Desktop Linux is insecure(bjornpagen.com)
48 points by bjornpagen | 38 comments
First screen, captured .
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Why are your models so big? (2023)(pawa.lt)
23 points by jxmorris12 | 13 comments
Policy on the AI Exponential(darioamodei.com)
131 points by yjp20 | 190 comments
Human Bottlenecks(borretti.me)
106 points by zdw | 34 comments
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GLM 5.2 and the coming AI margin collapse(martinalderson.com)
641 points by martinald | 412 comments
Blog post by Martin Alderson, first of a two-part series arguing that open models like GLM 5.2 will drive a collapse in AI provider margins.
What AI-Native Looks Like(fagnerbrack.com)
14 points by fagnerbrack | 7 comments
A blog post by Fagner Brack on Medium describing what an AI-native approach to software development with stable infrastructure looks like.
The path to ubiquitous AI (17k tokens/sec)(taalas.com)
804 points by sidnarsipur | 436 comments
Taalas blog post by Ljubisa Bajic arguing that latency and cost limit AI adoption and presenting its approach to very fast (17k tokens/sec) inference hardware.
LLMs aren't world models(yosefk.com)
330 points by ingve | 189 comments
Blog post by Yossi Kreinin arguing that large language models are not world models, illustrated with examples like LLMs losing track of chess board state.
How to Finetune GPT-Like Large Language Models on a Custom Dataset(lightning.ai)
465 points by T-A | 118 comments
Lightning AI blog tutorial by Aniket Maurya explaining how to finetune GPT-like large language models on a custom dataset.
Local AI needs to be the norm(unix.foo)
1767 points by cylo | 699 comments
Blog post on unix.foo arguing that apps should run AI models locally rather than relying on API calls to OpenAI or Anthropic.