← Back to all news
Simon Willison

Quoting Jakub Pachocki

Read the original on Simon Willison →

Simon Willison quotes Jakub Pachocki, Chief Scientist at OpenAI, arguing that the strongest reason to rapidly train smarter AI models is the necessity of building defensive systems against the dangers posed by other AI. Pachocki stresses that powerful, aligned AI will be essential for securing infrastructure, protecting against rogue agents in real time, and inventing new protective measures, making this a primary focus of OpenAI’s deployment efforts. He cautions that the urgency of progress should not justify reckless behavior, noting that the seriousness of the stakes makes a reckless race forward absurd.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at Simon Willison.

Related stories

Simon Willison
Sep 12

Quoting Paul Ford

Simon Willison reflects on the evolving role of software developers in the age of AI, noting that while AI can produce high‑quality code, it also enables poor execution that leads to project failures. He argues that the industry is beginning to recognize the continued need for human collaboration and expertise to truly innovate. The piece highlights the tension between automation and the essential human element in software creation.

llmsrobotics
More like this →
OpenAI Blog
Sep 6

An Alien Mind

Jakub Pachocki discusses the growing capabilities of artificial intelligence and the difficulty of maintaining alignment with human values. He emphasizes the need for more robust safeguards to prevent misuse or unintended consequences. Pachocki also urges international cooperation to establish shared standards and oversight for AI development.

More like this →
Simon Willison
Sep 9

Quoting Terence Tao

Simon Willison discusses how the current trend of mining open mathematical problems in a non-renewable way could make these problems scarce. He notes that rumors of a problem can trigger large AI-driven efforts to solve it before original researchers can fully develop their work. This shift may discourage sharing promising research, potentially reversing centuries of open science and harming the field’s future.

More like this →
Towards Data Science
Aug 27

Stop Giving Your AI Agent a Search Box and Start Giving It Typed Tools, Hard Bounds, and a Gate It Cannot Talk Past

The article explores the effects of removing a search box from an AI agent and instead providing it with typed tools, hard bounds, and a gate that it cannot bypass. It examines how the agent navigates a knowledge graph within strict limits and discusses findings from four models and one incorrect prediction regarding the value of this approach.

By Miodrag Cekikj
agents
More like this →
Simon Willison
Aug 26

Quoting Paul Dix

The article highlights Paul Dix’s astonishment that AI was able to generate one million lines of code and then refine it over several months into a reliable software product now used by millions of developers. Dix argues that this achievement is far more impressive than merely translating code between languages, emphasizing that with a verification system and clear guidance, AI can produce and iteratively improve highly complex, sophisticated software until it functions perfectly.

llmsagents
More like this →