DeepMind
00h00 23  décembre
MuZero: Mastering Go, chess, shogi and Atari without rules
Planning winning strategies in unknown environments is a step forward in the pursuit of general-purpose algorithms.
00h00 04  décembre
Using JAX to accelerate our research
An introduction to our JAX ecosystem and why we find it useful for our AI research.
00h00 30  novembre
AlphaFold: a solution to a 50-year-old grand challenge in biology
In a major scientific advance, AlphaFoldis recognised as a solution to the protein folding problem.
00h00 05  novembre
Breaking down global barriers to access
We’re expanding our scholars programme to support more countries currently underrepresented in AI.
00h00 19  octobre
FermiNet: Quantum Physics and Chemistry from First Principles
Weve developed a new neural network architecture, the Fermionic Neural Network or FermiNet, which is well-suited to modeling the quantum state of large collections of electrons, the fundamental building blocks of chemical bonds.
00h00 12  octobre
Fast reinforcement learning through the composition of behaviours
The combination of reinforcement learning and deep learning has led to impressive results, such as agents that can learn how to play boardgames, the full spectrum of Atari games, as well as more modern, difficult video games like Dota and StarCraft II.
00h00 03  septembre
Traffic prediction with advanced Graph Neural Networks
Working with our partners at Google Maps, we used advanced machine learning techniques including Graph Neural Networks, to improve the accuracy of real time ETAs by up to 50%.
00h00 23  juin
Applying for technical roles
We answer the Women in Machine Learning community’s questions about applying for a job in industry.
00h00 18  mai
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 degeneration (AMD) is the most common cause of blindness in the developed world. In Europe, approximately 25% of those 60 and older have AMD....
00h00 21  avril
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 experiences with specification gaming, even if not by this name. Readers may have heard the myth of King Midas and the golden touch, in which the king...
00h00 06  avril
Towards understanding glasses with graph neural networks
Under a microscope, a pane of window glass doesnt look like a collection of orderly molecules, as a crystal would, but rather a jumble with no discernable structure. Glass is made by starting with a glowing mixture of high-temperature melted sand and minerals. Once cooled, its viscosity (a measure...
00h00 31  mars
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. Weve developed Agent57, the first deep reinforcement learning agent to obtain a score that is above the human baseline on all 57 Atari 2600 games. Agent57 combines an algorithm for...
00h00 10  février
A new model and dataset for long-range memory
This blog introduces a new long-range memory model, the Compressive Transformer, alongside a new benchmark for book-level language modelling, PG19. We provide the conceptual tools needed to understand this new research in the context of recent developments in memory models and language modelling.
00h00 15  janvier
AlphaFold: Using AI for scientific discovery
Our Nature paper describes AlphaFold, a system that generates3D models of proteins that are far more accurate than any that have come before.
00h00 15  janvier
Dopamine and temporal difference learning: A fruitful relationship between neuroscience and AI
A recent development in computer science may provide a deep, parsimonious explanation for several previously unexplained features of reward learning in the brain.
00h00 18  décembre
Using WaveNet technology to reunite speech-impaired users with their original voices
We demonstrate an early proof of concept of how text-to-speech technologies can synthesise a high-quality, natural sounding voice using minimal recorded speech data.
00h00 13  décembre
Learning human objectives by evaluating hypothetical behaviours
We present a new method for training reinforcement learning agents from human feedback in the presence of unknown unsafe states.
00h00 05  décembre
From unlikely start-up to major scientific organisation: Entering our tenth year at DeepMind
Weve come a long way in building the organisation we need to achieve our long-term mission.
00h00 21  novembre
Strengthening the AI community
AI requires people with different experiences, knowledge and backgrounds, which is why we started the DeepMind Scholarship programme and supportuniversitiesand the wider ecosystem.
00h00 18  novembre
Advanced machine learning helps Play Store users discover personalised apps
In collaboration with Google Play,our team that leads on collaborations with Googlehas driven significant improvements in the Play Store’s discovery systems, helping to deliver a more personalised and intuitive Play Store experience for users.
00h00 30  octobre
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.
00h00 03  octobre
Causal Bayesian Networks: A flexible tool to enable fairer machine learning
Decisions based on machine learning (ML) are potentially advantageous over human decisions, but the data used to train them often contains human and societal biases that can lead to harmful decisions.
