From the Stone Age to the AI Age 🪨➡️💻 On our podcast, VP Science Pushmeet Kohli discusses with host Professor Hannah Fry how AI could assist materials discovery. Imagine the possibilities - lighter, stronger, more sustainable materials could help transform everything from construction to medicine. 🏗️🩺 Watch now ↓ https://goo.gle/3UibGA7
Google DeepMind
Research Services
London, London 1,088,044 followers
We're committed to solving intelligence, to advance science and benefit humanity.
About us
We’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority. Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI). Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges. We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.
- Website
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https://www.deepmind.google
External link for Google DeepMind
- Industry
- Research Services
- Company size
- 501-1,000 employees
- Headquarters
- London, London
- Type
- Privately Held
- Founded
- 2010
- Specialties
- Artificial Intelligence and Machine Learning
Locations
Employees at Google DeepMind
Updates
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Our CEO Demis Hassabis sat down with The Times at their recent Tech Summit to discuss building AGI with safety in mind, the power of #AlphaFold and his predictions for what’s next in AI development. Register to watch the full conversation ↓ https://lnkd.in/eVcT28vP
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Millions of scientists - now in 190 countries - are using #AlphaFold to accelerate their work. Our VP of Science Pushmeet Kohli spoke with Hannah Fry on our podcast about why using this breakthrough AI system feels like a superpower, how our other models are progressing science - and much more. Listen now ↓ https://dpmd.ai/3zNT4kF
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🥇 We're still celebrating a truly momentous achievement for AI and science. Here's the moment some of the #AlphaFold team found out our CEO Demis Hassabis and Research Director John Jumper were co-awarded the Nobel Prize in Chemistry 2024. After the news was announced, John and Demis reunited with their colleagues in London. 🎉
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Google DeepMind reposted this
Winning The Nobel Prize is the honour of a lifetime and the realisation of a lifelong dream - it still hasn’t really sunk in yet. With AlphaFold2 we cracked the 50-year grand challenge of protein structure prediction: predicting the 3D structure of a protein purely from its amino acid sequence. Proteins are the building blocks of life, and knowing the structure of a protein is crucial for understanding the function it performs. We then folded all 200 million proteins known to science and made those structures freely available for anyone in the world to use, with the help of our wonderful collaborators at European Bioinformatics Institute | EMBL-EBI. Over 2 million researchers have already used AlphaFold2 and its predictions to advance a huge range of important work - everything from enzyme design, to disease understanding, to drug discovery. But this is only the beginning. Over the next few years AI will help us make great strides towards developing new and more effective therapies for today's most prevalent diseases, and the fantastic team at Isomorphic Labs are making rapid progress on this mission. I can’t think of a more important or beneficial use of AI. Then of course there is advancing AGI itself, the original and enduring goal, and the vision behind the founding of DeepMind nearly 15 years ago. If AI is built safely and responsibly, I believe it will be one of the most transformative and beneficial technologies ever. I’ve always thought of AI as the ultimate tool to help us accelerate scientific discovery. Congratulations to John Jumper (and David Baker!), the amazing AlphaFold team, and all our incredible colleagues at Google DeepMind and Google that supported and encouraged us along the way - this award is for all of us! It’s been such an honour and privilege to work with all of you to advance the frontiers of AI and science, and there is so much more to come!
BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 Nobel Prize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.” The Nobel Prize in Chemistry 2024 is about proteins, life’s ingenious chemical tools. David Baker has succeeded with the almost impossible feat of building entirely new kinds of proteins. Demis Hassabis and John Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures. These discoveries hold enormous potential. The diversity of life testifies to proteins’ amazing capacity as chemical tools. They control and drive all the chemical reactions that together are the basis of life. Proteins also function as hormones, signal substances, antibodies and the building blocks of different tissues. Proteins generally consist of 20 different amino acids, which can be described as life’s building blocks. In 2003, David Baker succeeded in using these blocks to design a new protein that was unlike any other protein. Since then, his research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors. The second discovery concerns the prediction of protein structures. In proteins, amino acids are linked together in long strings that fold up to make a three-dimensional structure, which is decisive for the protein’s function. Since the 1970s, researchers had tried to predict protein structures from amino acid sequences, but this was notoriously difficult. However, four years ago, there was a stunning breakthrough. In 2020, Demis Hassabis and John Jumper presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic. Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind. Learn more Press release: https://bit.ly/3TM8oVs Popular information: https://bit.ly/3XYHZGp Advanced information: https://bit.ly/4ewMBta
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“Congratulations to John, the #AlphaFold team, and everyone at DeepMind & Google that supported us along the way - it’s an amazing award for all of us! It’s such an honour and privilege to work with all of you to advance the frontiers of science.” - Demis Hassabis Find out more about The Nobel Prize and AlphaFold’s impact → https://dpmd.ai/40iZAL9
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Huge congratulations to Demis Hassabis and John Jumper on being awarded the 2024 Nobel Prize in Chemistry for protein structure prediction with #AlphaFold, along with David Baker for computational protein design. This is a monumental achievement for AI, for computational biology, and science itself. 🧬
BREAKING NEWS The Royal Swedish Academy of Sciences has decided to award the 2024 Nobel Prize in Chemistry with one half to David Baker “for computational protein design” and the other half jointly to Demis Hassabis and John M. Jumper “for protein structure prediction.” The Nobel Prize in Chemistry 2024 is about proteins, life’s ingenious chemical tools. David Baker has succeeded with the almost impossible feat of building entirely new kinds of proteins. Demis Hassabis and John Jumper have developed an AI model to solve a 50-year-old problem: predicting proteins’ complex structures. These discoveries hold enormous potential. The diversity of life testifies to proteins’ amazing capacity as chemical tools. They control and drive all the chemical reactions that together are the basis of life. Proteins also function as hormones, signal substances, antibodies and the building blocks of different tissues. Proteins generally consist of 20 different amino acids, which can be described as life’s building blocks. In 2003, David Baker succeeded in using these blocks to design a new protein that was unlike any other protein. Since then, his research group has produced one imaginative protein creation after another, including proteins that can be used as pharmaceuticals, vaccines, nanomaterials and tiny sensors. The second discovery concerns the prediction of protein structures. In proteins, amino acids are linked together in long strings that fold up to make a three-dimensional structure, which is decisive for the protein’s function. Since the 1970s, researchers had tried to predict protein structures from amino acid sequences, but this was notoriously difficult. However, four years ago, there was a stunning breakthrough. In 2020, Demis Hassabis and John Jumper presented an AI model called AlphaFold2. With its help, they have been able to predict the structure of virtually all the 200 million proteins that researchers have identified. Since their breakthrough, AlphaFold2 has been used by more than two million people from 190 countries. Among a myriad of scientific applications, researchers can now better understand antibiotic resistance and create images of enzymes that can decompose plastic. Life could not exist without proteins. That we can now predict protein structures and design our own proteins confers the greatest benefit to humankind. Learn more Press release: https://bit.ly/3TM8oVs Popular information: https://bit.ly/3XYHZGp Advanced information: https://bit.ly/4ewMBta
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🐐🎮 Could playing Goat Simulator 3 help us develop better AI? Tune in to the latest episode of our podcast where Research Engineering Team Lead Frederic Besse discusses Scalable Instructable Multiworld Agent (SIMA), our AI agent that can follow instructions in a variety of games, including 3D worlds. ↓ https://dpmd.ai/3TWKoz9
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“Proteins sticking to other proteins is what makes life exist.” 🧬 We explain the science behind AlphaProteo: our AI system for protein binder design that holds huge potential for biology. ▶️ Hear from Jue Wang, co-lead of the protein design team, David La, research scientist, and Harshnira Patani, wet lab lead here at Google DeepMind. ↓
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Imagine AI as smart and adaptable as humans - helping solve problems, advance scientific progress, and even taking care of everyday tasks. 🧹 Join host Hannah Fry and Research Engineering Team Lead Frederic Besse as they explore the complex world of AI agents – programs that can learn, adapt, and act in virtual environments. ↓ https://dpmd.ai/3Y3Cwyb