ai progress

Tweet from Jack Clark (Anthropic co-founder) sketching a timeline of rough eras of AI research progress, from basic capabilities (2018-2022) to norm/time coherence via RLHF/CAI and agents (2022-2026) to a projected era of scientific intuition/independence starting 2026.

Tweet by will brown arguing against framing recursive self-improvement (RSI) in terms of 'progress multiples,' since comparing LLM-era progress speed to a counterfactual without LLMs is incoherent given that current techniques like judge rewards and synthetic data only make sense because good LLMs already exist.

Tweet by Andy Masley arguing against premature declarations that AI has failed to transform the world, comparing it to dismissing the internet in 1993 and noting the jump from GPT-3.5 to Fable in three years.

Tweet from Jerry Tworek (@MillionInt) speculating that discovering a new, more efficient reasoning method for neural networks is plausible, given the disruptive effects of the first such discovery (reasoning models).

X thread: Andrés (Captain Pleasure) asks how LLMs have recently surprised people. Liu Grey replies that agentic long-running task performance has improved dramatically — describing a 9-hour, 10,000-line-of-code pull request produced by 'fable & opus' (AI models) that was 'close to flawless,' a real-time map overlay for a web dashboard involving GPU work, SharedArrayBuffers, bitops, ported to WebGPU over a quarter-billion tokens.

X reply by Aryeh Kontorovich (@aryehazan) to John Carney's post, terse retort that 'losing our jobs will be the least of our problems' — quote-tweeting Carney's puzzlement over mathematicians' psychological reaction to AI solving open problems.

X post by John Carney expressing puzzlement at mathematicians' psychological reactions to AI solving open problems, arguing it's not an employment crisis but a purely mental one, and questioning why mathematicians uniquely generalize this to 'the fate of humanity.' Quotes Aryeh Kontorovich describing his own existential crisis ~2 years earlier when a colleague solved his problem using Gemini.

X post by davidad (verified) commenting that the human researchers willing to tackle hard problems and those capable of solving them are often different people, quote-tweeting @plumnotes's observation about mixed feelings on AI progress in mathematics depending on whether the problem is in their own field.

Tweet from Prakash arguing AI progress could see a sudden discontinuity from a transformer-scale algorithmic breakthrough, citing an 'idiot index' comparing the 20-watt human brain to the 14,000-watt Nvidia B300 GPU as evidence of ~700x remaining efficiency headroom.

Self-threaded tweet (reply to own earlier tweet), same author as several other tweets in this batch.

Simple quote-tweet, no additional images.

Plain text tweet, no images beyond profile pictures.

Ethan Mollick observing that multiple well-funded startups are betting against pure LLM scaling and pursuing alternative architectures, framed as increasing overall AI progress redundancy. Relevant to Nathan's tracking of AI progress/timelines and architecture diversity (parallels his own brain_graph_1 work as an alternative-architecture bet).

A reflection on the pace of technological change from 1990 to 2026, using AI coding agents as the capstone example of "unbelievable" progress, closing with the "Everything is amazing and nobody is happy" line (a nod to the Louis CK bit). Relevant to Nathan's tracking of public sentiment on AI progress and capability timelines.

A joke tweet capturing the sense that AI progress is moving fast enough that near-future extrapolation feels like sci-fi. Light context for the same fast-takeoff mood as the adjacent METR/Noam Brown screenshot.

A short, jokey tweet observing that AI models are increasingly exhibiting apparent preferences rather than random behavior (the "tomato angst" line likely riffing on some emergent-preference anecdote). Light general commentary tangential to Nathan's model-welfare interest in whether emergent preferences reflect something real.

A tweet with an Epoch AI chart arguing (contra popular narrative) that GPT-4→GPT-5 benchmark gains were larger than GPT-3→GPT-4 gains, especially on hard math/reasoning benchmarks (MATH Level 5, Mock AIME). Relevant to Nathan's tracking of empirical AI capability progress/scaling trajectory (cf. his singularity-rate tracking notes, Davidson/Houlden, METR).

A poetic tweet from David Holz (Midjourney founder) framing technological progress as a recursive tool-building process culminating in simulation of mind. Reflects the kind of big-picture AI-progress commentary Nathan tracks.

Noam Brown (OpenAI researcher) argues LLM eval saturation claims are overstated, listing tasks LLMs still fail at; follow-up tweet on grad students contributing via better evals. Relevant to Nathan's interest in AI capability evaluation and benchmarking.