“We analyze the expected behavior of an advanced artificial agent with a learned goal planning in an unknown environment. Given a few assumptions, we argue that it will encounter a fundamental ambiguity in the data about its goal. For example, if we provide a large reward to indicate that something about the world is satisfactory to us, it may hypothesize that what satisfied us was the sending of the reward itself; no observation can refute that. Then we argue that this ambiguity will lead it to intervene in whatever protocol we set up to provide data for the agent about its goal.”

– On controlling AI.

Predicting odours from their molecular structure.

How ML transformers seem to mimic parts of the brain.

Examples of using DALL-E 2.

Review of futurist predictions.

The future of EDA tools for the semi-conductor industry.

Lex Fridman interviews DeepMind’s Demis Hassabis. [YouTube]

The history of Bell Labs. [YouTube]