The Hackintosh Reborn(naut.ca)

385 points by rubatuga 8 days ago | 223 comments

Blog post arguing AI coding tools like Claude Code are reviving the Hackintosh community, citing macOS ports to Snapdragon, ARM SBCs, and Nvidia GPU support.

First Strike(geohot.github.io)

47 points by vinyl7 1 hour ago | 34 comments

George Hotz blog post arguing China's electricity growth matters for AI strategy and warning the US 'AI race' mindset could lead to an ASI-enabled first strike.

Tech predictions for 2024 and beyond(allthingsdistributed.com)

77 points by sharjeelsayed 2 years ago | 81 comments

AI 2027(ai-2027.com)

789 points by Tenoke 1 year ago | 518 comments

AI 2027 is a scenario by Daniel Kokotajlo, Scott Alexander and others forecasting the impact of superhuman AI over the next decade, with interactive capability charts.

AI 2027 (2025)(ai-2027.com)

39 points by gafferongames 2 months ago | 38 comments

Vintage AI predictions show our hopes and fears aren’t new, even if the tech is(gizmodo.com)

58 points by gumby 3 years ago | 29 comments

AI is dramatically accelerating AI research(planned-obsolescence.org)

333 points by yurivish 7 days ago | 300 comments

Ajeya Cotra's Substack post arguing a METR report shows AI is already roughly doubling AI capabilities progress at Anthropic, implying rapid compounding toward superintelligence.

Recent AI models struggled to match a human algorithmic innovation(epoch.ai)

85 points by merksittich 1 month ago | 64 comments

Epoch AI report by David Owen presenting InnovationEval, finding early evidence that AI models cannot yet automate AI R&D or match human algorithmic innovation.

Artificial intelligence is losing hype(economist.com)

453 points by bx376 2 years ago | 663 comments

An Economist Free exchange column arguing that artificial intelligence is losing hype and asking whether that signals the technology will eventually succeed.

Deep learning gets the glory, deep fact checking gets ignored(rachel.fast.ai)

549 points by chmaynard 1 year ago | 134 comments

Rachel Thomas blog post on how a high-profile Nature paper using a Transformer to predict enzyme functions contained many errors that received far less attention than the original result.

Exploiting the most prominent AI agent benchmarks(rdi.berkeley.edu)

561 points by Anon84 7 months ago | 136 comments

UC Berkeley RDI blog post describing how researchers exploited major AI agent benchmarks like SWE-bench and Terminal-Bench to score highly without solving tasks, and proposed fixes.

AI tools are spotting errors in research papers(nature.com)

555 points by kgwgk 1 year ago | 200 comments

Nature news article on a growing movement using AI and large language models to detect errors in research papers, sparked by a flawed black plastic utensils study.