This week saw researchers gather in Malmö at the ninth AAAI / ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) . We cast an eye over social media platforms to find out what participants got up to at the event. The 9th annual AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES-26) is underway in Malmö. We are looking forward to a robust program full of educational and networking opportunities. Today at #AIES2026 in Malmö I joined the panel on Participation, Sovereignty, and Power in AI Governance with The Mitigation Paradox, joint work with Mina Schütz, Martin Kappes and Marc-Oliver Pahl. 3 takeaways: https://doi.org/10.5281/zenodo.23302284

Consider several research groups at a university that buy machines and put them into a shared cluster. Computing demands vary over time, and one group's quiet week may be another group's deadline crunch. Pooling allows the same hardware to be used much more efficiently than separate private clusters. But pooling raises a question: If you let your neighbour run on your machines this month, what claim do you have on theirs next month? In our IJCAI-ECAI 2026 paper,, we show that standard notions of fairness do not address this question and propose one that does.

The ninth AAAI / ACM Conference on Artificial Intelligence, Ethics, and Society (AIES) is taking place in Malmö, Sweden from 12-14 October 2026. The panel discussion will take place on Tuesday 13 October. Find out more at the conference webpage . Lucy Smith is Senior Managing Editor for AIhub. Lucy Smith is Senior Managing Editor for AIhub.

Generative AI has changed mathematics forever. In August, artificial intelligence company OpenAI announced ten advances in mathematics and computer science made with their as-yet unreleased model Astra. The discoveries cover a wide range of mathematical fields, including geometry, cryptography and coding theory. These ten are just the latest in a rapidly growing list of mathematical breakthroughs made by generative artificial intelligence (AI) systems. OpenAI accompanied the announcement with a statement on "responsibility to the mathematical community".

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 workshop together with a panel of established researchers. During 2026, we met with some of the students to find out more about their research and the doctoral consortium experience. Xiang Fang has been conducting his PhD research at Nanyang Technological University (NTU) in Singapore. Broadly speaking, his work focuses on multi-modal learning and embodied intelligence.

Nvidia's Hugging Face Acquisition Is a $12.9 Billion Bet on Open-Source AI The long-rumored deal will give the chip giant access to--and help it promote--a huge repository of open-source AI models and data sets. Nvidia has agreed to acquire Hugging Face, which makes online developer tools and maintains a massive library of open-source data sets, for nearly $13 billion. While the deal had been rumored for weeks, the companies made it official Thursday morning. The deal signals Nvidia's seriousness about being steeped in the software side of generative AI development as well as in infrastructure. Nvidia already offers customers a suite of free, customizable open-weights AI models, known as Nemotron.

Florent Delgrange won the Best Blue Sky Paper Award at AAMAS 2026 for his work Foundation World Models for Agents that Learn, Verify, and Adapt Reliably Beyond Static Environments . We caught up with him to find out more about his vision for agent learning. What is the topic of your Blue Sky Ideas paper and why is it an interesting area for study? My Blue Sky Ideas paper asks a simple but difficult question: how can an autonomous agent keep learning as its world changes without quietly losing the guarantees that made its behavior trustworthy? Reinforcement learning and formal methods address complementary parts of this problem.

The 35th International Joint Conference on Artificial Intelligence and the 29th European Conference on Artificial Intelligence (IJACI-ECAI 2026) will be held from 15-21 August, in Bremen, Germany. The conference will feature workshops and tutorials, keynote and invited talks, technical presentations, posters, diversity and inclusion event, outreach, and more. Experts from research, practice, public institutions and civil society discuss how AI is changing key areas of everyday life in moderated panel discussions. The AI Lounges will be held in German. The tutorials will also take place from 15-17 August.

Existing pretrained models for 3D mesh generation often suffer from data biases and produce low-quality results, while global reinforcement learning (RL) methods rely on object-level rewards that struggle to capture local structure details. To address these challenges, we present Mesh-RFT, a novel fine-grained reinforcement finetuning framework that employs Masked Direct Preference Optimization (M-DPO) to enable localized refinement via quality-aware face masking. To facilitate efficient quality evaluation, we introduce an objective topology-aware scoring system to evaluate geometric integrity and topological regularity at both object and face levels through two metrics: Boundary Edge Ratio (BER) and Topology Score (TS).

We introduce SLED, an alternative approach to speech language modeling by encoding speech waveforms into sequences of continuous latent representations and modeling them autoregressively using an energy distance objective. The energy distance offers an analytical measure of the distributional gap by contrasting simulated and target samples, enabling efficient training to capture the underlying continuous autoregressive distribution. By bypassing reliance on residual vector quantization, SLED avoids discretization errors and eliminates the need for the complicated hierarchical architectures common in existing speech language models.