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Inside Isomorphic Labs, the secretive AI life sciences startup spun off from Google DeepMind
CNBC· 2025-04-09 12:00
Core Insights - Google DeepMind has invested in Isomorphic Labs, an AI life sciences startup focused on drug discovery using AlphaFold technology, aiming to "solve all disease" through AI-powered methods [2][4][5] Company Overview - Isomorphic Labs was spun out of Google DeepMind after significant advancements in AI, particularly with AlphaFold2, which predicts protein structures and has the potential to revolutionize drug discovery [2][4][14] - The company has grown to over 200 employees and established partnerships with major pharmaceutical firms like Eli Lilly and Novartis, with potential partnership values nearing $3 billion [9][26] Investment and Funding - Google initially invested in Isomorphic in November 2021, although the amount remains undisclosed. Recently, Isomorphic secured $600 million in external funding led by Thrive Capital [6][8] - The funding will be used to expand into biologics and enhance computational capabilities necessary for AI applications in drug discovery [25][27] Market Potential - The drug discovery market is projected to reach $71 billion by 2025, with AI expected to significantly alter the landscape [7] - Traditional drug development processes can take over 10 years and cost more than $2 billion, but AI could streamline these processes, reducing costs and increasing success rates [8] Technological Advancements - Isomorphic has made AlphaFold3 available for non-commercial use, expanding its capabilities to predict structures of various biological molecules beyond proteins [10][12] - The company is focused on utilizing AlphaFold3 to enhance drug discovery and biological understanding, particularly in cancer and immunology [26][27] Leadership and Vision - Demis Hassabis, co-founder of DeepMind and now CEO of Isomorphic, emphasizes the importance of AI in improving human health and solving complex biological challenges [24][25] - The leadership team at Isomorphic is committed to fostering an interdisciplinary culture that combines AI expertise with drug discovery knowledge [18][28]
UPDATE -- NVIDIA, Alphabet and Google Collaborate on the Future of Agentic and Physical AI
Globenewswire· 2025-03-19 03:39
Core Insights - NVIDIA, Alphabet, and Google are launching new initiatives to enhance AI, democratize access to AI tools, and transform various industries including healthcare, manufacturing, and energy [1][20] Group 1: AI and Robotics Development - Engineers and researchers from Alphabet and NVIDIA are collaborating to develop robots with advanced grasping skills and reimagine drug discovery using AI and simulation technologies [2] - The partnership includes the use of NVIDIA platforms such as Omniverse™, Cosmos™, and Isaac™ to support these initiatives [2] - Intrinsic, an Alphabet company, is focused on creating adaptive AI for robotics, aiming to reduce the complexity and cost of programming industrial robots [9][10] Group 2: Drug Discovery Innovations - Isomorphic Labs is leveraging AI to revolutionize drug discovery, utilizing a state-of-the-art drug design engine on Google Cloud powered by NVIDIA GPUs [12] - This collaboration aims to enhance the scale and performance of AI models that can significantly advance human health [12] Group 3: Energy Solutions - Tapestry, a project under Alphabet's X, is working with NVIDIA to develop AI-powered products for a more reliable and sustainable electric grid [13][14] - The focus is on optimizing energy grid simulations and integrating new energy sources to meet the demands of data centers and AI [14] Group 4: AI Infrastructure Advancements - Google Cloud will be among the first to adopt NVIDIA's latest GB300 NVL72 and RTX PRO 6000 Blackwell Server Edition GPUs, enhancing AI performance [3][15] - The GB300 NVL72 offers 1.5 times more AI performance compared to its predecessor, with a 50 times increase in revenue opportunity for AI factories [16] Group 5: Open Model Optimization - Google DeepMind and NVIDIA are optimizing Gemma, a family of lightweight open models, to run efficiently on NVIDIA GPUs, enhancing accessibility for developers [7] - The collaboration also includes optimizing Gemini-based workloads on NVIDIA accelerated computing via Vertex AI [8]