feminist thinking and the concept of care in social structures
[00:51:46] Intersectionality and its role in understanding social inequalities
[00:54:26] The entanglement of history, technology, and politics
[00:57:39] ChatGPT article - we come to bury ChatGPT
[00:59:41] Statistical pattern learning and convincing patterns in AI
[01:01:27] Anthropomorphization and understanding in AI
[01:03:26] AI in education and critical thinking
[01:06:09] European Union policies and trustable AI
[01:07:52] AI reliability and the halo effect
[01:09:26] AI as a tool enmeshed in society
[01:13:49] Luddites
[01:15:16] AI is a scam
[01:15:31] AI and Social Relations
[01:16:49] Invisible Labor in AI and Machine Learning
[01:21:09] Exploititative AI / alignment
[01:23:50] Science fiction AI / moral frameworks
[01:27:22] Discussing Stochastic Parrots and Nihilism
[01:30:36] Human Intelligence vs. Language Models
[01:32:22] Image Recognition and Emulation vs. Experience
[01:34:32] Thought Experiments and Philosophy in AI Ethics (mimicry)
[01:41:23] Abstraction, reduction, and grounding in reality
[01:43:13] Process philosophy and the possibility of change
[01:49:55] Mental health, AI, and epistemic injustice
[01:50:30] Hermeneutic injustice and gendered techniques
[01:53:57] AI and politics
[01:59:24] Epistemic injustice and testimonial injustice
[02:11:46] Fascism and AI discussion
[02:13:24] Violence in various systems
[02:16:52] Recognizing systemic violence
[02:22:35] Fascism in Today's Society
[02:33:33] Pace and Scale of Technological Change
[02:37:38] Alternative approaches to AI and society
[02:44:09] Self-Organization at Successive Scales / cybernetics
2 hr 52 min
March 16, 2023 #108 - Dr. JOEL LEHMAN - Machine Love [Staff Favourite]
Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5

We are honoured to welcome Dr. Joel Lehman, an eminent machine learning research scientist, whose work in AI safety, reinforcement learning, creative open-ended search algorithms, and indeed the philosophy of open-endedness and abandoning objectives has paved the way for innovative ideas that challenge our preconceptions and inspire new visions for the future.
Dr. Lehman's thought-provoking book, "Why Greatness Cannot Be Planned" penned with with our MLST favourite Professor Kenneth Stanley has left an indelible mark on the field and profoundly impacted the way we view innovation and the serendipitous nature of discovery. Those of you who haven't watched our special edition show on that, should do so at your earliest convenience! Building upon this foundation, Dr. Lehman has ventured into the domain of AI systems that embody principles of love, care, responsibility, respect, and knowledge, drawing from the works of Maslow, Erich Fromm, and positive psychology.

YT version: https://youtu.be/23-TXgJEv-Q

http://joellehman.com/
https://twitter.com/joelbot3000

Interviewer: Dr. Tim Scarfe

TOC:
Intro [00:00:00]
Model [00:04:26]
Intro and Paper Intro [00:08:52]
Subjectivity [00:16:07]
Reflections on Greatness Book [00:19:30]
Representing Subjectivity [00:29:24]
Nagal's Bat [00:31:49]
Abstraction [00:38:58]
Love as Action Rather Than Feeling [00:42:58]
Reontologisation [00:57:38]
Self Help [01:04:15]
Meditation [01:09:02]
The Human Reward Function / Effective... [01:16:52]
Machine Hate [01:28:32]
Societal Harms [01:31:41]
Lenses We Use Obscuring Reality [01:56:36]
Meta Optimisation and Evolution [02:03:14]
Conclusion [02:07:06]

References:

What Is It Like to Be a Bat? (Thomas Nagel)
https://warwick.ac.uk/fac/cross_fac/iatl/study/ugmodules/humananimalstudies/lectures/32/nagel_bat.pdf

Why Greatness Cannot Be Planned: The Myth of the Objective (Kenneth O. Stanley and Joel Lehman)
https://link.springer.com/book/10.1007/978-3-319-15524-1

Machine Love (Joel Lehman)
https://arxiv.org/abs/2302.09248

How effective altruists ignored risk (Carla Cremer)
https://www.vox.com/future-perfect/23569519/effective-altrusim-sam-bankman-fried-will-macaskill-ea-risk-decentralization-philanthropy

Philosophy tube - The Rich Have Their Own Ethics: Effective Altruism
https://www.youtube.com/watch?v=Lm0vHQYKI-Y

