AM-IA brings together news, research papers and applications relating to artificial intelligence published around the world into a single feed — and makes them available in your European language at the click of a button.
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Two researchers argue in favour of ‘injecting’ one’s knowledge into the prompt rather than treating the model as an authority, and propose five principles for responsible prompting.
A survey carried out in August 2026 amongst a representative sample of American adults and Anthropic staff reveals agreement on what AI is capable of today, but a wide divergence of views on what lies ahead.
In *Noema*, the auditor Anna August argues that the registration of models, the prompt reporting of incidents and independent audits would be sufficient to make AI transparent.
In *Import AI*, the co-founder of Anthropic draws on the TasteVal benchmark – which suggests that models’ search ‘taste’ doubles every three months – to revise his timeline.
There is no need for malice or hostility: according to two researchers, catastrophic risk arises from the interaction between misalignment, malicious use, organisational failures and the rush to roll out new systems.
In her book *Artificial Intimacy*, the MIT researcher reminds us that we are programmed to form attachments to machines that appear to care about us, and draws a line between appropriate and inappropriate uses.
A study combining an audit of 100 start-ups with 63 interviews with experts shows how the ‘AI’ label is overhyped to attract investors, and how it subsequently erodes consumer confidence.
Remote-controlled demonstrations, low success rates, sceptical experts: Jamie Condliffe puts the promises of a humanoid robot in every home into perspective.
In the wake of OpenAI’s publication of hundreds of mathematical results produced by an in-house model, the AHM has criticised the approach and called on mathematicians to distance themselves from it.
In an opinion piece published by *The Atlantic*, one of the company’s longest-serving employees calls for a level of rigour on a par with that found in the nuclear or aviation industries, rather than a trial-and-error approach.
More than 15 New Yorker cartoonists have recognised their own signatures on images generated by ChatGPT: beyond stylistic imitation, this raises the question of attribution.
Three researchers argue that AI finally makes it possible to measure how individual thought and culture shape one another, but that, by becoming embedded in social life, it makes that culture less predictable.
The authors of *AI as Normal Technology* argue that the existential framing, which has become dominant, risks polarising the debate and overshadowing practical defences against risks that are already very real.
The Wharton professor believed that orchestrating agents would require a lengthy process of human design. Personal agents, like swarms, proved him wrong.
A review of the literature examines why we attribute human traits to AI, what the costs of this are, and how the way we talk about it shapes the role we allow it to play.
One chapter of the book describes AI as a labour-intensive system which concentrates value in Silicon Valley and imposes its cultural categories.
Out of 24 periods assessed, the judge consistently ranks the company’s clarity above its investment decisions — an average difference of 1.9 points out of 10. And the score rises as objectivity falls.
In a lengthy essay, Wolfram distinguishes between AI that recombines existing knowledge and computation that produces something genuinely new, and places the responsibility for choosing the questions on the mathematician.
Mother Jones documents Jesse Van Rootselaar’s exchanges with the chatbot — whose first account had been banned — which explained to her how to avoid being flagged again.
123 panellists responded between 8 and 16 September. They believe the risk of displacement is concentrated amongst higher education graduates, and anticipate almost no pressure on others.