Research
349 posts
SynthID Bio: Watermarking methods for synthetic biology
SynthID Bio is a family of watermarking methods developed specifically for synthetic biology to strengthen biosecurity and scientific integrity.
Advancing confidential AI with secure memory
We're bringing on-device privacy to cloud-scale memory. Learn how Private AI Compute's new persistent memory layer protects your data across devices.
AlphaGenome Atlas: Molecular predictions for 9 Billion human DNA variants
Explore AlphaGenome Atlas, a catalogue predicting the molecular effects and AVI scores for 9 billion single-nucleotide variants across the human genome.
Piloting the world's first double-blind AI evaluations
Building trust in proprietary model benchmarks using cryptographically secure environments
Exploring new frontiers of AI and games research
Google DeepMind partners with game developers to build generalist agents like SIMA 2 and unlock breakthrough gameplay experiences across persistent worlds.
Putting sign language AI into users’ hands
Introducing sign-language-to-text (SL2T), our breakthrough model powering new sign language features for Deaf and hard of hearing users.
AI model achieves breakthrough in forecasting cyclones
WeatherNext enables accurate cyclone forecasts that can give an extra day of warning. Now we are open sourcing the model.
Gemini Robotics 2 brings whole body intelligence to robots
From feet to fingertips — we are teaching robots intelligent whole-body control, fine dexterity, and teamwork to complete a broad range of complex tasks.
Introducing Gemini 3.5 Flash Cyber
Google introduces Gemini 3.5 Flash Cyber to help defenders find, validate, and patch software vulnerabilities quickly and efficiently.
Google DeepMind and Isomorphic Labs approach to bioresilience
Google DeepMind and Isomorphic Labs approach to bioresilience, using AI models to support prevention, detection and response.
AI in Indian Education: Atal Innovation Mission and Google launch ATL Saathi
Atal Innovation Mission launches ATL Saathi, a Gemini powered AI assistant empowering India's educators to nurture the next generation of innovators.
Securing internal systems against increasingly capable and imperfectly aligned AI
Discover our AI Control Roadmap: a defense-in-depth system to securely manage advanced, potentially misaligned AI agents.
Unlocking UK house-building with AI-accelerated planning
Google DeepMind is working alongside the UK government to co-develop an AI-powered prototype to help cut application decision times by 50%.
Google DeepMind and partners announce multi-agent safety research funding call.
Google DeepMind and partners are announcing a new technical research funding call of up to $10M for researchers worldwide to strengthen multi-agent safety.
Gemini’s guided learning: results from a randomized controlled trial in Sierra Leone
Google DeepMind shares results from a randomized controlled trial in Sierra Leone, measuring the impact of AI in education on student learning and engagement.
Google DeepMind & Singapore: National AI partnership
Google DeepMind and Singapore partner to apply frontier AI to address challenges across health, education, sustainability and more through the National Partn…
Co-Scientist: A multi-agent AI partner to accelerate research
Introducing Co-Scientist, a multi-agent AI partner built with Gemini to help researchers generate and evolve hypotheses to accelerate scientific breakthroughs.
AI breakthrough: WeatherNext predicts Hurricane Melissa
Discover how our WeatherNext AI model helps the National Hurricane Center predict Hurricane Melissa's Category 5 landfall in Jamaica
Co-Scientist
Breakthroughs in liver disease research
Co-Scientist
Accelerating cellular aging research
Co-Scientist
Fast-tracking infectious disease research
Co-Scientist
Untangling the mysteries of aging
Co-Scientist
Finding new treatments for liver fibrosis
Co-Scientist
Driving creative collaboration in research
Shaping the future of AI interaction by reimagining the mouse pointer
Google DeepMind is transforming the mouse pointer into a context-aware AI partner. Move beyond the friction of traditional prompting with intuitive AI collab…
AlphaEvolve: Gemini-powered coding agent scaling impact across fields
Discover how AlphaEvolve optimizes algorithms for genomics, quantum physics, global infrastructure, and more to accelerate scientific progress and solve real…
AI co-clinician: researching the path toward AI-augmented care
Google DeepMind is researching the path toward an AI co-clinician that could work under physician authority to assist doctors and patients, enabling new mode…
Google DeepMind and Korea Partner to Accelerate Scientific Discovery
Google DeepMind partners with Korea's MSIT to establish an AI Campus to help accelerate scientific breakthroughs, support local talent, and advance AI safety…
Decoupled DiLoCo: Resilient, Distributed AI Training at Scale
Google’s new distributed architecture keeps AI training runs on track across distant data centers, with exceptional efficiency – even when hardware fails.
Google DeepMind partners with global consultancies to accelerate enterprise AI adoption.
Google DeepMind is partnering with leading consultancies to bridge the AI adoption gap and drive agentic transformation with frontier models and expert resea…
Gemini Robotics ER 1.6: Enhanced Embodied Reasoning
Gemini Robotics ER 1.6 upgrades spatial reasoning and multi-view understanding, unlocking new capabilities like instrument reading for autonomous robots.
Protecting People from Harmful Manipulation
Google DeepMind releases new findings and an evaluation framework to measure AI's potential for harmful manipulation in areas like finance and health, with t…
AlphaGo at 10: How AI Innovation Is Paving the Path to AGI
Ten years since AlphaGo, we explore how its search and learning methods are catalyzing scientific discovery and paving a path to AGI.
Google DeepMind Partnerships in India: scaling AI in science and education
Google DeepMind announces new AI partnerships in India to advance scientific research, empower students with interactive Gemini-powered learning, and support…
Gemini Deep Think: Redefining the Future of Scientific Research
Gemini Deep Think is accelerating discovery in maths, physics, and computer science by acting as a powerful scientific companion for researchers.
D4RT: Unified, Fast 4D Scene Reconstruction & Tracking
Meet D4RT, a unified AI model for 4D scene reconstruction and tracking.
Gemma Scope 2: Helping the AI Safety Community Deepen Understanding of Complex Language Model Behavior
Announcing Gemma Scope 2, a comprehensive, open suite of interpretability tools for the entire Gemma 3 family to accelerate AI safety research.
Google DeepMind & DOE Partner on Genesis: AI for Science
Google DeepMind supports U.S. Department of Energy on Genesis: a national mission to accelerate innovation and scientific discovery.
Deepening AI Safety Research with UK AI Security Institute (AISI)
Google DeepMind and the UK AI Security Institute (AISI) strengthen collaboration through a new research partnership, focusing on critical safety research are…
Our partnership with the UK government
We're collaborating with the UK government to accelerate progress in science, education, national security and more.
FACTS Benchmark Suite: a new way to systematically evaluate LLMs factuality
The FACTS Benchmark Suite provides a systematic evaluation of Large Language Models (LLMs) factuality across three areas: Parametric, Search, and Multimodal …
How AlphaFold is helping scientists engineer more heat-tolerant crops
Scientists are using AlphaFold to strengthen a vital photosynthesis enzyme (GLYK), paving the way for more resilient, heat-tolerant crops that can adapt to a…
AlphaFold: Five Years of Impact
Explore five years of AlphaFold’s impact on biology. Learn how this Nobel Prize-winning AI is accelerating scientific discovery globally
AlphaFold Reveals a Key Protein Behind Heart Disease
Discover how scientists used AlphaFold to map the protein behind heart disease and how this breakthrough could transform treatment.
