TechCrunch reported on Graphite's new research: comparing 10,000 human articles written before ChatGPT's release with rewritten versions by various models, it identified 13,000 phrases that appear at least 2x more frequently in AI text.
Anthropic Frontier Red Team evaluated multiple models on 100 randomly sampled tasks from an internal Binary Exploitation benchmark; GLM-5.3 achieved full control-flow hijack in 4% of trials, and Claude Mythos Preview in 6%. Earlier models like Claude Opus 4.6 and GLM-5.2 had no successes, and the author argues a meaningful threshold has been crossed.
A new working paper by CESifo economists Robert Fairlie and Jane Wu in Munich finds no evidence, in absolute or relative terms, of significant or widespread job displacement or hiring cutbacks among recent college graduates.
A new OpenAI economic research report analyzes how workers use AI beyond traditional job roles and which new activities have become a routine part of their work. The report reveals patterns of AI use in real-world work.
Epoch and METR released the MirrorCode benchmark, testing AI's ability to reimplement complete software with CLI access alone; 17 of 25 target programs had at least one perfect run, and Claude Opus 4.7 completed a task humans estimated at 2-17 weeks in 14 hours with $251 in inference costs.
In Import AI issue 464, Jack Clark reports that Fable wrote a megakernel in CUDA achieving an 18.71X speedup on KernelBench-Mega.
Import AI issue 462 rounds up multiple items: research from Oxford, the UK AISI, Stanford, and others, via 4 experiments and 18,978 conversations with 6,923 people, found that AI (strongest being Opus 4.1 and Opus 4.6) consistently surpasses expert humans at textual persuasion, raising 10.8 percentage points more in real donations than professional fundraisers; when AI is restricted to human speed and length, the advantage falls to insignificance.
Import AI issue 459 reports: researchers from the University of Virginia, Anthropic, and the Bank of Canada estimate the US AI economy at roughly $250 billion nominal in 2025, with quality-adjusted real output growing about 2,600% a year, yet hard to see in GDP because of falling prices and the high share of inference. The UK AI Security Institute argues that using AI to oversee training processes to automate alignment research is not a panacea and is harder in practice than expected.