Nvidia and Eli Lilly commit $1 billion to build AI lab that could reinvent drug discovery
13 Sources
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Nvidia to Invest $1 Billion in AI Drug Laboratory With Eli Lilly
Nvidia Corp. plans to invest $1 billion over five years in a new laboratory with Eli Lilly & Co., aiming to speed up the use of artificial intelligence in the pharmaceutical industry. The facility will be built in Silicon Valley and bring Lilly's lab expertise closer to the center of artificial
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Nvidia, Eli Lilly commit $1B to AI drug discovery lab
If penicillin was discovered on moldy bread, who's to say the next miracle drug won't be born from AI hallucinations Nvidia has teamed up with pharmaceutical heavyweight Eli Lilly to plow up to $1 billion into a research lab over the next five years to advance the development of foundation models
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Nvidia, Eli Lilly to spend $1 billion over five years on joint research lab
SAN FRANCISCO, Jan 12 (Reuters) - Nvidia (NVDA.O), opens new tab and U.S. pharma giant Eli Lilly (LLY.N), opens new tab will spend $1 billion building a new joint research lab in the San Francisco Bay area over five years which will use Nvidia's newest generation Vera Rubin AI chips, the firms said
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NVIDIA and Lilly Announce Co-Innovation AI Lab to Reinvent Drug Discovery in the Age of AI
Companies to Jointly Invest up to $1 Billion Over Five Years in Infrastructure and Research * NVIDIA and Lilly bring together a world-leading, multidisciplinary team of scientists, AI researchers and engineers to address the hardest problems in drug discovery. * The co-innovation lab
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Nvidia, Lilly to invest up to $1B in new AI medical research lab - SiliconANGLE
Nvidia Corp. is partnering with Eli Lilly and Co. to open a research lab that will use artificial intelligence to speed up drug discovery. The companies announced the collaboration today. They plan to spend up to $1 billion on the lab, which is set to open its doors in South San Francisco later
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Nvidia, Eli Lilly to spend $1 billion over five years on joint research lab
Nvidia and US pharma giant Eli Lilly will spend $1 billion building a new joint research lab in the San Francisco Bay area over five years which will use Nvidia's newest generation Vera Rubin AI chips, the firms said on Monday. Nvidia and US pharma giant Eli Lilly will spend $1 billion building a
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Nvidia, Eli Lilly to Invest USD 1 Billion in AI Co-Innovation Lab for Drug Discovery
Nvidia and Lilly will pioneer robotics and physical AI to accelerate and scale medicine discovery and production. Nvidia and Eli Lilly and Company announced on Monday the launch of what they call a first-of-its-kind AI co-innovation lab at the 44th J P Morgan Healthcare Conference, aimed at
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Jim Cramer Calls Nvidia, Eli Lilly Partnership 'Monumental Effort' To 'Speed Up' Critical Drug Creation - NVIDIA (NASDAQ:NVDA)
Jim Cramer highlighted the underappreciated synergy between Nvidia Corp. (NASDAQ:NVDA) and Eli Lilly And Co. (NYSE:LLY), calling their deep collaboration a "monumental effort" to revolutionize drug development that Wall Street is foolishly dismissing as a "gigantic sideshow." $1 Billion Validation
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Nvidia and Eli Lilly Are Partnering on a $1 Billion Lab. Here's What Investors Need to Know.
The high-powered duo is teaming up to build and equip a $1 billion research facility in California. In a corporate partnership many investors didn't see coming, chip maker Nvidia (NVDA +1.74%) and pharmaceutical company Eli Lilly (LLY +0.36%) say they are collaborating to build and operate a joint
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Nvidia, Eli Lilly Launch $1 Billion AI Lab To Build Meds - Eli Lilly and Co (NYSE:LLY), NVIDIA (NASDAQ:NVDA)
Nvidia Corp (NASDAQ:NVDA) and Eli Lilly and Co (NYSE:LLY) are launching a lab designed to apply advanced artificial intelligence to drug development. The collaboration will combine Lilly's expertise in biology, medicine, and manufacturing with Nvidia's leadership in AI, accelerated computing, and
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Nvidia Drives 70% Drug‑Discovery Cost Crash; Lilly Bets $1B - Eli Lilly and Co (NYSE:LLY), NVIDIA (NASDAQ:NVDA)
Nvidia Is Driving A 70% Cost Crash In Drug Discovery -- Lilly Just Bet $1 Billion On It The cost of drug discovery has always been time. Nvidia Corp (NASDAQ:NVDA) says it just crushed that cost by 70% -- and Eli Lilly And Co (NYSE:LLY) just put $1 billion behind the claim. At JPMorgan's
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Nvidia and Lilly form $1 billion AI partnership for drug discovery By Investing.com
SAN FRANCISCO - Nvidia (NASDAQ:NVDA) and Eli Lilly and Company announced today a five-year, $1 billion partnership to establish an artificial intelligence co-innovation laboratory focused on accelerating drug discovery and development. Nvidia, with its massive $4.47 trillion market capitalization
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Nvidia, Eli Lilly to Launch AI-Powered Co-Innovation Lab
Nvidia and Eli Lilly are partnering to launch a co-innovation lab to use Nvidia's artificial-intelligence and robotics expertise for drug discovery. The companies said Monday they would invest up to $1 billion in talent, infrastructure, and computing power, including Nvidia's Vera Rubin chips,
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Nvidia and Eli Lilly announced a $1 billion investment over five years to establish a co-innovation AI lab in the San Francisco Bay Area. The facility will combine Lilly's pharmaceutical expertise with Nvidia's AI capabilities to accelerate drug discovery through foundation models and continuous learning systems. The lab will use Nvidia's Vera Rubin chips and BioNeMo platform to enable 24/7 AI-assisted experimentation.