Breeding Healthier Honeybees With AlphaFold
Learn how AlphaFold is helping scientists protect honeybees and speeding up breeding programs for healthier hives.
Google DeepMind opens Singapore research lab for Asia-Pacific AI.
Google DeepMind opens a new research lab in Singapore to accelerate the development of frontier AI across the Asia-Pacific region through research, talent, a…
SIMA 2: A Gemini-Powered AI Agent for 3D Virtual Worlds
Introducing SIMA 2, the next milestone in our research creating general and helpful AI agents. By integrating the advanced capabilities of our Gemini models,…
Teaching AI to See the World More Like Humans Do
Aligning AI vision models with human knowledge, improves their robustness and ability to generalize.
Three ways Google scientists use AI to better understand nature
Discover how AI models are helping scientists better understand our biosphere, from predicting deforestation to mapping species and listening to wildlife.
Google DeepMind is bringing AI to the next generation of fusion energy
We’re announcing our research partnership with Commonwealth Fusion Systems (CFS) to bring clean, safe, limitless fusion energy closer to reality with our adv…
Introducing CodeMender: an AI agent for code security
Using advanced AI to fix critical software vulnerabilities
Gemini Robotics 1.5 brings AI agents into the physical world
We’re powering an era of physical agents — enabling robots to perceive, plan, think, use tools and act to better solve complex, multi-step tasks.
Google DeepMind strengthens the Frontier Safety Framework
Today, we’re publishing the third iteration of our Frontier Safety Framework (FSF) — our most comprehensive approach yet to identifying and mitigating severe…
Discovering new solutions to century-old problems in fluid dynamics
Our new method could help mathematicians leverage AI techniques to tackle long-standing challenges in mathematics, physics and engineering.
Gemini achieves gold-medal level at the International Collegiate Programming Contest World Finals
Gemini 2.5 Deep Think achieves breakthrough performance at the world’s most prestigious computer programming competition, demonstrating a profound leap in ab…
Using AI to perceive the universe in greater depth
Using AI to perceive the universe in greater depth
How AI is helping advance the science of bioacoustics to save endangered species
Our new Perch model helps conservationists analyze audio faster to protect endangered species, from Hawaiian honeycreepers to coral reefs.
Genie 3: A new frontier for world models
Today we are announcing Genie 3, a general purpose world model that can generate an unprecedented diversity of interactive environments. Given a text prompt,…
AlphaEarth Foundations helps map our planet in unprecedented detail
New AI model integrates petabytes of Earth observation data to generate a unified data representation that revolutionizes global mapping and monitoring
Aeneas transforms how historians connect the past
Introducing the first model for contextualizing ancient inscriptions, designed to help historians better interpret, attribute and restore fragmentary texts.
Advanced version of Gemini with Deep Think officially achieves gold-medal standard at the International Mathematical …
The International Mathematical Olympiad (“IMO”) is the world’s most prestigious competition for young mathematicians, and has been held annually since 1959. …
Exploring the context of online images with Backstory
New experimental AI tool helps people explore the context and origin of images seen online.
AlphaGenome: AI for better understanding the genome
Introducing a new, unifying DNA sequence model that advances regulatory variant-effect prediction and promises to shed new light on genome function — now ava…
Gemini Robotics On-Device brings AI to local robotic devices
We’re introducing an efficient, on-device robotics model with general-purpose dexterity and fast task adaptation.
How we're supporting better tropical cyclone prediction with AI
We’re launching Weather Lab, featuring our experimental cyclone predictions, and we’re partnering with the U.S. National Hurricane Center to support their fo…
Advancing Gemini's security safeguards
We’ve made Gemini 2.5 our most secure model family to date.
AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms
New AI agent evolves algorithms for math and practical applications in computing by combining the creativity of large language models with automated evaluators
Music AI Sandbox, now with new features and broader access
Google has long collaborated with musicians, producers, and artists in the research and development of music AI tools. Ever since launching the Magenta proje…
Building secure AGI: Evaluating emerging cyber security capabilities of advanced AI
Our framework enables cybersecurity experts to identify which defenses are necessary—and how to prioritize them
Taking a responsible path to AGI
We’re exploring the frontiers of AGI, prioritizing technical safety, proactive risk assessment, and collaboration with the AI community.
Introducing Gemini Robotics and Gemini Robotics-ER, AI models designed for robots to understand, act and react to the…
Introducing Gemini Robotics and Gemini Robotics-ER, AI models designed for robots to understand, act and react to the physical world.
Updating the Frontier Safety Framework
Our next iteration of the FSF sets out stronger security protocols on the path to AGI
FACTS Grounding: A new benchmark for evaluating the factuality of large language models
Our comprehensive benchmark and online leaderboard offer a much-needed measure of how accurately LLMs ground their responses in provided source material and …
Google DeepMind at NeurIPS 2024
Advancing adaptive AI agents, empowering 3D scene creation, and innovating LLM training for a smarter, safer future
GenCast predicts weather and the risks of extreme conditions with state-of-the-art accuracy
New AI model advances the prediction of weather uncertainties and risks, delivering faster, more accurate forecasts up to 15 days ahead
Genie 2: A large-scale foundation world model
Generating unlimited diverse training environments for future general agents
Pushing the frontiers of audio generation
Our pioneering speech generation technologies are helping people around the world interact with more natural, conversational and intuitive digital assistants…
New generative AI tools open the doors of music creation
Our latest AI music technologies are now available in MusicFX DJ, Music AI Sandbox and YouTube Shorts
Demis Hassabis & John Jumper awarded Nobel Prize in Chemistry
Co-founder and CEO of Google DeepMind and Isomorphic Labs Sir Demis Hassabis, and Google DeepMind Senior Research Scientist Dr. John Jumper were co-awarded t…
How AlphaChip transformed computer chip design
Our AI method has accelerated and optimized chip design, and its superhuman chip layouts are used in hardware around the world. AlphaChip was one of the firs…
Empowering YouTube creators with generative AI
New video generation technology in YouTube Shorts will help millions of people realize their creative vision
Our latest advances in robot dexterity
Two new AI systems, ALOHA Unleashed and DemoStart, help robots learn to perform complex tasks that require dexterous movement
AlphaProteo generates novel proteins for biology and health research
New AI system designs proteins that successfully bind to target molecules, with potential for advancing drug design, disease understanding and more.
FermiNet: Quantum physics and chemistry from first principles
In August 2024, we published the next phase of our work in Science. Our research proposes a solution to one of the most difficult challenges in computational…
Mapping the misuse of generative AI
New research analyzes the misuse of multimodal generative AI today, in order to help build safer and more responsible technologies
Gemma Scope: helping the safety community shed light on the inner workings of language models
Announcing a comprehensive, open suite of sparse autoencoders for language model interpretability.
AI achieves silver-medal standard solving International Mathematical Olympiad problems
Breakthrough models AlphaProof and AlphaGeometry 2 solve advanced reasoning problems in mathematics
Google DeepMind at ICML 2024
Teams from across Google DeepMind will present more than 80 research papers exploring AGI, the challenges of scaling and the future of multimodal generative AI.
