Introducing a new, unifying DNA sequence model that advances regulatory variant-effect prediction and promises to shed new light on genome function — now available via API.

We’re introducing an efficient, on-device robotics model with general-purpose dexterity and fast task adaptation.

Explore the latest Gemini 2.5 model updates with enhanced performance and accuracy: Gemini 2.5 Pro now stable, Flash generally available, and the new Flash-Lite in preview.

Gemini 2.5 Flash and Pro are now generally available, and we’re introducing 2.5 Flash-Lite, our most cost-efficient and fastest 2.5 model yet.

We partnered with Darren Aronofsky, Eliza McNitt and a team of more than 200 people to make a film using Veo and live-action filmmaking.

We’re launching Weather Lab, featuring our experimental cyclone predictions, and we’re partnering with the U.S. National Hurricane Center to support their forecasts and warnings this cyclone season.

Gemini 2.5 has new capabilities in AI-powered audio dialog and generation.

Introducing Veo 3 and Imagen 4, and a new tool for filmmaking called Flow.

We’re extending Gemini to become a world model that can make plans and imagine new experiences by simulating aspects of the world.

Gemma 3n is a cutting-edge open model designed for fast, multimodal AI on devices, featuring optimized performance, unique flexibility with a 2-in-1 model, and expanded multimodal understanding with audio, empowering developers to build live, interactive applications and sophisticated audio-centric experiences.

Gemini 2.5 Pro continues to be loved by developers as the best model for coding, and 2.5 Flash is getting even better with a new update. We’re bringing new capabilities to our models, including Deep Think, an experimental enhanced reasoning mode for 2.5 Pro.

Learn about the new SynthID Detector portal we announced at I/O to help people understand how the content they see online was generated.

We’ve made Gemini 2.5 our most secure model family to date.

New AI agent evolves algorithms for math and practical applications in computing by combining the creativity of large language models with automated evaluators

We’ve seen developers doing amazing things with Gemini 2.5 Pro, so we decided to release an updated version a couple of weeks early to get into developers hands sooner.

Our updated version of Gemini 2.5 Pro Preview has improved capabilities for coding.

Helping music professionals explore the potential of generative AI

Gemini 2.5 Flash is our first fully hybrid reasoning model, giving developers the ability to turn thinking on or off.

Transform text-based prompts into high-resolution eight-second videos in Gemini Advanced and use Whisk Animate to turn images into eight-second animated clips.

DolphinGemma, a large language model developed by Google, is helping scientists study how dolphins communicate — and hopefully find out what they're saying, too.

We’re exploring the frontiers of AGI, prioritizing technical safety, proactive risk assessment, and collaboration with the AI community.

Our framework enables cybersecurity experts to identify which defenses are necessary—and how to prioritize them

Gemini 2.5 is our most intelligent AI model, now with thinking built in.

Introducing Gemini Robotics and Gemini Robotics-ER, AI models designed for robots to understand, act and react to the physical world.

Native image output is available in Gemini 2.0 Flash for developers to experiment with in Google AI Studio and the Gemini API.

The most capable model you can run on a single GPU or TPU.

Gemini 2.0 Flash-Lite is now generally available in the Gemini API for production use in Google AI Studio and for enterprise customers on Vertex AI

We’re announcing new updates to Gemini 2.0 Flash, plus introducing Gemini 2.0 Flash-Lite and Gemini 2.0 Pro Experimental.

Our next iteration of the FSF sets out stronger security protocols on the path to AGI

Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and avoid hallucinations

We’re rolling out a new, state-of-the-art video model, Veo 2, and updates to Imagen 3. Plus, check out our new experiment, Whisk.

Today, we’re announcing Gemini 2.0, our most capable multimodal AI model yet.

Advancing adaptive AI agents, empowering 3D scene creation, and innovating LLM training for a smarter, safer future

New AI model advances the prediction of weather uncertainties and risks, delivering faster, more accurate forecasts up to 15 days ahead

Generating unlimited diverse training environments for future general agents

Our new AI system accurately identifies errors inside quantum computers, helping to make this new technology more reliable.

