This post introduces the concept of updatelessness for agents that follow a policy they would have wanted to commit to before learning their situation, even if a different action seems better after updating on observations. Examples like 'Parfit's Hitchhiker' are presented, and various approaches to updatelessness are discussed.
The chart will appear after repeat observations. The current metric comes from the source.
14 source pointsReal observations only. History before source connection is not reconstructed.
Understanding updatelessness can be useful for developing agents that make decisions based on prior commitments rather than current circumstances.
The website www.huggingface.wtf was launched, providing an accessible and comprehensive explanation of the Hugging Face incident. The site includes an AI quotes database for searching agent statements and sources related to the incident.
yesterdayLessWrongAnthropic released documents related to a copyright litigation case. The documents outline the company's research plans from 2021, including the development of a safe general AI assistant capable of programming tasks. The documents do not represent the company's official stance.
6 days agoLessWrongThe article discusses the existence of internal models that may not be publicly available and their impact on perceptions of AI capabilities and risks. It presents a graph showing a sharp increase in OpenAI's spending on AI agents, raising questions about its sustainability.
2 days agoLessWrongThe article examines the impact of the λ parameter, which measures task parallelism, on the efficiency of AI swarms. The author analyzes how changes in λ affect computational resource scaling and AI development timelines.
yesterdayLessWrong> TL;DR: I discovered (a few) exoplanet candidates, I walk through how. Then I talk about the near future of science given the ease of and growing capabilities of agentic systems. These are largely independent sections, you can skip ahead. > LLM Usage: All text was generated by a Human Language Model, the discovery itself was done mostly by Claude Opus 5.5. The widgets are all Claudeslop code but they really do help with the explanation so please bear with them. Exoplanet The Transiting Exoplanet Survey Satellite (TESS) was built for detecting exoplanets. Each month (27 days) TESS focuses on a different patch of the sky, and every 200 seconds its wide field-of-view cameras repeat their observations of that particular patch of the celestial sphere. In 2023 NASA estimated that TESS has photographed over 93% of the night sky at least once. TESS's observational sectors, from NASA's "How to find an Exoplanet with TESS data" In one of these sectors (55 to be exact[1]), there's a star elegantly named TIC 423560969. Given that TESS is made to scan large swaths of the night sky very quickly, the resolution isn't too great, yet as you'll see there's still a pretty clear signal that can be extracted. We can make a time-lapse of the month during which the star was recorded by TESS. It's not particularly illuminating. There's a lot of noise and being 2,300 light-years away doesn't help. It's not perceptible when a transit (partial eclipse) is happening. TESS actually scanned this star twice: Once in August 2022 and once in May 2025. By looking at when the star's brightness dips (or more precisely, at the period of the dips) we can get the exoplanet's orbital period. We can then test this on the other month of observations by TESS and double-check that the transit really does occur with that periodicity. There are a few steps to cleanly extract the transit's effect on the star's brightness, removing the sky's (changing w.r.t time) background glow, de-noising etc.
3 hours agoHacker NewsDocuments indicate that a police officer provided her Flock login to her husband, who is an ICE agent.
yesterday