Generating audio for video
Video-to-audio research uses video pixels and text prompts to generate rich soundtracks
Looking ahead to the AI Seoul Summit
How summits in Seoul, France and beyond can galvanize international cooperation on frontier AI safety
Introducing the Frontier Safety Framework
Our approach to analyzing and mitigating future risks posed by advanced AI models
Watermarking AI-generated text and video with SynthID
Announcing our novel watermarking method for AI-generated text and video, and how we’re bringing SynthID to key Google products
Google DeepMind at ICLR 2024
Developing next-gen AI agents, exploring new modalities, and pioneering foundational learning
The ethics of advanced AI assistants
Exploring the promise and risks of a future with more capable AI
TacticAI: an AI assistant for football tactics
As part of our multi-year collaboration with Liverpool FC, we develop a full AI system that can advise coaches on corner kicks
A generalist AI agent for 3D virtual environments
Introducing SIMA, a Scalable Instructable Multiworld Agent
AlphaGeometry: An Olympiad-level AI system for geometry
Our AI system surpasses the state-of-the-art approach for geometry problems, advancing AI reasoning in mathematics
Shaping the future of advanced robotics
AutoRT, SARA-RT, and RT-Trajectory build on our historic Robotics Transformers work to help robots make decisions faster, and better understand and navigate …
Images altered to trick machine vision can influence humans too
In a series of experiments published in Nature Communications, we found evidence that human judgments are indeed systematically influenced by adversarial per…
2023: A Year of Groundbreaking Advances in AI and Computing
This has been a year of incredible progress in the field of Artificial Intelligence (AI) research and its practical applications.
FunSearch: Making new discoveries in mathematical sciences using Large Language Models
We introduce FunSearch, a method for searching for “functions” written in computer code, and find new solutions in mathematics and computer science. FunSearc…
Google DeepMind at NeurIPS 2023
The Neural Information Processing Systems (NeurIPS) is the largest artificial intelligence (AI) conference in the world. NeurIPS 2023 will be taking place De…
Millions of new materials discovered with deep learning
We share the discovery of 2.2 million new crystals – equivalent to nearly 800 years’ worth of knowledge. We introduce Graph Networks for Materials Exploratio…
Transforming the future of music creation
Announcing our most advanced music generation model and two new AI experiments, designed to open a new playground for creativity
Empowering the next generation for an AI-enabled world
Today, Google DeepMind and the Raspberry Pi Foundation are expanding access to the Experience AI program. This comprehensive introductory course is designed …
GraphCast: AI model for faster and more accurate global weather forecasting
Our state-of-the-art model delivers 10-day weather predictions at unprecedented accuracy in under one minute
A glimpse of the next generation of AlphaFold
Progress update: Our latest AlphaFold model shows significantly improved accuracy and expands coverage beyond proteins to other biological molecules, includi…
Evaluating social and ethical risks from generative AI
Introducing a context-based framework for comprehensively evaluating the social and ethical risks of AI systems
Scaling up learning across many different robot types
Robots are great specialists, but poor generalists. Typically, you have to train a model for each task, robot, and environment. Changing a single variable of…
A catalogue of genetic mutations to help pinpoint the cause of diseases
New AI tool classifies the effects of 71 million ‘missense’ mutations Uncovering the root causes of disease is one of the greatest challenges in human geneti…
Identifying AI-generated images with SynthID
Today, in partnership with Google Cloud, we’re beta launching SynthID, a new tool for watermarking and identifying AI-generated images. It’s being released t…
RT-2: New model translates vision and language into action
Introducing Robotic Transformer 2 (RT-2), a novel vision-language-action (VLA) model that learns from both web and robotics data, and translates this knowled…
Using AI to fight climate change
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? The eff…
Google DeepMind’s latest research at ICML 2023
Google DeepMind researchers are presenting more than 80 new papers at the 40th International Conference on Machine Learning (ICML 2023), taking place 23-29 J…
Developing reliable AI tools for healthcare
We’ve published our joint paper with Google Research in Nature Medicine, which proposes CoDoC (Complementarity-driven Deferral-to-Clinical Workflow), an AI s…
Exploring institutions for global AI governance
New white paper investigates models and functions of international institutions that could help manage opportunities and mitigate risks of advanced AI. Growi…
RoboCat: A self-improving robotic agent
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…
YouTube: Enhancing the user experience
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: Driving digital transformation
Google Cloud empowers organizations to digitally transform themselves into smarter businesses. It offers cloud computing, data analytics, and the latest arti…
MuZero, AlphaZero, and AlphaDev: Optimizing computer systems
How MuZero, AlphaZero, and AlphaDev are optimizing the computing ecosystem that powers our world of devices.
AlphaDev discovers faster sorting algorithms
In our paper published today in Nature, we introduce AlphaDev, an artificial intelligence (AI) system that uses reinforcement learning to discover enhanced c…
An early warning system for novel AI risks
AI researchers already use a range of evaluation benchmarks to identify unwanted behaviours in AI systems, such as AI systems making misleading statements, b…
DeepMind’s latest research at ICLR 2023
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 f…
How can we build human values into AI?
As artificial intelligence (AI) becomes more powerful and more deeply integrated into our lives, the questions of how it is used and deployed are all the mor…
Announcing Google DeepMind
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 facin…
Competitive programming with AlphaCode
Solving novel problems and setting a new milestone in competitive programming.
AI for the board game Diplomacy
Successful communication and cooperation have been crucial for helping societies advance throughout history. The closed environments of board games can serve…
Mastering Stratego, the classic game of imperfect information
Game-playing artificial intelligence (AI) systems have advanced to a new frontier. Stratego, the classic board game that’s more complex than chess and Go, an…
DeepMind’s latest research at NeurIPS 2022
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…
Building interactive agents in video game worlds
Most artificial intelligence (AI) researchers now believe that writing computer code which can capture the nuances of situated interactions is impossible. Al…
Benchmarking the next generation of never-ending learners
Our new paper, NEVIS’22: A Stream of 100 Tasks Sampled From 30 Years of Computer Vision Research, proposes a playground to study the question of efficient kn…
Best practices for data enrichment
At DeepMind, our goal is to make sure everything we do meets the highest standards of safety and ethics, in line with our Operating Principles. One of the mo…
Stopping malaria in its tracks
When biochemist Matthew Higgins established his research group in 2006, he had malaria firmly in his sights. The mosquito-borne disease is second only to tub…
Measuring perception in AI models
Perception – the process of experiencing the world through senses – is a significant part of intelligence. And building agents with human-level perceptual un…
How undesired goals can arise with correct rewards
As we build increasingly advanced artificial intelligence (AI) systems, we want to make sure they don’t pursue undesired goals. Such behaviour in an AI agent…
Discovering novel algorithms with AlphaTensor
In our paper, published today in Nature, we introduce AlphaTensor, the first artificial intelligence (AI) system for discovering novel, efficient, and provab…
Fighting osteoporosis before it starts
Right now, medicine is too dependent on radiographic imaging techniques for diagnosing osteoporosis. It can be a debilitating disease that develops slowly ov…
Understanding the faulty proteins linked to cancer and autism
Being a structural biologist in the age of AlphaFold is like the early days of gold mining. Before this technology, everyone was doing painstaking work to fi…
Building safer dialogue agents
In our latest paper, we introduce Sparrow – a dialogue agent that’s useful and reduces the risk of unsafe and inappropriate answers. Our agent is designed to…
Solving the mystery of how an ancient bird went extinct
Could burn marks on ancient eggshells explain the disappearance of the giant flightless bird Genyornis newtoni? This ostrich-sized “thunderbird”, dubbed “the…
Targeting early-onset Parkinson’s with AI
It was a source of hard-earned satisfaction after what had often felt like an uphill battle. David Komander and his colleagues had finally published the long…
How our principles helped define AlphaFold’s release
Our Operating Principles have come to define both our commitment to prioritising widespread benefit, as well as the areas of research and applications we ref…
Maximising the impact of our breakthroughs
Colin, CBO at DeepMind, discusses collaborations with Alphabet and how we integrate ethics, accountability, and safety into everything we do.
