We made it to the cover of Nature Machine Intelligence Nature Machine Intelligence ! Congrats Rodrigo Bonazzola Prof Alejandro Frangi FREng and team! If you are interested in imaging genetics and how to discover new phenotype-genotype associations for anatomy, check it out: nature.com/natmachintell/ 👇

Our March editorial, about the longstanding and evolving connections between neuroscience and AI research nature.com/articles/s4225…

📢Our March issue is now live, and it’s a special one, including a Focus that highlights the state of the art, challenges, and opportunities in the development and use of digital twins across different domains. 👉go.nature.com/4anUL4E 🧵1/11

Very happy to share this work testing a widespread assumption in chemical AI and showing that invalid SMILES are a feature, not a bug: nature.com/articles/s4225…

New paper out today in Nature Machine Intelligence, where we show robust neural to speech decoding across 48 patients. nature.com/articles/s4225…

Our method for molecular linker design with diffusion models (DiffLinker) got published in Nature Machine Intelligence 🥳 nature.com/articles/s4225… Thanks a lot to our amazing coauthors Hannes Stärk Clément Vignac Arne Schneuing Víctor Garcia Satorras Pascal Frossard Max Welling Michael Bronstein Bruno Correia

Published in Nature Machine Intelligence today, our new article explores the trade-offs of personalised alignment in large language models ⚖️ Personalisation has potential to democratise decisions over how LLMs behave, but brings its own set of risks... nature.com/articles/s4225…

⚡️New paper in Nature Machine Intelligence⚡️ Embodied AI is the future, but are our algorithms ready for it? With MaxDiff RL, we reveal how continuity of experience breaks the performance of RL algorithms. Continuity is a fact of embodied experience, introducing correlations between data

ChemCrow is out today in Nature Machine Intelligence! ChemCrow is an agent that uses chem tools and a cloud-based robotic lab for open-ended chem tasks. It’s been a journey to get to publication and I’d like to share some history about it. It started back in 2022. 1/8

This is the end of the world as we know it, if this is reproducible! The new era of functional modeling has begun. I took a transcription factor with an unknown structure and folded it with its recognition sequence embedded in longer DNA. AlphaFold3 accurately positioned the

Great questions about AI and empathy in this short piece: People cannot experience love from an LLM unless they act on the supposition that LLMs can love. Because LLMs cannot love, the experience of their love is premised on self-deception. nature.com/articles/s4225…

⚡️genQC made it to Nature Machine Intelligence ⚡️ We use the full power and flexibility of diffusion models to contribute to the quantum circuit synthesis field! Excited with all the upcoming applications🥳 Short summary by Universität Innsbruck @[email protected] : tinyurl.com/2s3wdnbn ⬇️⬇️ more info ⬇️⬇️

More than a year after the preprint, I’m excited to have the first LIAC at EPFL study featured on the EPFL landing page - out in Nature Machine Intelligence! We present how LLM agents can be augmented with chemistry tools and demonstrate some of the few first successful syntheses — from

📢Our May issue is now live, and it includes a Perspective on computational frameworks for semiconductor discovery, a database for structure-based drug discovery, an algorithm to uncover laws of skill acquisition -- and much more! Check it out! nature.com/natcomputsci/v…

Great to see our personalised LLMs article in this Nature Machine Intelligence editorial. Increased empathy exemplifies 2nd-order effects of personalised alignment...may seem preferable in the short-term but has long-term consequences for healthy human-AI interaction nature.com/articles/s4225…

This year may see big advances in solving longstanding robotics challenges with generative AI - or are expectations too high? We discuss various viewpoints in our June editorial. nature.com/articles/s4225…

I'm thrilled to announce that our paper has been published in Nature Machine Intelligence Nature Machine Intelligence today! To encourage research on the natural and agile movement of quadrupedal robots, we've open-sourced our code and data. Check out our project page: tencent-roboticsx.github.io/lifelike-agili…

New (short) paper by Silvia Milano (Silvia Milano) and me: "Advanced AI assistants that act on our behalf may not be ethically or legally feasible", in Nature Machine Intelligence (Nature Machine Intelligence) #aiethics doi.org/10.1038/s42256… Munich Center for Machine Learning Universität München @aiatlmu

So pleased to have been able to write a little commentary piece with my advisor Xue-Xin Wei for Nature Machine Intelligence! It's about this great work by James Gornet and Matt Thomson taking a look at how cognitive maps can arise just from predicting visual observations: nature.com/articles/s4225…