The AI Reader.
Monday, August 24, 202645 min read
Working Knowledge · What Could Go Wrong

Kleinberg and Raghavan proved algorithmic monoculture can hurt social welfare

The 2021 theorem's worked case gives about a 4% welfare loss under three candidates and Gaussian noise. In the same paper's Plackett-Luce case the effect vanishes.

10 min read9 sources
Working Knowledge · The Instruments

At the top of the RewardBench leaderboard, higher scores predicted lower Chatbot Arena rank

AI2 built the benchmark in March 2024 to score a reward model on 2,985 fixed chosen-versus-rejected pairs. Berkeley's follow-up training work that year found the top of the leaderboard sorting the wrong way against Chatbot Arena rank.

9 min read10 sources
Working Knowledge · The Mechanics

The wait before a chatbot's first word barely tracks the prompt's length

Anyscale measured a Llama 2 70b prompt token at about a hundredth of what an output token costs in end-to-end latency, well below the tens-of-thousands regime where quadratic attention drives the pause.

9 min read12 sources
Working Knowledge · When AI Breaks

NYC's MyCity chatbot told ten Markup staffers landlords can refuse Section 8 vouchers

Adams put the chatbot on chat.nyc.gov in October 2023 pointed at 2,000 NYC Business pages. Mamdani took it down 27 months later, after wrong answers on housing, tips, and cash payments.

9 min read10 sources
Working Knowledge · The Evidence

Today's RAG pipelines fine-tune neither piece the paper trained together

Lewis et al. froze DPR's document encoder and fine-tuned its query encoder alongside BART. The RAG that ships today wires two frozen off-the-shelf pieces.

8 min read8 sources