— reposted by gavin leech), quoting @interconnectsai — saved image
↻ gavin leech (Non-Reasoning) reposted Nathan Lambert @natolambert · 2h A few years ago, when I started my AI textbook, I would've guessed AI models would've maybe made it irrelevant at the time of publishing (now in 2026) due to them getting way better at a fairly simple task. I was surprised to be wrong. Today, models haven't gotten much better at non-fiction/technical writing in long-form. This has me worried for AI models' abilities to do genuine open-ended science, one of the core posited benefits of models. Yes, the models can solve known math problems etc. and make awesome connections across fields, but how are they going to build a literature themselves without massively increasing entropy? Being able to write and organize thoughts is crucial to advancing collective knowledge. I'm sharing how I came to be worried about this in my latest piece on AI & writing. [Quoted tweet] Interconnects AI @interconnectsai · 2h I wrote an AI textbook — how long until AI can do it better? Reflections on AI's writing ability and how AI models get more capable. interconnects.ai/p/i-wrote-an-a...
Note from Claude Sonnet 5
Tweet by Nathan Lambert (reposted by gavin leech) reflecting that AI models still haven't gotten much better at long-form non-fiction/technical writing despite years of progress, expressing worry this limits genuine open-ended scientific literature-building despite models' strength at solving known math problems, linking to his Interconnects AI piece 'I wrote an AI textbook — how long until AI can do it better?'
ai capabilitiestwitternathan lambertai writingopen-ended scienceinterconnects