00h00 18  septembre
DeepMind’s health team joins Google Health
Heres what the future looks like for the team.
00h00 17  septembre
Episode 8: Demis Hassabis - The interview
In this special extended episode, Hannah meets Demis Hassabis, the CEO and co-founder of DeepMind.
00h00 10  septembre
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 how. Hannah explores the journey to get there.
00h00 06  septembre
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 ill-fated choice decades ago that haunts us as we struggle to fall asleep.
00h00 03  septembre
Episode 6: AI for everyone
Hannah investigates the more human side of the technology, some ethical issues around how it is developed and used, and the efforts to create a future of AI that works for everyone.
00h00 27  août
Episode 5: Out of the lab
Hannah Fry meets the scientists building systems that could be used to save the sight of thousands; help us solve one of the most fundamental problems in biology, and reduce energy consumption in an effort to combat climate change.
00h00 20  août
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 DeepMinds robotics laboratory, Hannah explores what researchers call embodied AI.
00h00 19  août
Episode 3: Life is like a game
Video games have become a favourite tool for AI researchers to test the abilities of their systems. Why?
00h00 18  août
Episode 2: Go to Zero
The story of AlphaGo, first computer program to defeat a professional human player at the game of Go, a milestone considered a decade ahead of its time.
00h00 17  août
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?
00h00 16  août
Welcome to the DeepMind podcast
This eight part series hosted by mathematician and broadcaster Hannah Fry aims to give listeners an inside look at the fascinating world of AI research and explores some of the questions and challenges the whole field is wrestling with today.
00h00 08  août
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, some migrating thousands of miles across multiple countries following seasonal rainfall. As human encroachment around the park becomes more...
00h00 31  juillet
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 byour latest research published in Nature.
00h00 25  juillet
How evolutionary selection can train more capable self-driving cars
00h00 25  juin
Unsupervised learning: The curious pupil
One in a series of posts explaining the theories underpinning our research. Over the last decade, machine learning has made unprecedented progress in areas as diverse as image recognition, self-driving cars and playing complex games like Go. These successes have been largely realised by training...
00h00 30  mai
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. Now, through new developments in reinforcement learning, our agents have achieved human-level performance in Quake III Arena Capture the Flag, a complex...
00h00 28  mars
Identifying and eliminating bugs in learned predictive models
One in a series of posts explaining the theories underpinning our research. 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 for testing and debugging before deployment, but these practices...
00h00 07  mars
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-Replicator, a software library that helps researchers deploy their TensorFlow models on GPUs and Cloud TPUs with minimal effort and no previous...
00h00 26  février
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 the past decade, wind farms have become an important source of carbon-free electricity as the cost of turbines has plummeted and adoption has...
00h00 24  janvier
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, the research community has sought games with increasing complexity that capture different elements of intelligence required to solve...
00h00 06  décembre
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, beating a world-champion program in each case. We were excited by the preliminary results and thrilled to see the response from members of the...
00h00 02  décembre
AlphaFold: Using AI for scientific discovery
Today were excited to share DeepMinds first significant milestone in demonstrating how artificial intelligence research can drive and accelerate new scientific discoveries. With a strongly interdisciplinary approach to our work, DeepMind has brought together experts from the fields of structural...
00h00 13  novembre
Scaling Streams with Google
Were excited to announce that the team behind Streams our mobile app that supports doctors and nurses to deliver faster, better care to patientswill be joining Google.Its been a phenomenal journey to see Streams go from initial idea to live deployment, and to hear how its helped change the lives...
00h00 05  novembre
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 at recommending the correct course of treatment for over 50 eye diseases, and also explain how it arrives at its recommendations.Now were...
00h00 17  octobre
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 truffle), it represents a collection of key algorithmic components that we have used internally for a large number of our most successful agents...
00h00 04  octobre
Expanding our research on breast cancer screening to Japan
Japanese version followsSix months ago, we joined a groundbreaking new research partnership led by the Cancer Research UK Imperial Centre at Imperial College London to explore whether AI technology could help clinicians diagnose breast cancers on mammograms quicker and more effectively.Breast...
00h00 13  septembre
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. Recently, there has been a lot of excellent progress, with agents likeDQN able to use the same algorithm to learn to play multiple games...
00h00 13  septembre
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 our way to developing an artificial intelligence (AI) system that can analyse and segment medical scans of head and neck cancer to a similar...