Abandoning Objectives: Evolution through the Search for Novelty Alone (Joel Lehman and Kenneth O. Stanley)
https://www.cs.swarthmore.edu/~meeden/DevelopmentalRobotics/lehman_ecj11.pdf
2 hr 10 min
March 13, 2023 #107 - Dr. RAPHAËL MILLIÈRE - Linguistics, Theory of Mind, Grounding
Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5
Dr. Raphaël Millière is the 2020 Robert A. Burt Presidential Scholar in Society and Neuroscience in the Center for Science and Society, and a Lecturer in the Philosophy Department at Columbia University. His research draws from his expertise in philosophy and cognitive science to explore the implications of recent progress in deep learning for models of human cognition, as well as various issues in ethics and aesthetics. He is also investigating what underlies the capacity to represent oneself as oneself at a fundamental level, in humans and non-human animals; as well as the role that self-representation plays in perception, action, and memory. In a world where technology is rapidly advancing, Dr. Millière is striving to gain a better understanding of how artificial neural networks work, and to establish fair and meaningful comparisons between humans and machines in various domains in order to shed light on the implications of artificial intelligence for our lives.
https://www.raphaelmilliere.com/
https://twitter.com/raphaelmilliere

Here is a version with hesitation sounds like "um" removed if you prefer (I didn't notice them personally): https://share.descript.com/view/aGelyTl2xpN
YT: https://www.youtube.com/watch?v=fhn6ZtD6XeE

TOC:
Intro to Raphael [00:00:00]
Intro: Moving Beyond Mimicry in Artificial Intelligence (Raphael Millière) [00:01:18]
Show Kick off [00:07:10]
LLMs [00:08:37]
Semantic Competence/Understanding [00:18:28]
Forming Analogies/JPG Compression Article [00:30:17]
Compositional Generalisation [00:37:28]
Systematicity [00:47:08]
Language of Thought [00:51:28]
Bigbench (Conceptual Combinations) [00:57:37]
Symbol Grounding [01:11:13]
World Models [01:26:43]
Theory of Mind [01:30:57]

Refs (this is truncated, full list on YT video description):

Moving Beyond Mimicry in Artificial Intelligence (Raphael Millière)
https://nautil.us/moving-beyond-mimicry-in-artificial-intelligence-238504/

On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 (Bender et al)
https://dl.acm.org/doi/10.1145/3442188.3445922

ChatGPT Is a Blurry JPEG of the Web (Ted Chiang)
https://www.newyorker.com/tech/annals-of-technology/chatgpt-is-a-blurry-jpeg-of-the-web

The Debate Over Understanding in AI's Large Language Models (Melanie Mitchell)
https://arxiv.org/abs/2210.13966

Talking About Large Language Models (Murray Shanahan)
https://arxiv.org/abs/2212.03551

Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data (Bender)
https://aclanthology.org/2020.acl-main.463/

The symbol grounding problem (Stevan Harnad)
https://arxiv.org/html/cs/9906002

Why the Abstraction and Reasoning Corpus is interesting and important for AI (Mitchell)
https://aiguide.substack.com/p/why-the-abstraction-and-reasoning

Linguistic relativity (Sapir–Whorf hypothesis)
https://en.wikipedia.org/wiki/Linguistic_relativity

Cooperative principle (Grice's four maxims of conversation - quantity, quality, relation, and manner)
https://en.wikipedia.org/wiki/Cooperative_principle
1 hr 44 min
March 11, 2023 #106 - Prof. KARL FRISTON 3.0 - Collective Intelligence [Special Edition]
This show is sponsored by Numerai, please visit them here with our sponsor link (we would really appreciate it) http://numer.ai/mlst
Prof. Karl Friston recently proposed a vision of artificial intelligence that goes beyond machines and algorithms, and embraces humans and nature as part of a cyber-physical ecosystem of intelligence. This vision is based on the principle of active inference, which states that intelligent systems can learn from their observations and act on their environment to reduce uncertainty and achieve their goals. This leads to a formal account of collective intelligence that rests on shared narratives and goals.
To realize this vision, Friston suggests developing a shared hyper-spatial modelling language and transaction protocol, as well as novel methods for measuring and optimizing collective intelligence. This could harness the power of artificial intelligence for the common good, without compromising human dignity or autonomy. It also challenges us to rethink our relationship with technology, nature, and each other, and invites us to join a global community of sense-makers who are curious about the world and eager to improve it.

