Kenneth Stanley (@kenneth0stanley) / X

Kenneth Stanley

2,034 posts

Kenneth Stanley

@kenneth0stanley

SVP of Open-Endedness @LilaSciences. Prev: Maven CEO, Lead@OpenAI, Uber AI, prof@UCF. NEAT,HyperNEAT,novelty search, POET. Book:Why Greatness Cannot Be Planned

San Francisco, CA

Joined March 2016

Pinned
Kenneth Stanley
@kenneth0stanley
Mar 23
Job opportunity: the Open-Endedness Team at @LilaSciences is seeking a talented research engineer who would enjoy applying your wizard-like technical skills to genuinely deep and fundamental AI research into the algorithmic basis of creativity and innovation. This role is about
19K
Kenneth Stanley
@kenneth0stanley
Sep 10, 2025
If you’re struggling to understand what people mean when they say things like “truly understand,” it boils down to Unified Factored Representation (UFR). That’s the foundation behind the slippery intuition.
François Chollet
@fchollet
Sep 9, 2025
A student who truly understands F=ma can solve more novel problems than a Transformer that has memorized every physics textbook ever written.
193K
Kenneth Stanley
@kenneth0stanley
May 20, 2025
Could a major opportunity to improve representation in deep learning be hiding in plain sight? Check out our new position paper: Questioning Representational Optimism in Deep Learning: The Fractured Entangled Representation Hypothesis. The idea stems from a little-known
164K
Kenneth Stanley
@kenneth0stanley
Aug 7, 2025
Those who intuit something is lacking in LLMs struggle to pinpoint the gap beyond inadequate metaphors like “stochastic parrot” or “glorified autocomplete.” What you’re groping for is fractured entangled representation (FER). That’s the concrete crux of your slippery intuitions.
82K
Kenneth Stanley
@kenneth0stanley
Apr 23, 2020
I'm thrilled to announce that I will be joining the superb team at @OpenAI in June, where I will be starting a group (and indeed hiring) focused on achieving open-endedness in machine learning. Looking forward to exploring a novel path!
Kenneth Stanley
@kenneth0stanley
Jun 20, 2022
New paper from our team @OpenAI: “Evolution through Large Models.” Idea: Large language models trained on code can propose mutations to programs of unprecedented coherence. Broad implications for EC,Genetic Programming,RL,deep learning,open-endedness. arxiv.org/abs/2206.08896 1/4
Kenneth Stanley
@kenneth0stanley
Jan 17, 2024
Announcing Maven: We’ve created a new kind of social network - a serendipity network - that’s directly inspired by insights from open-endedness and Why Greatness Cannot Be Planned. iPhone: apps.apple.com/app/maven-the-… Android: play.google.com/store/apps/det… It's very different.... More 👉
102K
Kenneth Stanley
@kenneth0stanley
Sep 12, 2023
Though it does some optimization, natural evolution is not primarily an optimization algorithm. It's unfortunate that classical genetic algorithms created a misapprehension among computer scientists that evolution is best abstracted as optimization. So what is evolution? 1/2
Yann LeCun
@ylecun
Aug 28, 2023
I'd say *optimization* is the only way to obtain complexity from primeval simplicity. There are many ways to optimize . Darwinian evolution (mutate and select among a population) is just one particularly simple and *inefficient* way to perform zeroth-order optimization. But there
180K
Kenneth Stanley
@kenneth0stanley
Mar 10, 2025
Important announcement (with job opportunities!): I’m thrilled to share that I just joined @LilaSciences as SVP of Open-Endedness! Lila is a new name in the AI space, but one you will be hearing a lot from. Their unique mission to pursue Scientific Superintelligence could not
00:00
63K
Kenneth Stanley
@kenneth0stanley
Sep 28, 2025
So much controversy triggered by claims about how humans learn. But the deeper question is why the way we learn works. We need to understand the why to know in what way “how” matters. Nature is inspiration for AI, not prescription. The crux of the whole debate is abstraction.
Dwarkesh Patel
@dwarkesh_sp
Sep 26, 2025
.@RichardSSutton, father of reinforcement learning, doesn’t think LLMs are bitter-lesson-pilled. My steel man of Richard’s position: we need some new architecture to enable continual (on-the-job) learning. And if we have continual learning, we don't need a special training
00:00
58K
Kenneth Stanley
@kenneth0stanley
Nov 14, 2022
Mostly missing from current ML discourse: the order in which things are learned profoundly affects their ultimate representation, & representation is the true heart of “understanding.” But we just shovel in the data like order doesn’t matter. No AGI without addressing this. 1/2
Kenneth Stanley
@kenneth0stanley
Jul 14, 2024
When you realize your book can still go viral 9 years after it was published. (Thanks @bmix012 !)
This Post is from a suspended account. Learn more
49K
Kenneth Stanley
@kenneth0stanley
Jul 26, 2024
I'm curious, if you think "LLMs can't reason," what do you precisely mean by that and why do you think that is? In particular I'm curious about insights beyond "they are just doing statistics" or "they just make predictions." What beyond that do you think supports the claim?
135K
Kenneth Stanley
@kenneth0stanley
Sep 21, 2018
NEAT (NeuroEvolution of Augmenting Topologies) is now available to work with PyTorch, thanks to Alex Gajewski @UberAILabs ! github.com/uber-research/… . Also includes CPPNs and HyperNEAT capabilities.
GitHub - uber-research/PyTorch-NEAT
From github.com