#108 - Dr. JOEL LEHMAN - Machine Love [Staff Favourite]

#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

Tämä jakso on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi jakso saattaa sisältää mainontaa.

Jaksot(260)

Stealing Reasoning Traces from Proprietary LLM APIs — Ilia Shumailov & Alexander Panfilov

Stealing Reasoning Traces from Proprietary LLM APIs — Ilia Shumailov & Alexander Panfilov

Tim Scarfe speaks with Ilia Shumailov and Alexander Panfilov about their paper, Stealing Reasoning Traces from Proprietary LLM APIs.The core bug sounds deceptively simple: providers return encrypted r...

22 Elo 49min

Every Exponential Ends — Silicon Valley Forgot — Adam Becker

Every Exponential Ends — Silicon Valley Forgot — Adam Becker

Astrophysicist Adam Becker, author of "What Is Real?", joins Tim Scarfe to take apart the futures Silicon Valley keeps selling: the 2045 singularity, mind uploading, Mars colonies, and the AI apocalyp...

20 Elo 1h 18min

AI Is Learning at the Wrong Level of Abstraction — Matthieu Wyart

AI Is Learning at the Wrong Level of Abstraction — Matthieu Wyart

This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at https://notion.com/mlstWhy can deep networks discover abstractions that shallow models miss? Statistical phys...

10 Elo 1h 18min

How Researchers Test AI for Hidden Goals — Apollo Research

How Researchers Test AI for Hidden Goals — Apollo Research

Can an AI do the right thing for the wrong reason? Tim Scarfe speaks with Apollo Research’s Alexander Meinke, Axel Højmark and Jérémy Scheurer about Measuring Reward-Seeking via Contrastive Belief Upd...

31 Heinä 1h 18min

Why a Nation Can't Outsource Its Frontier AI - Alistair Pullen (Cosine AI)

Why a Nation Can't Outsource Its Frontier AI - Alistair Pullen (Cosine AI)

This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at https://notion.com/mlstBritain's most capable coding model can't be exported, and that ban is the whole reaso...

13 Heinä 55min

 The Benchmark With No Instructions — ARC-AGI-3 (winning team!)

The Benchmark With No Instructions — ARC-AGI-3 (winning team!)

Tim Scarfe travels to Zurich to sit down with the Tufa Labs ARC-AGI-3 team — founder Benjamin Crouzier, with Jeroen Cottaar, Dries Smit, Stefano Viel and Michal Tesnar — to work out what their leaderb...

1 Heinä 1h 24min

The Thermodynamic AI Computing Chip - Thomas Ahle

The Thermodynamic AI Computing Chip - Thomas Ahle

Thomas Ahle wants Normal Computing to be the Lovable for chip design: type your intent, and a swarm of agents carries it from design through optimisation, formalisation and verification to tape-out. T...

28 Kesä 1h 2min

He won a Nobel here for AlphaFold. Then he left. - John Jumper

He won a Nobel here for AlphaFold. Then he left. - John Jumper

This episode is sponsored by Notion. Learn more about Notion's Developer Platform today at https://notion.com/mlstProtein folding stalled biology for fifty years. A sequence of amino acids dictates a ...

22 Kesä 53min