2023 was the breakthrough year for Large Language Models (LLMs). I think it’s OK to call these AI—they’re the latest and (currently) most interesting development in the academic field of …
The Thoughts The Civilized Keep
The hype around a new AI language generator reveals the sterility of mainstream thinking on AI today — and indeed on how we think about thinking itself.
Artificial intelligences and human scientists exhibit...
We investigate the effectiveness of artificial intelligences (AI)-specifically large language models (LLMs)-relative to human scientists at high-level cognitive tasks in social science such as...
Where will AI be at the end of 2027? A bet
We, Gary Marcus, author, scientist, and noted skeptic of generative AI, and Miles Brundage, an independent AI policy researcher who recently left OpenAI and is bullish on AI progress, have agreed to the following bet, at 10:1 odds, with criteria drawn from two earlier Substack essays by Gary that proposed criteria for
We Don't Understand Neural Networks At The Algorithmic Level
The largest ongoing debate about AI is “Are Large Language Models (LLMs) intelligent?” That makes sense, at least: the evidence is ambiguous and the stakes a...
How we use AI at Stalwart
It is difficult to have a conversation about software in 2026 without AI showing up in it. Two years ago the interesting question was…
More Than a Tool
What We Learned from a Year of Conversations About AI
AI made me doubt everything about programming by Felienne Hermans - DDD Europe 2026
AI made me doubt everything about programming by Felienne Hermans - DDD Europe 2026
The 2026 AI Index Report | Stanford HAI
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Unresolved debates about the future of AI
How far the current paradigm can go, AI improving AI, and whether thinking of AI as a tool will keep making sense
Big AI is accelerating the metacrisis: What can we do?
The world is in the grip of ecological, meaning, and language crises that are converging into a metacrisis. Big AI is accelerating them all. LLM engineering sits at the core. Despite the public good motives of language engineers and the promise of LLMs, this work is being leveraged to create unprecedented wealth and power for a handful of individuals and corporations while causing existential harm to life on earth. As a profession, we urgently need to come together to explore alternatives and to design a life-affirming future for our field of natural language processing that is centered on human flourishing on a living planet.
Large language models are not the problem
If a Large Language Model (LLM) can replicate your scientific contribution, the problem is not the LLM. What does it say about our field that so much of the anxiety about AI comes down to the fear that a machine could do what we do? Perhaps it says we should be doing something better.
Is there something it is like to be an AI?
Posted on Wednesday 2 Jul 2025. 1,593 words, 6 links. By Matt Webb.