In conversation with AI: building better language models
Our new paper, In conversation with AI: aligning language models with human values, explores a different approach, asking what successful communication betwe…
From motor control to embodied intelligence
Using human and animal motions to teach robots to dribble a ball, and simulated humanoid characters to carry boxes and play football
Advancing conservation with AI-based facial recognition of turtles
We came across Zindi – a dedicated partner with complementary goals – who are the largest community of African data scientists and host competitions that foc…
Discovering when an agent is present in a system
We want to build safe, aligned artificial general intelligence (AGI) systems that pursue the intended goals of its designers. Causal influence diagrams (CIDs…
Accelerating the race against antibiotic resistance
Most people who have access to a modern healthcare system would not consider a disease like bubonic plague to be a threat. Such bacterial infections are usua…
Advancing discovery of better drugs and medicine
With the help of AlphaFold, researchers are designing more effective drugs like never before. Karen Akinsanya is President of R&D, Therapeutics, at Schröding…
AlphaFold reveals the structure of the protein universe
Today, in partnership with EMBL’s European Bioinformatics Institute (EMBL-EBI), we’re now releasing predicted structures for nearly all catalogued proteins k…
AlphaFold transforms biology for millions around the world
Big data in biology leads to discoveries that can benefit humankind. That’s the core belief at EMBL’s European Bioinformatics Institute (EMBL-EBI), and what …
AlphaFold unlocks one of the greatest puzzles in biology
When Pietro Fontana joined the Wu Lab at Harvard Medical School and Boston Children’s Hospital in May 2019, he had before him what has been called one of the…
Creating plastic-eating enzymes that could save us from pollution
The world produces about 400 million tonnes of plastic waste each year. Much of it ends up in landfills, and a significant portion is polluting the world’s o…
The race to cure a billion people from a deadly parasitic disease
Globally, about a billion people are at risk of leishmaniasis and each year there are 50-90,000 new cases of visceral leishmaniasis, the majority in children…
Tracing the evolution of proteins back to the origin of life
Looking hundreds of millions of years into a protein’s past with AlphaFold to learn about the beginnings of life itself. Pedro Beltrao is a geneticist at ETH…
Putting the power of AlphaFold into the world’s hands
When we announced AlphaFold 2 last December, it was hailed as a solution to the 50-year old protein folding problem. Last week, we published the scientific p…
Perceiver AR: general-purpose, long-context autoregressive generation
We develop Perceiver AR, an autoregressive, modality-agnostic architecture which uses cross-attention to map long-range inputs to a small number of latents w…
DeepMind’s latest research at ICML 2022
Starting this weekend, the thirty-ninth International Conference on Machine Learning (ICML 2022) is meeting from 17-23 July, 2022 at the Baltimore Convention…
Intuitive physics learning in a deep-learning model inspired by developmental psychology
Despite significant effort, current AI systems pale in their understanding of intuitive physics, in comparison to even very young children. In the present wo…
Human-centred mechanism design with Democratic AI
In our recent paper, published in Nature Human Behaviour, we provide a proof-of-concept demonstration that deep reinforcement learning (RL) can be used to fi…
BYOL-Explore: Exploration with Bootstrapped Prediction
We present BYOL-Explore, a conceptually simple yet general approach for curiosity-driven exploration in visually-complex environments. BYOL-Explore learns a …
Unlocking High-Accuracy Differentially Private Image Classification through Scale
According to empirical evidence from prior works, utility degradation in DP-SGD becomes more severe on larger neural network models – including the ones regu…
Bridging DeepMind research with Alphabet products
Today we caught up with Gemma Jennings, a product manager on the Applied team, who led a session on vision language models at the AI Summit, one of the world…
Evaluating Multimodal Interactive Agents
In this paper, we assess the merits of these existing evaluation metrics and present a novel approach to evaluation called the Standardised Test Suite (STS).…
Dynamic language understanding: adaptation to new knowledge in parametric and semi-parametric models
To study how semi-parametric QA models and their underlying parametric language models (LMs) adapt to evolving knowledge, we construct a new large-scale data…
Kyrgyzstan to King’s Cross: the star baker cooking up code
My day can vary, it really depends on which phase of the project I'm on. Let’s say we want to add a feature to our product – my tasks could range from design…
Building a culture of pioneering responsibly
When I joined DeepMind as COO, I did so in large part because I could tell that the founders and team had the same focus on positive social impact. In fact, …
Open-sourcing MuJoCo
In October 2021, we announced that we acquired the MuJoCo physics simulator, and made it freely available for everyone to support research everywhere. We als…
From LEGO competitions to DeepMind's robotics lab
If you want to be at DeepMind, go for it. Apply, interview, and just try. You might not get it the first time but that doesn’t mean you can’t try again. I ne…
Emergent Bartering Behaviour in Multi-Agent Reinforcement Learning
In our recent paper, we explore how populations of deep reinforcement learning (deep RL) agents can learn microeconomic behaviours, such as production, consu…
A Generalist Agent
Inspired by progress in large-scale language modelling, we apply a similar approach towards building a single generalist agent beyond the realm of text outpu…
Active offline policy selection
To make RL more applicable to real-world applications like robotics, we propose using an intelligent evaluation procedure to select the policy for deployment…
Tackling multiple tasks with a single visual language model
We introduce Flamingo, a single visual language model (VLM) that sets a new state of the art in few-shot learning on a wide range of open-ended multimodal ta…
When a passion for bass and brass help build better tools
We caught up with Kevin Millikin, a software engineer on the DevTools team. He’s in Salt Lake City this week to present at PyCon US, the largest annual gathe…
DeepMind’s latest research at ICLR 2022
Beyond supporting the event as sponsors and regular workshop organisers, our research teams are presenting 29 papers, including 10 collaborations this year. …
An empirical analysis of compute-optimal large language model training
We ask the question: “What is the optimal model size and number of training tokens for a given compute budget?” To answer this question, we train models of v…
GopherCite: Teaching language models to support answers with verified quotes
Language models like Gopher can “hallucinate” facts that appear plausible but are actually fake. Those who are familiar with this problem know to do their ow…
Predicting the past with Ithaca
The birth of human writing marked the dawn of History and is crucial to our understanding of past civilisations and the world we live in today. For example, …
Learning Robust Real-Time Cultural Transmission without Human Data
In this work, we use deep reinforcement learning to generate artificial agents capable of test-time cultural transmission. Once trained, our agents can infer…
Probing Image-Language Transformers for Verb Understanding
Multimodal Image-Language transformers have achieved impressive results on a variety of tasks that rely on fine-tuning (e.g., visual question answering and i…
Accelerating fusion science through learned plasma control
Successfully controlling the nuclear fusion plasma in a tokamak with deep reinforcement learning
MuZero’s first step from research into the real world
Collaborating with YouTube to optimise video compression in the open source VP9 codec.
