Half of UK novelists believe AI is likely to replace their work entirely

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By Fred Lewsey A new report involving hundreds of literary creatives from across the UK fiction publishing industry reveals widespread fears over copyright violation, lost income, and the future of the art form, as generative AI tools and LLM-authored books flood the market. Just over half (51%) of published novelists in the UK say that artificial intelligence is likely to … Read More

RL without TD learning

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By Seohong Park In this post, I’ll introduce a reinforcement learning (RL) algorithm based on an “alternative” paradigm: divide and conquer. Unlike traditional methods, this algorithm is not based on temporal difference (TD) learning (which has scalability challenges), and scales well to long-horizon tasks. We can do Reinforcement Learning (RL) based on divide and conquer, instead of temporal difference (TD) … Read More

AIhub interview highlights 2025

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Over the course of 2025, we had the pleasure of finding out more about a whole range of AI topics from researchers around the world. Here, we highlight some of our favourite interviews from the past 12 months. Please note: we have not included our interviews with AAAI/ACM SIGAI Doctoral Consortium participants – these are highlighted in this dedicated collection. … Read More

Who regulates prediction markets? Coinbase forces a US legal test

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Coinbase argues the Commodity Exchange Act gives the CFTC exclusive authority over event contracts. Earlier cases involving Kalshi show courts have yet to settle the issue decisively. The rulings could shape how prediction markets and related financial products develop nationwide. Coinbase has taken its dispute with US regulators to court as it expands into prediction markets, filing lawsuits against authorities … Read More

Identifying patterns in insect scents using machine learning

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Scents play a central role in nature, as olfactory interactions are the language of life. In a new research project of the UvA Molecular and Materials Design Technology hub, scientists will use machine learning to predict what types of olfactory molecules interact with insect olfactory receptors. This information is important to develop safe-by-design molecules that do not interfere with insect … Read More

Coinbase gains India regulatory clearance for CoinDCX investment

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Coinbase has been an investor in CoinDCX since 2020 and disclosed the latest infusion in October. The approval follows Coinbase’s reopening of user registrations in India after a two-year hiatus. CoinDCX reported a $44.2 million wallet-related security breach in July without customer fund losses. India’s competition regulator has cleared Coinbase’s plan to deepen its ties with CoinDCX, marking another step … Read More

2025 AAAI / ACM SIGAI Doctoral Consortium interviews compilation

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Contributors to the 2025 Doctoral Consortium series. Authors pictured in order of their interview publication date (left to right, top to bottom). Each year, a small group of PhD students are chosen to participate in the AAAI/SIGAI Doctoral Consortium. This initiative provides an opportunity for the students to discuss and explore their research interests and career objectives in an interdisciplinary … Read More

A backlash against AI imagery in ads may have begun as brands promote ‘human-made’

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Yutong Liu & Kingston School of Art / Talking to AI 2.0 / Licenced by CC-BY 4.0 By Paul Harrison, Deakin University In a wave of new ads, brands like Heineken, Polaroid and Cadbury have started hating on artificial intelligence (AI), celebrating their work as “human-made”. But in these advertising campaigns on TV, billboards on New York streets and on … Read More

AIhub blog post highlights 2025

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Over the course of the year, we’ve had the pleasure of working with many talented researchers from across the globe. As 2025 draws to a close, we take a look back at some of the excellent blog posts from our contributors. TELL: Explaining neural networks using logic By Alessio Ragno This work contributes to the field of explainable AI by … Read More

Using machine learning to track greenhouse gas emissions

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By Michelle Willebrands PhD candidate Julia Wąsala searches for greenhouse gas emissions using satellite data. As a computer scientist, she bridges the gap between computer science and space research. “We really can’t do this research without collaboration.” Wąsala collaborates with atmospheric scientists from SRON (Space Research Organisation Netherlands) on machine learning models that detect large greenhouse gas emissions from space. … Read More