YT version: https://www.youtube.com/watch?v=V_VXOdf1NMw
Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5

TOC:
Intro [00:00:00]
Numerai (Sponsor segment) [00:07:10]
Designing Ecosystems of Intelligence from First Principles (Friston et al) [00:09:48]
Information / Infosphere and human agency [00:18:30]
Intelligence [00:31:38]
Reductionism [00:39:36]
Universalism [00:44:46]
Emergence [00:54:23]
Markov blankets [01:02:11]
Whole part relationships / structure learning [01:22:33]
Enactivism [01:29:23]
Knowledge and Language [01:43:53]
ChatGPT [01:50:56]
Ethics (is-ought) [02:07:55]
Can people be evil? [02:35:06]
Ethics in Al, subjectiveness [02:39:05]
Final thoughts [02:57:00]

References:
Designing Ecosystems of Intelligence from First Principles (Friston et al)
https://arxiv.org/abs/2212.01354

GLOM - How to represent part-whole hierarchies in a neural network (Hinton)
https://arxiv.org/pdf/2102.12627.pdf

Seven Brief Lessons on Physics (Carlo Rovelli)
https://www.amazon.co.uk/Seven-Brief-Lessons-Physics-Rovelli/dp/0141981725

How Emotions Are Made: The Secret Life of the Brain (Lisa Feldman Barrett)
https://www.amazon.co.uk/How-Emotions-Are-Made-Secret/dp/B01N3D4OON

Am I Self-Conscious? (Or Does Self-Organization Entail Self-Consciousness?) (Karl Friston)
https://www.frontiersin.org/articles/10.3389/fpsyg.2018.00579/full

Integrated information theory (Giulio Tononi)
https://en.wikipedia.org/wiki/Integrated_information_theory
3 hr
March 04, 2023 #105 - Dr. MICHAEL OLIVER [CSO - Numerai]
Access Numerai here: http://numer.ai/mlst

Michael Oliver is the Chief Scientist at Numerai, a hedge fund that crowdsources machine learning models from data scientists. He has a PhD in Computational Neuroscience from UC Berkeley and was a postdoctoral researcher at the Allen Institute for Brain Science before joining Numerai in 2020. He is also the host of Numerai Quant Club, a YouTube series where he discusses Numerai’s research, data and challenges.

YT version: https://youtu.be/61s8lLU7sFg

TOC:
[00:00:00] Introduction to Michael and Numerai
[00:02:03] Understanding / new Bing
[00:22:47] Quant vs Neuroscience
[00:36:43] Role of language in cognition and planning, and subjective...
[00:45:47] Boundaries in finance modelling
[00:48:00] Numerai
[00:57:37] Aggregation systems
[01:00:52] Getting started on Numeral
[01:03:21] What models are people using
[01:04:23] Numerai Problem Setup
[01:05:49] Regimes in financial data and quant talk
[01:11:18] Esoteric approaches used on Numeral?
[01:13:59] Curse of dimensionality
[01:16:32] Metrics
[01:19:10] Outro

References:

Growing Neural Cellular Automata (Alexander Mordvintsev)
https://distill.pub/2020/growing-ca/

A Thousand Brains: A New Theory of Intelligence (Jeff Hawkins)
https://www.amazon.fr/Thousand-Brains-New-Theory-Intelligence/dp/1541675819

Perceptual Neuroscience: The Cerebral Cortex (Vernon B. Mountcastle)
https://www.amazon.ca/Perceptual-Neuroscience-Cerebral-Vernon-Mountcastle/dp/0674661885

Numerai Quant Club with Michael Oliver
https://www.youtube.com/watch?v=eLIxarbDXuQ&list=PLz3D6SeXhT3tTu8rhZmjwDZpkKi-UPO1F

Numerai YT channel
https://www.youtube.com/@Numerai/featured

Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5
1 hr 21 min
February 22, 2023 #104 - Prof. CHRIS SUMMERFIELD - Natural General Intelligence [SPECIAL EDITION]
Support us! https://www.patreon.com/mlst
MLST Discord: https://discord.gg/aNPkGUQtc5

Christopher Summerfield, Department of Experimental Psychology, University of Oxford is a Professor of Cognitive Neuroscience at the University of Oxford and a Research Scientist at Deepmind UK. His work focusses on the neural and computational mechanisms by which humans make decisions.
Chris has just released an incredible new book on AI called "Natural General Intelligence". It's my favourite book on AI I have read so so far.
The book explores the algorithms and architectures that are driving progress in AI research, and discusses intelligence in the language of psychology and biology, using examples and analogies to be comprehensible to a wide audience. It also tackles longstanding theoretical questions about the nature of thought and knowledge.
With Chris' permission, I read out a summarised version of Chapter 2 from his book on which was on Intelligence during the 30 minute MLST introduction.
Buy his book here:
https://global.oup.com/academic/product/natural-general-intelligence-9780192843883?cc=gb&lang=en&

