Together with @GoogleResearch, we’ve developed AI technologies which can monitor endangered species, protect forests, and listen to birds around the world. Here’s how. 🌱🧵

Our Lyria RealTime API on @GoogleAIStudio helps developers build apps for people to interactively create and perform instrumental music. Try Space DJ now and learn more → goo.gle/lyria-space-dj

We built a web app that lets you fly a spaceship through a 3D constellation of music - powered by our Lyria RealTime model. 🎶 Space DJ is an interactive visualization where every star represents a different music genre. As you explore, your path is translated into prompts for the API, creating a continuously evolving soundtrack. ↓

Really happy to share our new paper on using AlphaEvolve for mathematical exploration at scale, written with Javier Gómez-Serrano, Terence Tao, and @GoogleDeepMind's Bogdan Georgiev. We tested it on 67 problems and documented all our successes and failures. 🧵

We’re excited to share these AI tools with researchers, nonprofits and intergovernmental agencies, in the hope that we can help preserve the biosphere for future generations of plants, animals, and people. Find out more → goo.gle/4hNIxr8

We recently released Perch 2.0, an upgraded AI to identify animal species using bioacoustics. 🐦 Our improved model is trained on 15,000 species, is state-of-the-art for bird identification, and can also learn to identify sounds it has never heard before - like whales and dolphins - from just a few examples.

To conserve the planet's endangered species, we would have to identify and locate more than 2.2 million types of animals, plants and fungi. 🌿 That’s why we’re developing a new AI-powered approach for inferring species range maps at scale, with the potential to cover more types across more of the world. → goo.gle/3XdXRnk

Forests are important hubs of biodiversity for the world, but we’re losing them at an alarming rate. 🌲 In partnership with @WorldResources, we uncovered the underlying drivers of forest loss around the world. Today, we’re releasing a model and dataset for predicting tropical deforestation risk. → goo.gle/3XjlBGB

Excited to share our new paper, "DataRater: Meta-Learned Dataset Curation"! We explore a fundamental question: How can we *automatically* learn which data is most valuable for training foundation models? Paper: arxiv.org/pdf/2505.17895 to appear @NeurIPSConf Thread 👇

Continuing our IMO-gold journey, I’m delighted to share our #EMNLP2025 paper “Towards Robust Mathematical Reasoning”, which tells some of the key stories behind the success of our advanced Gemini #DeepThink at this year IMO. Finding the right north-star metrics was highly critical for our IMO effort and we did it with #IMOBench, a suite of advanced reasoning benchmarks for foundation models. More importantly, we encourage the community to go beyond short answers and showed that automatic grading of long-form answers is promising! Read on to see our project page, paper, and datasets in the thread 🙂

Thrilled to share our new #NeurIPS2025 paper done at @GoogleDeepMind, Plasticity as the Mirror of Empowerment We prove every agent faces a trade-off between its capacity to adapt (plasticity) and its capacity to steer (empowerment) Paper: david-abel.github.io/plastic… 🧵🧵🧵👇

That’s a wrap on our first #FlowSessions! We loved partnering with these artists for six weeks of mentorship, education, and building with Flow. Stay tuned for exclusive artist spotlights and examples of their work. Want to join the next chapter? Show us your work and tag us!

Sharing some work from my amazing PAIR teammates @GoogleDeepMind: Lumi lets you read smarter, not harder - using Gemini 2.5 to annotate arXiv papers with summaries, references, and inline Q&A medium.com/p/6a1a8210ccc7

I am excited to share a work we did in the Discovery team at @GoogleDeepMind using RL and generative models to discover creative chess puzzles 🔊♟️♟️ #neurips2025 🎨While strong chess players intuitively recognize the beauty of a position, articulating the precise elements that constitute creativity remains elusive. To address this, we pre-trained generative models on public datasets and then applied reinforcement learning, using novel rewards designed for uniqueness, counter-intuitiveness, realism, and novelty. This approach doubled the number of novel chess puzzles compared to the original training data, while successfully maintaining aesthetic diversity. Three distinguished experts—International Master of chess compositions Amatzia Avni (author of "Creative Chess"), Grandmaster Jonathan Levitt @JonathanLevitt7 (author of "Secrets of Spectacular Chess"), and Grandmaster Matthew Sadler @gmmds (author of "Game Changer")—evaluated and selected the puzzles they found most compelling. Their preference was for puzzles exhibiting original, paradoxical, surprising, and naturally occurring positions, with particular emphasis on those that integrated aesthetic themes in innovative ways and demonstrated exceptional over-the-board vision. 🧩Try to solve the puzzles @chesscom: chess.com/c/2wCTN7Uv2

We are only at the beginning of understanding everything AI can do. By empowering world-leading mathematicians, we could open up new pathways of research, advance human knowledge and move towards more breakthroughs across the scientific disciplines. → goo.gle/4qz2aqS

With funding from @Googleorg, partners will gain access to our state-of-the-art technologies, including: 🔹Gemini Deep Think, our enhanced reasoning model. 🔹AlphaEvolve, our agent to help discover new algorithms. 🔹AlphaProof, able to solve advanced reasoning problems in maths.

Together with @Googleorg, we’re introducing the AI for Math initiative, bringing together five prestigious research institutions pioneering the use of AI in mathematics. ⤵️

Today in @Nature, we published a breakthrough demonstration of verifiable quantum advantage using a measurement known as out-of-time-order correlator (OTOC), or Quantum Echoes. Performed on our Willow chip, it paves a path toward real-world applications → goo.gle/3Jqaqst

If you want to learn AI from the experts, keep reading. 💡 Together with @UCL, we made a free AI Research Foundations curriculum – available now on Google Skills. With lessons from a Gemini Lead like @OriolVinyalsML, you'll explore how to code better, fine-tune an AI model and more. → skills.google/collections/de…

Scheduling virtual machines (VMs) is like a puzzle game with disappearing pieces. Here we present LAVA, an AI-based scheduling algorithm that continuously re-predicts & adapts to the lifetimes of VMs to optimize resource efficiency in cloud data centers. goo.gle/4oshML2