The AI Science Forum highlights AI's present and potential role in revolutionizing scientific discovery and solving global challenges, emphasizing collaboration between the scientific community, policymakers, and industry leaders.

Our pioneering speech generation technologies are helping people around the world interact with more natural, conversational and intuitive digital assistants and AI tools.

Our latest AI music technologies are now available in MusicFX DJ, Music AI Sandbox and YouTube Shorts

The award recognizes their work developing AlphaFold, a groundbreaking AI system that predicts the 3D structure of proteins from their amino acid sequences.

Our AI method has accelerated and optimized chip design, and its superhuman chip layouts are used in hardware around the world.

We’re releasing two updated production-ready Gemini models

New video generation technology in YouTube Shorts will help millions of people realize their creative vision

Two new AI systems, ALOHA Unleashed and DemoStart, help robots learn to perform complex tasks that require dexterous movement

New AI system designs proteins that successfully bind to target molecules, with potential for advancing drug design, disease understanding and more.

Using deep learning to solve fundamental problems in computational quantum chemistry and explore how matter interacts with light

New research analyzes the misuse of multimodal generative AI today, in order to help build safer and more responsible technologies.

Announcing a comprehensive, open suite of sparse autoencoders for language model interpretability.

Breakthrough models AlphaProof and AlphaGeometry 2 solve advanced reasoning problems in mathematics

Exploring AGI, the challenges of scaling and the future of multimodal generative AI

Video-to-audio research uses video pixels and text prompts to generate rich soundtracks

How summits in Seoul, France and beyond can galvanize international cooperation on frontier AI safety

Our approach to analyzing and mitigating future risks posed by advanced AI models

We’re introducing a series of updates across the Gemini family of models, including the new 1.5 Flash, our lightweight model for speed and efficiency, and Project Astra, our vision for the future of AI assistants.

We’re introducing Veo, our most capable model for generating high-definition video, and Imagen 3, our highest quality text-to-image model. We’re also sharing new demo recordings created with our Music AI Sandbox.

Announcing our novel watermarking method for AI-generated text and video, and how we’re bringing SynthID to key Google products

Introducing a new AI model developed by Google DeepMind and Isomorphic Labs.

Developing next-gen AI agents, exploring new modalities, and pioneering foundational learning

Exploring the promise and risks of a future with more capable AI

As part of our multi-year collaboration with Liverpool FC, we develop a full AI system that can advise coaches on corner kicks

Introducing SIMA, a Scalable Instructable Multiworld Agent

Gemma is built for responsible AI development from the same research and technology used to create Gemini models.

The model delivers dramatically enhanced performance, with a breakthrough in long-context understanding across modalities.

We're bringing Gemini to more Google products

Advancing AI reasoning in mathematics

Introducing AutoRT, SARA-RT, and RT-Trajectory

In a series of experiments published in Nature Communications, we found evidence that human judgments are indeed systematically influenced by adversarial perturbations.

This has been a year of incredible progress in the field of Artificial Intelligence (AI) research and its practical applications.

In a paper published in Nature, we introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearch works by pairing a pre-trained LLM, whose goal is to provide creative solutions in the form of computer code, with an automated “evaluator”, which guards against hallucinations and incorrect ideas.

The Neural Information Processing Systems (NeurIPS) is the largest artificial intelligence (AI) conference in the world. NeurIPS 2023 will be taking place December 10-16 in New Orleans, USA.Teams from across Google DeepMind are presenting more than 150 papers at the main conference and workshops.

Making AI more helpful for everyone

We share the discovery of 2.2 million new crystals – equivalent to nearly 800 years’ worth of knowledge. We introduce Graph Networks for Materials Exploration (GNoME), our new deep learning tool that dramatically increases the speed and efficiency of discovery by predicting the stability of new materials.

Announcing our most advanced music generation model and two new AI experiments, designed to open a new playground for creativity

Experience AI's course and resources are expanding on a global scale

We introduce GraphCast, a state-of-the-art AI model able to make medium-range weather forecasts with unprecedented accuracy

Progress update: Our latest AlphaFold model shows significantly improved accuracy and expands coverage beyond proteins to other biological molecules, including ligands.