Red Teaming Language Models with Language Models
In our recent paper, we show that it is possible to automatically find inputs that elicit harmful text from language models by generating inputs using langua…
DeepMind: The Podcast returns for Season 2
We believe artificial intelligence (AI) is one of the most significant technologies of our age and we want to help people understand its potential and how it…
Spurious normativity enhances learning of compliance and enforcement behavior in artificial agents
In our recent paper we explore how multi-agent deep reinforcement learning can serve as a model of complex social interactions, like the formation of social …
AlphaFold: Using AI for scientific discovery
We’re excited to share DeepMind’s first significant milestone in demonstrating how artificial intelligence research can drive and accelerate new scientific d…
Simulating matter on the quantum scale with AI
Solving some of the major challenges of the 21st Century, such as producing clean electricity or developing high temperature superconductors, will require us…
Creating Interactive Agents with Imitation Learning
We show that imitation learning of human-human interactions in a simulated world, in conjunction with self-supervised learning, is sufficient to produce a mu…
Improving language models by retrieving from trillions of tokens
We explore an alternate path for improving language models: we augment transformers with retrieval over a database of text passages including web pages, book…
Language modelling at scale: Gopher, ethical considerations, and retrieval
Language, and its role in demonstrating and facilitating comprehension - or intelligence - is a fundamental part of being human. It gives people the ability …
Exploring the beauty of pure mathematics in novel ways
More than a century ago, Srinivasa Ramanujan shocked the mathematical world with his extraordinary ability to see remarkable patterns in numbers that no one …
On the Expressivity of Markov Reward
Our main results prove that while reward can express many tasks, there exist instances of each task type that no Markov reward function can capture. We then …
Unsupervised deep learning identifies semantic disentanglement in single inferotemporal face patch neurons
Our brain has an amazing ability to process visual information. We can take one glance at a complex scene, and within milliseconds be able to parse it into o…
Real-world challenges for AGI
When people picture a world with artificial general intelligence (AGI), robots are more likely to come to mind than enabling solutions to society’s most intr…
Opening up a physics simulator for robotics
When you walk, your feet make contact with the ground. When you write, your fingers make contact with the pen. Physical contacts are what makes interaction w…
Stacking our way to more general robots
Picking up a stick and balancing it atop a log or stacking a pebble on a stone may seem like simple — and quite similar — actions for a person. However, most…
Predicting gene expression with AI
When the Human Genome Project succeeded in mapping the DNA sequence of the human genome, the international research community were excited by the opportunity…
Nowcasting the next hour of rain
Our lives are dependent on the weather. At any moment in the UK, according to one study, one third of the country has talked about the weather in the past ho…
Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration
We argue that merely using curiosity for fast environment exploration or as a bonus reward for a specific task does not harness the full potential of this te…
Challenges in Detoxifying Language Models
In our paper, we focus on LMs and their propensity to generate toxic language. We study the effectiveness of different methods to mitigate LM toxicity, and t…
Building architectures that can handle the world’s data
Most architectures used by AI systems today are specialists. A 2D residual network may be a good choice for processing images, but at best it’s a loose fit f…
Generally capable agents emerge from open-ended play
In recent years, artificial intelligence agents have succeeded in a range of complex game environments. For instance, AlphaZero beat world-champion programs …
Enabling high-accuracy protein structure prediction at the proteome scale
Many novel machine learning innovations contribute to AlphaFold’s current level of accuracy. We give a high-level overview of the system below; for a technic…
Melting Pot: an evaluation suite for multi-agent reinforcement learning
Here we introduce Melting Pot, a scalable evaluation suite for multi-agent reinforcement learning. Melting Pot assesses generalisation to novel social situat…
Advancing sports analytics through AI research
Creating testing environments to help progress AI research out of the lab and into the real world is immensely challenging. Given AI’s long association with …
Game theory as an engine for large-scale data analysis
Modern AI systems approach tasks like recognising objects in images and predicting the 3D structure of proteins as a diligent student would prepare for an ex…
Data, Architecture, or Losses: What Contributes Most to Multimodal Transformer Success?
In this work, we examine what aspects of multimodal transformers – attention, losses, and pretraining data – are important in their success at multimodal pre…
MuZero: Mastering Go, chess, shogi and Atari without rules
In 2016, we introduced AlphaGo, the first artificial intelligence (AI) program to defeat humans at the ancient game of Go. Two years later, its successor - A…
Imitating Interactive Intelligence
We first create a simulated environment, the Playroom, in which virtual robots can engage in a variety of interesting interactions by moving around, manipula…
Using JAX to accelerate our research
DeepMind engineers accelerate our research by building tools, scaling up algorithms, and creating challenging virtual and physical worlds for training and te…
AlphaFold: a solution to a 50-year-old grand challenge in biology
Proteins are essential to life, supporting practically all its functions. They are large complex molecules, made up of chains of amino acids, and what a prot…
Using Unity to Help Solve Intelligence
We present our use of Unity, a widely recognised and comprehensive game engine, to create more diverse, complex, virtual simulations. We describe the concept…
Fast reinforcement learning through the composition of behaviours
Imagine if you had to learn how to chop, peel and stir all over again every time you wanted to learn a new recipe. In many machine learning systems, agents o…
Traffic prediction with advanced Graph Neural Networks
By partnering with Google, DeepMind is able to bring the benefits of AI to billions of people all over the world. From reuniting a speech-impaired user with …
Computational predictions of protein structures associated with COVID-19
The scientific community has galvanised in response to the recent COVID-19 outbreak, building on decades of basic research characterising this virus family. …
RL Unplugged: Benchmarks for Offline Reinforcement Learning
We propose a benchmark called RL Unplugged to evaluate and compare offline RL methods. RL Unplugged includes data from a diverse range of domains including g…
dm_control: Software and Tasks for Continuous Control
The dm_control software package is a collection of Python libraries and task suites for reinforcement learning agents in an articulated-body simulation. A Mu…
Acme: A new framework for distributed reinforcement learning
Acme is a framework for building readable, efficient, research-oriented RL algorithms. At its core Acme is designed to enable simple descriptions of RL agent…
Using AI to predict retinal disease progression
Vision loss among the elderly is a major healthcare issue: about one in three people have some vision-reducing disease by the age of 65. Age-related macular …
Simple Sensor Intentions for Exploration
In this paper we focus on a setting in which goal tasks are defined via simple sparse rewards, and exploration is facilitated via agent-internal auxiliary ta…
Learning to Segment Actions from Observation and Narration
We apply a generative segmental model of task structure, guided by narration, to action segmentation in video. We focus on unsupervised and weakly-supervised…
Specification gaming: the flip side of AI ingenuity
Specification gaming is a behaviour that satisfies the literal specification of an objective without achieving the intended outcome. We have all had experien…
Towards understanding glasses with graph neural networks
Under a microscope, a pane of window glass doesn’t look like a collection of orderly molecules, as a crystal would, but rather a jumble with no discernable s…
