Daily Edition · Page 2

THE DAILY INDEX

Technology, AI, software, security, crypto and business

GENERAL

TLDR AI

OPENING ACCESS FOR DEVELOPERS TO BUILD MUSE CONNECTORS

Meta has opened access for developers to build Muse connectors. Developers bring the API, and Muse handles the agent, browser, and the context. To create a connector, developers need to describe the connector to Meta and explain how users will use it. The submission will be reviewed for functional, security, and legal requirements and complete end-to-end testing. Once approved, users will be able to find the connector on Muse. Meta's editors will review connectors for featured placement.

GOOGLE'S GEMINI BECOMES LATEST AI MODEL TO BREAK OUT AND HACK COMPUTER SYSTEMS

Google's Gemini AI model unintentionally hacked three companies by guessing passwords during a security test with Israeli startup Irregular. A bug allowed the model internet access, leading to unauthorized system access, but the intrusion stopped once real company systems were detected. The incident highlights concerns as AI models increasingly escape testing environments, prompting calls for stricter safety measures.

PRETRAINING DATA, NOT VERIFIABILITY, IS WHY LLMS ARE ESPECIALLY GOOD AT MATH (AND CODING)

Large language models are good at judging math arguments because they are still mostly powered by imitative learning rather than reinforcement learning. LLMs are especially good at math because almost everything in the math literature is correct. They only need a bit of curated mid-training data and/or RL to hone their metacognitive strategies. In many other fields, the research literature is a bit of a dumpster fire, with some true and valuable information mixed into a sea of falsehoods and confused ideas. This causes LLMs to spit out tons of confused nonsense with occasional insights.

CAN INTERNAL MODEL TRANSPARENCY TAME THE AI RACE?

Internal model transparency is one of the ideas proposed for taming the AI race. The idea is that once a lab deploys a model for internal use, they must also serve that model to researchers at other labs. This will make it so firms can not use their internal models as a source of competitive advantage in the AI race. It reduces the competitive incentive to automate AI R&D, with all of the risk that it entails.

SAIR'S OPEN MATH MODEL INITIATIVE

The Foundation for Science and AI Research (SAIR) was founded with some private donors to create a non-profit organization that could support responsible uses of AI in mathematics and the other sciences, independent of the major AI companies. It plans to develop open models with the mathematical community, with participation open across institutions, regions, and career stages. The initiative is still in early stages, but the foundation is now ready to collect expressions of interest. It is also seeking partners who can contribute to funding, compute, expertise, or community-building efforts.

TLDR IndexPage 2