YT version: https://youtu.be/31VRbxAl3t0
Interviewer: Dr. Tim Scarfe

TOC:
[00:00:00] Walk and talk with Chris on Knowledge and Abstractions
[00:04:08] Intro to Chris and his book
[00:05:55] (Intro) Tim reads Chapter 2: Intelligence
[00:09:28] Intro continued: Goodhart's law
[00:15:37] Intro continued: The "swiss cheese" situation
[00:20:23] Intro continued: On Human Knowledge
[00:23:37] Intro continued: Neats and Scruffies
[00:30:22] Interview kick off
[00:31:59] What does it mean to understand?
[00:36:18] Aligning our language models
[00:40:17] Creativity
[00:41:40] "Meta" AI and basins of attraction
[00:51:23] What can Neuroscience impart to AI
[00:54:43] Sutton, neats and scruffies and human alignment
[01:02:05] Reward is enough
[01:19:46] Jon Von Neumann and Intelligence
[01:23:56] Compositionality

References:

The Language Game (Morten H. Christiansen, Nick Chater
https://www.penguin.co.uk/books/441689/the-language-game-by-morten-h-christiansen-and--nick-chater/9781787633483
Theory of general factor (Spearman)
https://www.proquest.com/openview/7c2c7dd23910c89e1fc401e8bb37c3d0/1?pq-origsite=gscholar&cbl=1818401
Intelligence Reframed (Howard Gardner)
https://books.google.co.uk/books?hl=en&lr=&id=Qkw4DgAAQBAJ&oi=fnd&pg=PT6&dq=howard+gardner+multiple+intelligences&ots=ERUU0u5Usq&sig=XqiDgNUIkb3K9XBq0vNbFmXWKFs#v=onepage&q=howard%20gardner%20multiple%20intelligences&f=false
The master algorithm (Pedro Domingos)
https://www.amazon.co.uk/Master-Algorithm-Ultimate-Learning-Machine/dp/0241004543
A Thousand Brains: A New Theory of Intelligence (Jeff Hawkins)
https://www.amazon.co.uk/Thousand-Brains-New-Theory-Intelligence/dp/1541675819
The bitter lesson (Rich Sutton)
http://www.incompleteideas.net/IncIdeas/BitterLesson.html
1 hr 29 min
February 11, 2023 #103 - Prof. Edward Grefenstette - Language, Semantics, Philosophy
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YT: https://youtu.be/i9VPPmQn9HQ

Edward Grefenstette is a Franco-American computer scientist who currently serves as Head of Machine Learning at Cohere and Honorary Professor at UCL. He has previously been a research scientist at Facebook AI Research and staff research scientist at DeepMind, and was also the CTO of Dark Blue Labs. Prior to his move to industry, Edward was a Fulford Junior Research Fellow at Somerville College, University of Oxford, and was lecturing at Hertford College. He obtained his BSc in Physics and Philosophy from the University of Sheffield and did graduate work in the philosophy departments at the University of St Andrews. His research draws on topics and methods from Machine Learning, Computational Linguistics and Quantum Information Theory, and has done work implementing and evaluating compositional vector-based models of natural language semantics and empirical semantic knowledge discovery.

https://www.egrefen.com/
https://cohere.ai/

TOC:
[00:00:00] Introduction
[00:02:52] Differential Semantics
[00:06:56] Concepts
[00:10:20] Ontology
[00:14:02] Pragmatics
[00:16:55] Code helps with language
[00:19:02] Montague
[00:22:13] RLHF
[00:31:54] Swiss cheese problem / retrieval augmented
[00:37:06] Intelligence / Agency
[00:43:33] Creativity
[00:46:41] Common sense
[00:53:46] Thinking vs knowing

References:

Large language models are not zero-shot communicators (Laura Ruis)
https://arxiv.org/abs/2210.14986

Some remarks on Large Language Models (Yoav Goldberg)
https://gist.github.com/yoavg/59d174608e92e845c8994ac2e234c8a9

Quantum Natural Language Processing (Bob Coecke)
https://www.cs.ox.ac.uk/people/bob.coecke/QNLP-ACT.pdf

Constitutional AI: Harmlessness from AI Feedback
https://www.anthropic.com/constitutional.pdf

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks (Patrick Lewis)
https://www.patricklewis.io/publication/rag/

Natural General Intelligence (Prof. Christopher Summerfield)
https://global.oup.com/academic/product/natural-general-intelligence-9780192843883

ChatGPT with Rob Miles - Computerphile
https://www.youtube.com/watch?v=viJt_DXTfwA
1 hr 2 min

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