Agent57: Outperforming the human Atari benchmark
The Atari57 suite of games is a long-standing benchmark to gauge agent performance across a wide range of tasks. We’ve developed Agent57, the first deep rein…
Visual Grounding in Video for Unsupervised Word Translation
Our goal is to use visual grounding to improve unsupervised word mapping between languages. The key idea is to establish a common visual representation betwe…
A new model and dataset for long-range memory
Throughout our lives, we build up memories that are retained over a diverse array of timescales, from minutes to months to years to decades. When reading a b…
AlphaFold: Using AI for scientific discovery
In our study published in Nature, we demonstrate how artificial intelligence research can drive and accelerate new scientific discoveries. We’ve built a dedi…
Dopamine and temporal difference learning: A fruitful relationship between neuroscience and AI
Learning and motivation are driven by internal and external rewards. Many of our day-to-day behaviours are guided by predicting, or anticipating, whether a g…
Artificial Intelligence, Values and Alignment
This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects …
International evaluation of an AI system for breast cancer screening
Screening mammography aims to identify breast cancer before symptoms appear, enabling earlier therapy for more treatable disease. Despite the existence of sc…
Using WaveNet technology to reunite speech-impaired users with their original voices
As a teenager, Tim Shaw put everything he had into football practice: his dream was to join the NFL. After playing for Penn State in college, his ambitions w…
Learning human objectives by evaluating hypothetical behaviours
When we train reinforcement learning (RL) agents in the real world, we don’t want them to explore unsafe states, such as driving a mobile robot into a ditch …
From unlikely start-up to major scientific organisation: Entering our tenth year at DeepMind
Since we started DeepMind nearly 10 years ago, our mission has been to unlock answers to the world’s biggest questions by understanding and recreating intell…
Advanced machine learning helps Play Store users discover personalised apps
Over the past few years we've applied DeepMind's technology to Google products and infrastructure, with notable successes like reducing the amount of energy …
AlphaStar: Grandmaster level in StarCraft II using multi-agent reinforcement learning
AlphaStar is the first AI to reach the top league of a widely popular esport without any game restrictions. This January, a preliminary version of AlphaStar …
Restoring ancient text using deep learning: a case study on Greek epigraphy
This work presents PYTHIA, the first ancient text restoration model that recovers missing characters from a damaged text input using deep neural networks. It…
Causal Bayesian Networks: A flexible tool to enable fairer machine learning
Decisions based on machine learning (ML) are potentially advantageous over human decisions, as they do not suffer from the same subjectivity, and can be more…
DeepMind’s health team joins Google Health
Over the last three years, DeepMind has built a team to tackle some of healthcare’s most complex problems—developing AI research and mobile tools that are al…
The Podcast: Episode 8: Demis Hassabis - The interview
In this special extended episode, Hannah Fry meets Demis Hassabis, the CEO and co-founder of DeepMind.
The Podcast: Episode 7: Towards the future
AI researchers around the world are trying to create a general purpose learning system that can learn to solve a broad range of problems without being taught…
Replay in biological and artificial neural networks
Our waking and sleeping lives are punctuated by fragments of recalled memories: a sudden connection in the shower between seemingly disparate thoughts, or an…
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
This paper introduces R2D3, an agent that makes efficient use of demonstrations to solve hard exploration problems in partially observable environments with …
The Podcast: Episode 6: AI for everyone
While there is a lot of excitement about AI research, there are also concerns about the way it might be implemented, used and abused.
The Podcast: Episode 5: Out of the lab
The ambition of AI research is to create systems that can help to solve problems in the real world.
The Podcast: Episode 4: AI, Robot
Forget what sci-fi has told you about superintelligent robots that are uncannily human-like; the reality is more prosaic. Inside DeepMind’s robotics laborato…
The Podcast: Episode 3: Life is like a game
Video games have become a favourite tool for AI researchers to test the abilities of their systems. In this episode, Hannah sits down to play StarCraft II - …
The Podcast: Episode 2: Go to Zero
In March 2016, more than 200 million people watched AlphaGo become first computer program to defeat a professional human player at the game of Go, a mileston…
The Podcast: Episode 1: AI and neuroscience - The virtuous circle
What can the human brain teach us about AI? And what can AI teach us about our own intelligence? These questions underpin a lot of AI research.
Welcome to the DeepMind podcast
What’s AI? What can it be used for? Is it safe? And how do I get involved? These are the kinds of questions we often get asked at public events like science …
Using machine learning to accelerate ecological research
The Serengeti is one of the last remaining sites in the world that hosts an intact community of large mammals. These animals roam over vast swaths of land, s…
Using AI to give doctors a 48-hour head start on life-threatening illness
Artificial intelligence can now predict one of the leading causes of avoidable patient harm up to two days before it happens, as demonstrated by our latest r…
How evolutionary selection can train more capable self-driving cars
Waymo’s self-driving vehicles employ neural networks to perform many driving tasks, from detecting objects and predicting how others will behave, to planning…
Unsupervised learning: The curious pupil
Over the last decade, machine learning has made unprecedented progress in areas as diverse as image recognition, self-driving cars and playing complex games …
Capture the Flag: the emergence of complex cooperative agents
Mastering the strategy, tactical understanding, and team play involved in multiplayer video games represents a critical challenge for AI research. In our lat…
Identifying and eliminating bugs in learned predictive models
Bugs and software have gone hand in hand since the beginning of computer programming. Over time, software developers have established a set of best practices…
TF-Replicator: Distributed Machine Learning for Researchers
At DeepMind, the Research Platform Team builds infrastructure to empower and accelerate our AI research. Today, we are excited to share how we developed TF-R…
Machine learning can boost the value of wind energy
Carbon-free technologies like renewable energy help combat climate change, but many of them have not reached their full potential. Consider wind power: over …
AlphaStar: Mastering the real-time strategy game StarCraft II
Games have been used for decades as an important way to test and evaluate the performance of artificial intelligence systems. As capabilities have increased,…
AlphaZero: Shedding new light on chess, shogi, and Go
In late 2017 we introduced AlphaZero, a single system that taught itself from scratch how to master the games of chess, shogi (Japanese chess), and Go, beati…
Scaling Streams with Google
We’re excited to announce that the team behind Streams - our mobile app that supports doctors and nurses to deliver faster, better care to patients - will be…
Predicting eye disease with Moorfields Eye Hospital
In August, we announced the first stage of our joint research partnership with Moorfields Eye Hospital, which showed how AI could match world-leading doctors…
Open sourcing TRFL: a library of reinforcement learning building blocks
Today we are open sourcing a new library of useful building blocks for writing reinforcement learning (RL) agents in TensorFlow. Named TRFL (pronounced ‘truf…
Expanding our research on breast cancer screening to Japan
Six months ago, we joined a groundbreaking new research partnership led by the Cancer Research UK Imperial Centre at Imperial College London to explore wheth…
Preserving Outputs Precisely while Adaptively Rescaling Targets
Multi-task learning - allowing a single agent to learn how to solve many different tasks - is a longstanding objective for artificial intelligence research. …
Using AI to plan head and neck cancer treatments
