Skip to content
0:00 / 0:00

#kennethstanley#noveltysearch#neat

Why Greatness Cannot Be Planned — Kenneth Stanley

Machine Learning Street Talk

221K subscribers • 1 video on Hallway

YouTube
  • Recommended by 4 people: 4 on Hacker News.
  • A classic. People kept recommending it from 2021 to 2024.
  • Presented by Kenneth Stanley, AI researcher and co-author of Why Greatness Cannot Be Planned
  • An opinion. It argues one side of a question engineers disagree on.

Intermediate. Assumes working knowledge.

154K views5 years ago4 recommendations

AI and machine learningComputer scienceReinforcement learningNeural networks and deep learningComputation and complexity

Kenneth Stanley discusses open-endedness, novelty search, and why objective-driven optimization can hinder breakthrough discoveries in AI and life.

Professor Kenneth Stanley is currently a research science manager at OpenAI in San Fransisco. We've Been dreaming about getting Kenneth on the show since the very begininning of Machine Learning Street Talk. Some of you might recall that our first ever show was on the enhanced POET paper, of course Kenneth had his hands all over it. He's been cited over 16000 times, his most popular paper with over 3K citations was the NEAT algorithm. His interests are neuroevolution, open-endedness, NNs, artificial life, and AI. He invented the concept of novelty search with no clearly defined objective. His key idea is that there is a tyranny of objectives prevailing in every aspect of our lives, society and indeed our algorithms. Crucially, these objectives produce convergent behaviour and thinking and distract us from discovering stepping stones which will lead to greatness. He thinks that this monotonic objective obsession, this idea that we need to continue to improve benchmarks every year is dangerous. He wrote about this in detail in his recent book "greatness can not be planned" which will be the main topic of discussion in the show. We also cover his ideas on open endedness in machine learning. Intro to Kenneth Show structure disclaimer Passionate discussion Why greatness cant be planned and the tyranny of objectives Chinese Finger Trap Perverse Incentives and feedback loops Deception Maze example How can we define curiosity or interestingness Open endedness ICML 2019 and Yannic, POET, first MSLST evolutionary algorithms++ POET, the first MLST A lesson to GOFAI people Machine Learning -- the great stagnation Actual scientific successes are usually luck, and against the odds -- Biontech Picbreeder and NEAT How Tim applies these ideas to his life and why he runs MLST Keith Skit about UCF Main show kick off Why does Kenneth value serendipitous exploration so much Scientific support for Kenneth's ideas in normal life We should drop objectives to achieve them. An oxymoron? Isn't this just resource allocation between exploration and exploitation? Are objectives merely a matter of degree? How do we allocate funds for treasure hunting in society A keen nose for what is interesting, and voting can be dangerous Committees are the antithesis of innovation Does Kenneth apply these ideas to his real life? Divergence vs interestingness vs novelty vs complexity Picbreeder Isn't everything novel in some sense? Imagine if there was no selection pressure? Is innovation == environment exploitation? Is it possible to take shortcuts if you already knew what the innovations were? Go Explore -- does the algorithm encode

Why it's here

4 people recommend this

What people say. Recommended as a mind-expanding discussion on open-endedness and the limitations of objective-driven optimization in machine learning.

visargaon Hacker News • Recommends

On “Ask HN: Is the Brain a Computer or an Antenna?”

I think it's mainly a competitive & cooperative self replicator. The brain exists because previous generations did well. Do we need to infuse "antenna magic" into our brains, aren't they marvelous enough? I found this video about open endedness (contrasting evolution vs optimization) in the brain and AI very inspiring: link to this video

ZephyrBluon Hacker News • Recommends

On “NNCP: Lossless Data Compression with Neural Networks (2019)”

…through the filter of "does this directly help me achieve my goals?" isn't the best way to pursue your goals, assuming we're talking about big goals where the path to achieving them isn't clear. I recommend checking out this podcast episode called "Why Greatness Cannot be Planned". It really changed my perspective on achieving my long term goals: link to this video Also on Twitter, yeah some people don't only tweet things in their domain. But I've found that some people do reliably stick to a single domain. Though I don't really follow science people on Twitter.…

visargaon Hacker News • Recommends

On “DeepMind achieves SOTA image recognition with 8.7x faster training”

…on't even know what might be useful later on, then all attempts are good. They increase diversity and discover blind spots. Some of them will be the stepping stones for the future, but we can't say in advance which and how. Link to a long discussion about the evolution of ML ideas and the book "Why greatness cannot be planned" by Kenneth Stanley - link to this video…

visargaon Hacker News • Recommends

On “Feynman: I am burned out and I'll never accomplish anything (1985)”

> Do things that don't matter. Aside from the doors it can unlock, it's just damn fun. I found this discussion about open-endedness being very illuminating about doing stuff that are just fun. A revolt against objectives. link to this video

bvsrinivasanon Hacker News • Recommends

On “Feynman: I am burned out and I'll never accomplish anything (1985)”

In all probability, Youtube's algorithm will already suggest this to anyone who watches the talk, but there is a (very) long, ML Street Talk interview on this idea here link to this video Stanley addresses some strong and subtle criticisms here but I actually preferred the book the most. The book is a bit repetitive but has some very good ideas in the appendix.

visargaon Hacker News • Recommends

On “Crazy New Ideas”

This video is relevant. They talk about "openendedness", serendipity, the tyranny of objectives, the evolution of ideas (and biology), inventing new problems not just solving problems. There are important implications in AI. Kenneth Stanley - Why Greatness Cannot Be Planned on Machine Learning Street Talk. link to this video

visargaon Hacker News • Recommends

On “Campus College of Letters and Science plans to limit high-demand majors”

You're right, the search space is deceptive and going directly towards the goal might lead to a dead end. Only in hindsight we can tell which stepping stones were essential. Immediate results are the best, but in the meantime we need to focus on novelty and interestingness. A great video about open-endedness (warning - very long) with Kenneth Stanley, author of the book "Why Greatness Cannot be Planned" link to this video

mikhailfrancoon Hacker News • Recommends

On “Abandoning Objectives: Evolution with the Search for Novelty Alone (2011) [pdf]”

Lehman & Stanley concerning how explicit objectives encourage effort on exploit rather than explore. AI is progressing using objective functions that can be expressed in a concise form (energy minimization, gradient descent, etc.). A similar mechanism has been at work in industry since Ford and Winslow, from time-and-motion to jit-supply-chain, all under the short-term profit incentive. These are narrow known objectives with a desire to get relatively quick results. But perhaps the big leaps are not achieved by climbing local hills. The observation harks back to Thomas Kuhn, who described the activities of normal science and great leaps - scientific recolutions. Obviously there are further p…

gradschoolfailon Hacker News • Mentions

On “Lessons from history's greatest R&D labs”

@publicdaniel asked below about the relevance of openai’s Ken Stanley of “greatness cannot be planned” fame. @jph00 Can you comment on the similarities and difference of your approach as you understand it, given that Ken is or was a research manager at OpenAI? Here is Ken talking about the concept link to this video link “ collaboration can sometimes thwart innovation by tacitly forcing its participants into an objective-driven mindset.”