Today, we’re delighted to announce that our research project into breast cancer screening is expanding internationally, with The Jikei University Hospital, one of Japan’s foremost medical institutions, joining the collaboration as part of a wider five year partnership they have signed with DeepMind Health.
In our study published today in Nature, we demonstrate how artificial intelligence research can drive and accelerate new scientific discoveries. We’ve built a dedicated, interdisciplinary team in hopes of using AI to push basic research forward: bringing together experts from the fields of structural biology, physics, and machine learning to apply cutting-edge techniques to predict the 3D structure of a protein based solely on its genetic sequence.
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 given action will result in a positive (that is, rewarding) outcome. The study of how organisms learn from experience to correctly anticipate rewards has been a productive research field for well over a century, since Ivan Pavlov's seminal psychological work. In his most famous experiment, dogs were trained to expect food some time after a buzzer sounded. These dogs began salivating as soon as they heard the sound, before the food had arrived, indicating they'd learned to predict the reward. In the original experiment, Pavlov estimated the dogs’ anticipation by measuring the volume of saliva they produced. But in recent decades, scientists have begun to decipher the inner workings of how the brain learns these expectations. Meanwhile, in close contact with this study of reward learning in animals, computer scientists have developed algorithms for reinforcement learning in artificial systems. These algorithms enable AI systems to learn complex strategies without external instruction, guided instead by reward predictions.
This post presents a recent project we undertook with Google and ALS campaigner Tim Shaw, as part of Google’s Euphonia project. 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. 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 were finally realised: the Carolina Panthers drafted him at age 23, and he went on to play for the Chicago Bears and Tennessee Titans, where he broke records as a linebacker. After six years in the NFL, on the cusp of greatness, his performance began to falter. He couldn’t tackle like he once had; his arms slid off the pullup bar. At home, he dropped bags of groceries, and his legs began to buckle underneath him. In 2013 Tim was cut from the Titans but he resolved to make it onto another team. Tim practiced harder than ever, yet his performance continued to decline. Five months later, he finally discovered the reason: he was diagnosed with Amyotrophic lateral sclerosis (ALS, commonly known as Lou Gehrig’s disease). In ALS, the neurons that control a person’s voluntary muscles die, eventually leading to a total loss of control over one’s body. ALS has no known cause, and, as of today, has no cure.
Products and Case Studies
Deepmind - Deepmind - Dnc
We introduced a form of memory-augmented neural network called a differentiable neural computer (DNC), and demonstrated that it can learn to use its memory to answer questions about complex, structured data.
Deepmind - Deepmind - Dqn
We leveraged recent breakthroughs in training deep neural networks to show that a novel end-to-end reinforcement learning agent, termed a deep Q-network (DQN), was able to surpass the overall performance of a professional human reference player.
Deepmind - Deepmind - Alphago
AlphaGo is the first computer program to defeat a professional human Go player, the first program to defeat a Go world champion, and arguably the strongest Go player in history.
In 2016, DeepMind and Google jointly developed an AI-powered recommendations system to improve the energy efficiency of Google’s already highly-optimised data centres. Now we’re taking...Save to Library
Case Study : The Promising Role Of Ai In Helping Plan Treatment For Patients With Head & Neck Cancers | Deepmind
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...Save to Library
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...Save to Library
Our system, AlphaFold, which we have been working on for the past two years, builds on years of prior research in using vast genomic data...Save to Library