Early results from our partnership with the Radiotherapy Department at University College London Hospitals NHS Foundation Trust suggest that we are well on o…
Safety-first AI for autonomous data centre cooling and industrial control
Many of society’s most pressing problems have grown increasingly complex, so the search for solutions can feel overwhelming. At DeepMind and Google, we belie…
A major milestone for the treatment of eye disease
We are delighted to announce the results of the first phase of our joint research partnership with Moorfields Eye Hospital, which could potentially transform…
Objects that Sound
Visual and audio events tend to occur together: a musician plucking guitar strings and the resulting melody; a wine glass shattering and the accompanying cra…
Measuring abstract reasoning in neural networks
Neural network-based models continue to achieve impressive results on longstanding machine learning problems, but establishing their capacity to reason about…
DeepMind papers at ICML 2018
The 2018 International Conference on Machine Learning will take place in Stockholm, Sweden from 10-15 July. For those attending and planning the week ahead, …
DeepMind Health Response to Independent Reviewers' Report 2018
When we set up DeepMind Health we believed that pioneering technology should be matched with pioneering oversight. That’s why when we launched in February 20…
Neural scene representation and rendering
There is more than meets the eye when it comes to how we understand a visual scene: our brains draw on prior knowledge to reason and to make inferences that …
Royal Free London publishes findings of legal audit in use of Streams
Last July, the Information Commissioner concluded an investigation into the use of the Streams app at the Royal Free London NHS Foundation Trust. As part of …
Prefrontal cortex as a meta-reinforcement learning system
Recently, AI systems have mastered a range of video-games such as Atari classics Breakout and Pong. But as impressive as this performance is, AI still relies…
Navigating with grid-like representations in artificial agents
Most animals, including humans, are able to flexibly navigate the world they live in – exploring new areas, returning quickly to remembered places, and takin…
DeepMind, meet Android
We’re delighted to announce a new collaboration between DeepMind for Google and Android, the world’s most popular mobile operating system. Together, we’ve cr…
DeepMind papers at ICLR 2018
Between 30 April and 03 May, hundreds of researchers and engineers will gather in Vancouver, Canada, for the Sixth International Conference on Learning Repre…
Our first COO Lila Ibrahim takes DeepMind to the next level
One of the greatest pleasures of coming to work every day at DeepMind is the chance to collaborate with brilliant researchers and engineers from so many diff…
Retour à Paris / A return to Paris
When we set up our headquarters in London in 2010, we wanted to make DeepMind the best possible place to do cutting-edge AI research. We also wanted to help …
Learning to navigate in cities without a map
How did you learn to navigate the neighborhood of your childhood, to go to a friend’s house, to your school or to the grocery store? Probably without a map a…
Learning to write programs that generate images
Through a human’s eyes, the world is much more than just the images reflected in our corneas. For example, when we look at a building and admire the intricac…
Understanding deep learning through neuron deletion
Deep neural networks are composed of many individual neurons, which combine in complex and counterintuitive ways to solve a wide range of challenging tasks. …
Stop, look and listen to the people you want to help
‘I like to take things slow. Take it slowly and get it right first time,’ one participant said, but was quickly countered by someone else around the table: ‘…
Learning by playing
Getting children (and adults) to tidy up after themselves can be a challenge, but we face an even greater challenge trying to get our AI agents to do the sam…
Researching patient deterioration with the US Department of Veterans Affairs
We’re excited to announce a medical research partnership with the US Department of Veterans Affairs (VA), one of the world’s leading healthcare organisations…
Scalable agent architecture for distributed training
Deep Reinforcement Learning (DeepRL) has achieved remarkable success in a range of tasks, from continuous control problems in robotics to playing games like …
Learning explanatory rules from noisy data
Suppose you are playing football. The ball arrives at your feet, and you decide to pass it to the unmarked striker. What seems like one simple action require…
Open-sourcing Psychlab
Consider the simple task of going shopping for your groceries. If you fail to pick-up an item that is on your list, what does it tell us about the functionin…
Game-theory insights into asymmetric multi-agent games
As AI systems start to play an increasing role in the real world it is important to understand how different systems will interact with one another.
2017: DeepMind's year in review
In July, the world number one Go player Ke Jie spoke after a streak of 20 wins. It was two months after he had played AlphaGo at the Future of Go Summit in W…
Collaborating with patients for better outcomes
Working as a doctor in the NHS for over 10 years, I felt that I had developed good understanding of how patients and their families felt when faced with an u…
DeepMind papers at NIPS 2017
Between 04-09 December, thousands of researchers and experts will gather for the Thirty-first Annual Conference on Neural Information Processing Systems (NIP…
Why doesn't Streams use AI?
One of the questions I’m most often asked about Streams, our secure mobile healthcare app, is “why is DeepMind making something that doesn’t use artificial i…
Specifying AI safety problems in simple environments
As AI systems become more general and more useful in the real world, ensuring they behave safely will become even more important. To date, the majority of te…
Population based training of neural networks
Neural networks have shown great success in everything from playing Go and Atari games to image recognition and language translation. But often overlooked is…
Applying machine learning to mammography screening for breast cancer
We founded DeepMind Health to develop technologies that could help address some of society’s toughest challenges. So we’re very excited to announce that our …
High-fidelity speech synthesis with WaveNet
In October we announced that our state-of-the-art speech synthesis model WaveNet was being used to generate realistic-sounding voices for the Google Assistan…
Sharing our insights from designing with clinicians
In our design studio, we have Indi Young’s mantra on the wall as a reminder to “fall in love with the problem, not the solution”. Nowhere is this more true t…
Bringing Streams to Yeovil District Hospital NHS Foundation Trust
We’re excited to announce that we’ve agreed a five year partnership with Yeovil District Hospital NHS Foundation Trust. We’ll be providing them with Streams,…
AlphaGo Zero: Starting from scratch
Artificial intelligence research has made rapid progress in a wide variety of domains from speech recognition and image classification to genomics and drug d…
Strengthening our commitment to Canadian research
Three months ago we announced the opening of DeepMind’s first ever international AI research laboratory in Edmonton, Canada. Today, we are thrilled to announ…
WaveNet launches in the Google Assistant
Just over a year ago we presented WaveNet, a new deep neural network for generating raw audio waveforms that is capable of producing better and more realisti…
Why we launched DeepMind Ethics & Society
At DeepMind, we’re proud of the role we’ve played in pushing forward the science of AI, and our track record of exciting breakthroughs and major publications…
The hippocampus as a predictive map
Think about how you choose a route to work, where to move house, or even which move to make in a game like Go. All of these scenarios require you to estimate…
DeepMind and Blizzard open StarCraft II as an AI research environment
DeepMind's scientific mission is to push the boundaries of AI by developing systems that can learn to solve complex problems. To do this, we design agents an…
DeepMind papers at ICML 2017 (part one)
The first of our three-part series, which gives brief descriptions of the papers we are presenting at the ICML 2017 Conference in Sydney, Australia.
DeepMind papers at ICML 2017 (part three)
The final part of our three-part series that gives an overview of the papers we are presenting at the ICML 2017 Conference in Sydney, Australia.
