Introducing AlphaProteo: an AI system for designing novel proteins that bind more successfully to target molecules. 🧬 This research could help deepen our understanding of fundamental biology. Here’s how: 🔵 Protein binders are essential tools in drug development and biotech. They’ve already demonstrated potential in binding cancer cells, blocking viral infections and more. 🔵 AlphaProteo managed to generate candidates with strong binding to 7️⃣ diverse proteins related to infection, cancer, inflammation, and autoimmune disease. 🔵 AI for protein design has great potential - but more work is needed. We’re improving AlphaProteo’s success rate and will continue working with scientists to develop a responsible offering for the community. Find out more ↓https://dpmd.ai/4geFM0L
Google DeepMind
Research Services
London, London 1,081,367 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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“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
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We developed AlphaChip: an AI approach for designing microchips. Here’s how it’s helping unlock new technologies. ⚡ 🔲 It was used in the latest generations of Google’s Tensor Processing Units (TPUs), which are specialized chips for building AI models. 🔲 This includes Trillium, its sixth-generation TPU, which set the new state of the art - delivering nearly five times the peak performance, double the bandwidth, and 67% better energy efficiency than its predecessor. 🔲 Our ultimate vision is using AI to create chips which are faster, cheaper and more sustainable. 🔲 This could help develop new AI-powered technologies in devices such as smartphones, medical devices and agricultural sensors. Find out more → https://dpmd.ai/4gItIFw
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Google DeepMind reposted this
Q: What happens to qubits after they’re made? A: Quantum processors operate in harsh environments like extreme temperatures and ultra high vacuums. Just like delicate microchips, they need a special "home" to work properly. That's where qubit packaging comes in! Watch how our #QuantumAI team is mastering this process to protect qubits from mechanical stress, moisture, and stray electromagnetic fields.
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Today, we’re excited to release two new, production-ready versions of Gemini 1.5 Pro and Flash. 🚢 They build on our latest experimental releases and include significant improvements in long context understanding, vision and math. Developers can access both for free via Google AI Studio and the Gemini API - while enterprises can try it on Google Cloud's Vertex AI platform. 🤝 → https://dpmd.ai/4dz7q6l
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From cleaning up the kitchen to fetching a snack, could robots one day assist us in our daily lives? In Google DeepMind: The Podcast, Jeff Dean spoke with Hannah Fry about the potential for AI to power robots capable of understanding and responding to natural language. ↓ https://dpmd.ai/3TDyGcA