In February 1953, two men walked into a pub in Cambridge and announced they had found the secret of life. It was not an idle boast. One was James Watson, an American biologist from the Cavendish laboratory; the other was his British research partner, Francis Crick. The full Promethean power of their achievement would slowly emerge over decades of research by fellow geneticists. It also opened a Pandora's Box of controversial scientific and ethical issues - including human cloning, designer babies and Frankenstein foods.

This post contains a list of the AI-related seminars that are scheduled to take place between 2 September and 31 October 2025. All events detailed here are free and open for anyone to attend virtually. I know it when I see it: Creativity with Vibe Speaker: Jianbo Shi (University of Pennsylvania) Organised by: University of Michigan Zoom link is here. AI and mathematics Speaker: Gabriel Peyré (École Normale Supérieure) Organised by: EPFL Zoom link is here. Somekone – Teaching about AI with an explainable social media simulator Speakers: Henriikka Vartiainen and Matti Tedre (University of Eastern Finland) Organised by: Raspberry PI Sign up here to join.

This post contains a list of the AI-related seminars that are scheduled to take place between 19 August and 30 September 2025. All events detailed here are free and open for anyone to attend virtually. La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching Speakers: Kieran Didi (PhD student, Oxford) & Tomas Geffner, PhD (NVIDIA Research) Organised by: ML Protein Engineering Sign up to the mailing list for instructions on how to join (scroll to the end of the page). Somekone – Teaching about AI with an explainable social media simulator Speakers: Henriikka Vartiainen and Matti Tedre (University of Eastern Finland) Organised by: Raspberry PI Sign up here to join. Title to be confirmed Speaker: Oscar Leong (UCLA) Organised by: University of Minnesota Check the website nearer the time for Zoom registration details.

Vaccine hesitancy threatens public health, leading to delayed or rejected vaccines. Social media is a vital source for understanding public concerns, and traditional methods like topic modelling often struggle to capture nuanced opinions. Though trained for query answering, large Language Models (LLMs) often miss current events and community concerns. Additionally, hallucinations in LLMs can compromise public health communication. To address these limitations, we developed a tool (VaxPulse Query Corner) using the Retrieval Augmented Generation technique. It addresses complex queries about public vaccine concerns on various online platforms, aiding public health administrators and stakeholders in understanding public concerns and implementing targeted interventions to boost vaccine confidence. Analysing 35,103 Shingrix social media posts, it achieved answer faithfulness (0.96) and relevance (0.94).

Fox News anchor Bret Baier has the latest on the Murdoch Children's Research Institute's partnership with the Gladstone Institutes for the'Decoding Broken Hearts' initiative on'Special Report.' Australia's Murdoch Children's Research Institute is helping scientists use stem cell medicine and artificial intelligence to develop precision therapies for pediatric heart disease, the leading cause of death and disability in children. Around 260,000 children die from heart disease around the world each year. In the U.S., a child is born with a heart defect every 15 minutes. "We're really interested in understanding how kids develop heart disease and where we can interfere to stop it progressing," Murdoch Children's Research Institute (MCRI) Heart Disease Group Leader David Elliott said.

This post contains a list of the AI-related seminars that are scheduled to take place between 3 March and 30 April 2025. All events detailed here are free and open for anyone to attend virtually. Pareto sensitivity, most-changing sub-fronts, and optimal knee solutions Speaker: Luis Nunes Vicente (Lehigh University) Organised by: Association of European Operational Research Societies To receive the seminar link, sign up to the mailing list. Title to be confirmed Speaker: Maximilian Nickel (Meta AI) Organised by: Vanderbilt University Check the Google group for Zoom instructions. Unsupervised Discovery of Interpretable Structure in Complex Systems Speaker: Mark Hamilton (MIT/Microsoft) Organised by: EPFL Zoom link is here.

Robotic catching has traditionally focused on single-handed systems, which are limited in their ability to handle larger or more complex objects. In contrast, bimanual catching offers significant potential for improved dexterity and object handling but introduces new challenges in coordination and control. In this paper, we propose a novel framework for learning dexterous bimanual catching skills using Heterogeneous-Agent Reinforcement Learning (HARL). Our approach introduces an adversarial reward scheme, where a throw agent increases the difficulty of throws-adjusting speed-while a catch agent learns to coordinate both hands to catch objects under these evolving conditions. We evaluate the framework in simulated environments using 15 different objects, demonstrating robustness and versatility in handling diverse objects. Our method achieved approximately a 2x increase in catching reward compared to single-agent baselines across 15 diverse objects.

This post contains a list of the AI-related seminars that are scheduled to take place between 3 February and 31 March 2025. All events detailed here are free and open for anyone to attend virtually. Concept bottleneck language models for protein design Speakers: Aya Abdelsalam, PhD (Guide Labs) & Nathan Frey, PhD (Prescient Design) Organised by: ML Protein Engineering Sign up to the mailing list for instructions on how to join (scroll to the end of the page). Bridging smooth regression and mathematical optimization Speaker: Vanesa Guerrero (Universidad Carlos III de Madrid) Organised by: Association of European Operational Research Societies To receive the seminar link, sign up to the mailing list. Misinformation and Social Media as a Historical Process: Insights from the American Experience Speaker: James W. Cortada Organised by: The Digital Humanism (DIGHUM) Initiative The talk will be livestreamed on YouTube here.

Aerospace embodied intelligence aims to empower unmanned aerial vehicles (UAVs) and other aerospace platforms to achieve autonomous perception, cognition, and action, as well as egocentric active interaction with humans and the environment. The aerospace embodied world model serves as an effective means to realize the autonomous intelligence of UAVs and represents a necessary pathway toward aerospace embodied intelligence. However, existing embodied world models primarily focus on ground-level intelligent agents in indoor scenarios, while research on UAV intelligent agents remains unexplored. To address this gap, we construct the first large-scale real-world image-text pre-training dataset, AerialAgent-Ego10k, featuring urban drones from a first-person perspective. We also create a virtual image-text-pose alignment dataset, CyberAgent Ego500k, to facilitate the pre-training of the aerospace embodied world model. For the first time, we clearly define 5 downstream tasks, i.e., aerospace embodied scene awareness, spatial reasoning, navigational exploration, task planning, and motion decision, and construct corresponding instruction datasets, i.e., SkyAgent-Scene3k, SkyAgent-Reason3k, SkyAgent-Nav3k and SkyAgent-Plan3k, and SkyAgent-Act3k, for fine-tuning the aerospace embodiment world model. Simultaneously, we develop SkyAgentEval, the downstream task evaluation metrics based on GPT-4, to comprehensively, flexibly, and objectively assess the results, revealing the potential and limitations of 2D/3D visual language models in UAV-agent tasks. Furthermore, we integrate over 10 2D/3D visual-language models, 2 pre-training datasets, 5 finetuning datasets, more than 10 evaluation metrics, and a simulator into the benchmark suite, i.e., AeroVerse, which will be released to the community to promote exploration and development of aerospace embodied intelligence.

[PhD thesis of FCP.] Nowadays, genetics studies large amounts of very diverse variables. Mathematical statistics has evolved in parallel to its applications, with much recent interest high-dimensional settings. In the genetics of human common disease, a number of relevant problems can be formulated as tests of independence. We show how defining adequate premetric structures on the support spaces of the genetic data allows for novel approaches to such testing. This yields a solid theoretical framework, which reflects the underlying biology, and allows for computationally-efficient implementations. For each problem, we provide mathematical results, simulations and the application to real data.