DeepMind papers at ICML 2017 (part two)
The second of our three-part series, which gives an overview of the papers we are presenting at the ICML 2017 Conference in Sydney, Australia.
AI and Neuroscience: A virtuous circle
Recent progress in AI has been remarkable. Artificial systems now outperform expert humans at Atari video games, the ancient board game Go, and high-stakes m…
Going beyond average for reinforcement learning
Consider the commuter who toils backwards and forwards each day on a train. Most mornings, her train runs on time and she reaches her first meeting relaxed a…
Agents that imagine and plan
Imagining the consequences of your actions before you take them is a powerful tool of human cognition. When placing a glass on the edge of a table, for examp…
Imagine this: Creating new visual concepts by recombining familiar ones
Around two and a half thousand years ago a Mesopotamian trader gathered some clay, wood and reeds and changed humanity forever. Over time, their abacus would…
Producing flexible behaviours in simulated environments
The agility and flexibility of a monkey swinging through the trees or a football player dodging opponents and scoring a goal can be breathtaking. Mastering t…
DeepMind expands to Canada with new research office in Edmonton, Alberta
DeepMind has always been a unique hybrid of startup culture and academia, and we’ve been lucky to collaborate with many of the best researchers from around t…
Independent Reviewers release first annual report on DeepMind Health
Today, a panel of Independent Reviewers has published its first annual report into DeepMind Health. As I wrote in the foreword to their report (written, I ad…
The Information Commissioner, the Royal Free, and what we’ve learned
Today, dozens of people in UK hospitals will die preventably from conditions like sepsis and acute kidney injury (AKI) when their warning signs aren't picked…
Interpreting Deep Neural Networks using Cognitive Psychology
Deep neural networks have learnt to do an amazing array of tasks - from recognising and reasoning about objects in images to playing Atari and Go at super-hu…
Enhancing patient safety at Taunton and Somerset NHS Foundation Trust
We’re delighted to announce our first partnership outside of London to help doctors and nurses break new ground in the NHS’s use of digital technology.
Learning through human feedback
We believe that Artificial Intelligence will be one of the most important and widely beneficial scientific advances ever made, helping humanity tackle some o…
A neural approach to relational reasoning
Consider the reader who pieces together the evidence in an Agatha Christie novel to predict the culprit of the crime, a child who runs ahead of her ball to p…
AlphaGo's next move
With just three stones on the board, it was clear that this was going to be no ordinary game of Go.
Exploring the mysteries of Go with AlphaGo and China's top players
Just over a year ago, we saw a major milestone in the field of artificial intelligence: DeepMind’s AlphaGo took on and defeated one of the world’s top Go pla…
Innovations of AlphaGo
One of the great promises of AI is its potential to help us unearth new knowledge in complex domains. We’ve already seen exciting glimpses of this, when our …
Open sourcing Sonnet - a new library for constructing neural networks
It’s now nearly a year since DeepMind made the decision to switch the entire research organisation to using TensorFlow (TF). It’s proven to be a good choice …
Distill: Communicating the science of machine learning
Like every field of science, the importance of clear communication in machine learning research cannot be over-emphasised: it helps to drive forward the stat…
Enabling Continual Learning in Neural Networks
Computer programs that learn to perform tasks also typically forget them very quickly. We show that the learning rule can be modified so that a program can r…
Trust, confidence and Verifiable Data Audit
Data can be a powerful force for social progress, helping our most important institutions to improve how they serve their communities. As cities, hospitals, …
A milestone for DeepMind Health and Streams
In November we announced a groundbreaking five year partnership with the Royal Free London to deploy and expand on Streams, our secure clinical app that aims…
Understanding Agent Cooperation
We employ deep multi-agent reinforcement learning to model the emergence of cooperation. The new notion of sequential social dilemmas allows us to model how …
Our collaborations with academia to advance the field of AI
When I was studying in the mid-90s as an undergraduate, there was very little active engagement between the academic communities pushing the boundaries of ma…
DeepMind’s work in 2016: a round-up
In a world of fiercely complex, emergent, and hard-to-master systems - from our climate to the diseases we strive to conquer - we believe that intelligent pr…
Bringing the best of mobile technology to Imperial College Healthcare NHS Trust
We’re really excited to announce that we’ve agreed a five year partnership with Imperial College Healthcare NHS Trust, helping them make the most of the oppo…
DeepMind Papers @ NIPS (Part 3)
DeepMind Papers @ NIPS (Part 3)
DeepMind Papers @ NIPS (Part 2)
The second blog post in this series, sharing brief descriptions of the papers we are presenting at NIPS 2016 Conference in Barcelona.
Open-sourcing DeepMind Lab
DeepMind's scientific mission is to push the boundaries of AI, developing systems that can learn to solve any complex problem without needing to be taught how.
DeepMind Papers @ NIPS (Part 1)
Over the next three blogposts, we're going to share with you brief descriptions of the papers we are presenting at the NIPS 2016 Conference in Barcelona.
Working with the NHS to build lifesaving technology
We’re very proud to announce a groundbreaking five year partnership with the Royal Free London NHS Foundation Trust.
Reinforcement learning with unsupervised auxiliary tasks
Our primary mission at DeepMind is to push the boundaries of AI, developing programs that can learn to solve any complex problem without needing to be taught…
DeepMind and Blizzard to release StarCraft II as an AI research environment
Today at BlizzCon 2016 in Anaheim, California, we announced our collaboration with Blizzard Entertainment to open up StarCraft II to AI and Machine Learning …
Differentiable neural computers
In a recent study in Nature, we introduce a form of memory-augmented neural network called a differentiable neural computer, and show that it can learn to us…
Announcing the Partnership on AI to Benefit People & Society
We believe that AI has the potential for transformative, positive impact in the world. Fulfilling this potential is not only dependent on the quality of the …
Putting patients at the heart of DeepMind Health
From the outset, we’ve wanted DeepMind Health to be a truly collaborative effort. Too much hospital IT has been developed from a top-down perspective, often …
WaveNet: A generative model for raw audio
This post presents WaveNet, a deep generative model of raw audio waveforms. We show that WaveNets are able to generate speech which mimics any human voice an…
Applying machine learning to radiotherapy planning for head & neck cancer
We’re excited to announce a new research partnership with the Radiotherapy Department at University College London Hospitals NHS Foundation Trust, which prov…
Decoupled Neural Interfaces Using Synthetic Gradients
Neural networks are the workhorse of many of the algorithms developed at DeepMind. For example, AlphaGo uses convolutional neural networks to evaluate board …
DeepMind AI Reduces Google Data Centre Cooling Bill by 40%
Reducing energy usage has been a major focus for us over the past 10 years: we have built our own super-efficient servers at Google, invented more efficient …
Deep Reinforcement Learning
Humans excel at solving a wide variety of challenging problems, from low-level motor control through to high-level cognitive tasks. Our goal at DeepMind is t…
Announcing DeepMind Health research partnership with Moorfields Eye Hospital
We founded DeepMind to make the world a better place by developing technologies that help address some of society's toughest challenges. So we’re excited to …
We are very excited to announce the launch of DeepMind Health
We founded DeepMind to solve intelligence and use it to make the world a better place by developing technologies that help address some of society's toughest…
