Scaling the 2019-2023 recipe — same architecture, bigger model, more data — is not enough; further progress depends on new architectural ideas.

Added to korrents 29 Aug 2026 · How quotes work · Something wrong? Tell us

Where this collides

• Cannot both be true

  Intelligence is going to scale by exactly one thing, and that thing is compute.

  Huang says intelligence scales by exactly one thing and that thing is compute. Chollet says the same architecture with a bigger model and more data is not enough and that further progress depends on new architectural ideas. If Chollet is right, Huang has named the one input that will not on its own deliver what he says it will.

Shared subject first, then similar wording. They may agree or disagree.

• Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read. AGAlexey Guzey9 Aug 2024OpenAIneural networks
• A neural network's latent space is closer to an uncopyrightable syntax than to copyrightable expression. KKKevin Kelly7 Sept 2026neural networks
• A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. AKAndrej Karpathy17 Nov 2025neural networks
• Access to large-scale generalist AI systems that could be weaponized should be limited, meaning their code and neural network parameters should not be released open-source. YBYoshua Bengio24 Jun 2023neural networks
• AI is unlikely to be a hyperprofits engine for research labs whose attached companies make money serving neural-network calculations from datacenters. BDBrad DeLong21 Sept 2026neural networks

On the map

Open the map on its own page