#72 Prof. KEN STANLEY 2.0 - On Art and Subjectivity [UNPLUGGED]

#72 Prof. KEN STANLEY 2.0 - On Art and Subjectivity [UNPLUGGED]

YT version: https://youtu.be/DxBZORM9F-8

Patreon: https://www.patreon.com/mlst

Discord: https://discord.gg/ESrGqhf5CB


Prof. Ken Stanley argued in his book that our world has become saturated with objectives. The process of setting an objective, attempting to achieve it, and measuring progress along the way has become the primary route to achievement in our culture. He’s not saying that objectives are bad per se, especially if they’re modest, but he thinks that when goals are ambitious then the search space becomes deceptive.


Is the key to artificial intelligence really related to intelligence? Does taking a job with a higher salary really bring you closer to being a millionaire? The problem is that the stepping stones which lead to ambitious objectives tend to be pretty strange, they don't resemble the final end state at all. Vaccum tubes led to computers for example and Youtube started as a dating website.


What fascinated us about this conversation with Ken is that we got a much deeper understanding of his philosophy. He lead by saying that he thought it's worth questioning whether artificial intelligence is even a science or not. Ken thinks that the secret to future progress is for us to embrace more subjectivity.


[00:00:00] Tim Intro

[00:12:54] Intro

[00:17:08] Seeing ideas everywhere - AI and art are highly connected

[00:28:40] Creativity in Mathematics

[00:30:14] Where is the intelligence in art?

[00:38:49] Is AI disappointingly simple to mechanise?

[00:42:48] Slightly conscious

[00:46:27] Do we have subjective experience?

[00:50:23] Fear of the unknown

[00:51:48] Free Will

[00:54:22] Chalmers

[00:55:08] What's happening now in open-endedness

[00:58:31] Generalisation

[01:06:34] Representation primitives and what it means to understand

[01:12:37] Appeal to definitions, knowledge itself blocks discovery


Make sure you buy Kenneth's book!


Why Greatness Cannot Be Planned: The Myth of the Objective [Stanley, Lehman]

https://www.amazon.co.uk/Why-Greatness-Cannot-Planned-Objective/dp/3319155237


Abandoning Objectives: Evolution through the

Search for Novelty Alone [Lehman, Stanley]

https://www.cs.swarthmore.edu/~meeden/DevelopmentalRobotics/lehman_ecj11.pdf


Twitter

https://twitter.com/kenneth0stanley

Denne episoden er hentet fra en åpen RSS-feed og er ikke publisert av Podme. Den kan derfor inneholde annonser.

Episoder(271)

What Most People Get Wrong About Evolution | Akarsh Kumar

What Most People Get Wrong About Evolution | Akarsh Kumar

A lot of people in AI treat evolution as a dumb fallback, basically random search for when you can't take a gradient. Akarsh Kumar thinks that is wrong. Selection hangs on to partial solutions, so mut...

10 Okt 47min

How a Voice Agent Learns the Rhythm of Conversation — Shawn Wen

How a Voice Agent Learns the Rhythm of Conversation — Shawn Wen

Tsung-Hsien (Shawn) Wen, CTO of PolyAI, tells Tim Scarfe why voice agents are harder than text agents. Voice adds time, and a good conversation depends on adapting to the person on the line, not just ...

1 Okt 1h 10min

Who Checks a Proof No Human Can Read? — Leo de Moura

Who Checks a Proof No Human Can Read? — Leo de Moura

Leonardo de Moura created Lean and co-created Z3. ---This episode is sponsored by Parallel.Parallel, where agents find answers: web search, extraction and deep research APIs built for AI agents.Start ...

30 Sep 1h 14min

When AI Research Starts Moving Faster Than Human Research - Zhengyao Jiang

When AI Research Starts Moving Faster Than Human Research - Zhengyao Jiang

Weco let an AI coding agent rewrite the harness around another agent for eight days: its code, prompts and tools, while the underlying language model stayed fixed. Tim Scarfe asks Weco co-founder Zhen...

26 Sep 43min

How Deep Learning Finally Cracked Messy Tables - Frank Hutter

How Deep Learning Finally Cracked Messy Tables - Frank Hutter

Frank Hutter, co-founder of Prior Labs, talks about TabPFN, a tabular foundation model that makes predictions in a single forward pass, and the research behind it.TabPFN is pre-trained on synthetic da...

23 Sep 1h 53min

Why Scaling Prediction Cannot Create Intelligence - Alexander Mattick

Why Scaling Prediction Cannot Create Intelligence - Alexander Mattick

Alexander Mattick is a researcher at Fraunhofer IIS and a PhD researcher at the University of Technology Nuremberg (UTN), and a regular on Yannic Kilcher's Discord. He first came on MLST in 2022, afte...

21 Sep 2h 14min

How Physical AI Learns Across Language, Video and Action — Ming-Yu Liu

How Physical AI Learns Across Language, Video and Action — Ming-Yu Liu

The car making a left turn at the start of this episode was never filmed. Cosmos 3 generated it. Ming-Yu Liu, who leads the Cosmos research at NVIDIA, explains how one model can describe a video, gene...

15 Sep 25min

Speech Recognition Is Not a Solved Problem — Pavan Kumar Reddy

Speech Recognition Is Not a Solved Problem — Pavan Kumar Reddy

Pavan Kumar Reddy leads audio research at Mistral AI. He joins Tim Scarfe for a deep technical tour of Voxtral — and explains why the frontier of deployed voice is still a cascade of specialised model...

14 Sep 1h 42min

Populært innen Teknologi

energi-og-klima
teknisk-sett
lydartikler-fra-aftenposten
elektropodden
nasjonal-sikkerhetsmyndighet-nsm
tomprat-med-gunnar-tjomlid
rss-ai-forklart
rss-alt-som-gar-pa-strom
rss-kunstig-intelligens-med-elisabeth-maren-og-morten
shifter
smart-forklart
fornybaren
rss-alt-vi-kan
rss-bak-skyen
pedagogisk-intelligens
rss-romnasjonen
rss-teknologioptimistene-en-podkast-om-teknologi-og-mennesker
rss-heis
rss-larervarelset
rss-hvorfor-ble-det-sann