Introducing a context-based framework for comprehensively evaluating the social and ethical risks of AI systems

Robots are great specialists, but poor generalists. Typically, you have to train a model for each task, robot, and environment. Changing a single variable often requires starting from scratch. But what if we could combine the knowledge across robotics and create a way to train a general-purpose robot?

New AI tool classifies the effects of 71 million ‘missense’ mutations.

New tool helps watermark and identify synthetic images created by Imagen

Robotic Transformer 2 (RT-2) is a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowledge into generalised instructions for robotic control.

AI is a powerful technology that will transform our future, so how can we best apply it to help combat climate change and find sustainable solutions?

Exploring AI safety, adaptability, and efficiency for the real world

We’ve published our joint paper with Google Research in Nature Medicine, which proposes CoDoC (Complementarity-driven Deferral-to-Clinical Workflow), an AI system that learns when to rely on predictive AI tools or defer to a clinician for the most accurate interpretation of medical images.

New white paper investigates models and functions of international institutions that could help manage opportunities and mitigate risks of advanced AI.

Robots are quickly becoming part of our everyday lives, but they’re often only programmed to perform specific tasks well. While harnessing recent advances in AI could lead to robots that could help in many more ways, progress in building general-purpose robots is slower in part because of the time needed to collect real-world training data. Our latest paper introduces a self-improving AI agent for robotics, RoboCat, that learns to perform a variety of tasks across different arms, and then self-generates new training data to improve its technique.

It’s all about using our technology and research to help enrich people’s lives. Like YouTube — and its mission to give everyone a voice and show them the world.

Google Cloud empowers organizations to digitally transform themselves into smarter businesses. It offers cloud computing, data analytics, and the latest artificial intelligence (AI) and machine learning tools.

How MuZero, AlphaZero, and AlphaDev are optimizing the computing ecosystem that powers our world of devices.

New algorithms will transform the foundations of computing

New research proposes a framework for evaluating general-purpose models against novel threats

Next week marks the start of the 11th International Conference on Learning Representations (ICLR), taking place 1-5 May in Kigali, Rwanda. This will be the first major artificial intelligence (AI) conference to be hosted in Africa and the first in-person event since the start of the pandemic. Researchers from around the world will gather to share their cutting-edge work in deep learning spanning the fields of AI, statistics and data science, and applications including machine vision, gaming and robotics. We’re proud to support the conference as a Diamond sponsor and DEI champion.

Drawing from philosophy to identify fair principles for ethical AI...

DeepMind and the Brain team from Google Research will join forces to accelerate progress towards a world in which AI helps solve the biggest challenges facing humanity.

Solving novel problems and setting a new milestone in competitive programming.

Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve as a sandbox for modelling and investigating interaction and communication – and we can learn a lot from playing them. In our recent paper, published today in Nature Communications, we show how artificial agents can use communication to better cooperate in the board game Diplomacy, a vibrant domain in artificial intelligence (AI) research, known for its focus on alliance building.

Game-playing artificial intelligence (AI) systems have advanced to a new frontier.

NeurIPS is the world’s largest conference in artificial intelligence (AI) and machine learning (ML), and we’re proud to support the event as Diamond sponsors, helping foster the exchange of research advances in the AI and ML community. Teams from across DeepMind are presenting 47 papers, including 35 external collaborations in virtual panels and poster sessions.

Most artificial intelligence (AI) researchers now believe that writing computer code which can capture the nuances of situated interactions is impossible. Alternatively, modern machine learning (ML) researchers have focused on learning about these types of interactions from data. To explore these learning-based approaches and quickly build agents that can make sense of human instructions and safely perform actions in open-ended conditions, we created a research framework within a video game environment.Today, we’re publishing a paper [INSERT LINK] and collection of videos, showing our early steps in building video game AIs that can understand fuzzy human concepts – and therefore, can begin to interact with people on their own terms.

Learning how to build upon knowledge by tapping 30 years of computer vision research