Nvidia and Eli Lilly Launch Joint Research Lab for AI Drug Discovery
Nvidia and Eli Lilly unveiled plans to invest up to $1 billion over five years in a co-innovation AI lab that aims to transform how pharmaceutical companies discover and develop new medicines
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. Announced at the JPMorgan Healthcare Conference on Monday, the collaboration brings together the world's most valuable listed firm with one of the pharmaceutical industry's leading players to tackle some of the most challenging problems in medicine development2
. The facility, set to open later this year in South San Francisco, will co-locate Lilly's top biologists and chemists alongside Nvidia's software engineers and AI model developers4
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Source: NVIDIA
Building a Continuous Learning System for Drug Discovery
The AI medical research lab will initially focus on creating a continuous learning system for drug discovery that connects Lilly's agentic wet labs with computational dry labs, enabling 24/7 AI-assisted experimentation
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. This scientist-in-the-loop framework will allow experiments, data generation, and AI model development to continuously inform and improve one another. According to Nvidia, when scientists go home for the evening, compute resources can continue preparing for the next day's experiments—essentially creating a continuous integration pipeline for AI-assisted drug research2
. "AI is transforming every industry, and its most profound impact will be in life sciences," said Jensen Huang, founder and CEO of Nvidia. "Nvidia and Lilly are bringing together the best of our industries to invent a new blueprint for drug discovery—one where scientists can explore vast biological and chemical spaces in silico before a single molecule is made"4
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Source: SiliconANGLE
Leveraging Vera Rubin Chips and BioNeMo Platform
The joint research lab will harness Nvidia's newly unveiled Vera Rubin compute platform, which promises a fivefold increase in performance over Nvidia's prior-generation Grace Blackwell GPUs
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. These AI chips, announced at CES last week, aren't expected to be available in significant numbers until the second half of this year, suggesting the lab will be among the first to access this cutting-edge hardware2
. The infrastructure will be built on Nvidia's BioNeMo platform, an open-source framework introduced in fall 2022 for building and training deep learning models for use in AI drug discovery2
. Teams will focus on building next-generation foundation models for drug discovery in biology and chemistry, leveraging unprecedented compute power and massive, high-quality data generation4
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Source: ET
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Expanding Beyond Drug Discovery to Manufacturing and Operations
While AI in the pharmaceutical industry applications for drug discovery remain the primary focus, researchers will also explore how AI can optimize clinical development, manufacturing, and commercial operations
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. Lilly is investigating Nvidia's Omniverse Robotics platforms and digital twins to optimize its manufacturing plants and increase production of high-demand drugs2
. The use of physical AI and robotics in the AI factory will help Lilly enhance its capacity for manufacturing optimization and strengthen supply chain reliability4
. This isn't Lilly's first major investment in accelerated computing—at GTC DC last October, the pharmaceutical giant revealed it had deployed a Blackwell Ultra-based SuperPOD with 1,016 B300 GPUs to support its exploration into computational biology and chemistry2
.Supporting the Broader Biotechnology Ecosystem
The $1 billion investment extends beyond the two companies' immediate needs. Lilly TuneLab, an AI and machine learning platform, will provide biotechnology companies with access to select Lilly models for drug discovery built on decades of proprietary data
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. The platform will include Nvidia Clara open foundation models for life sciences as part of a future workflow offering4
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. "Combining our volumes of data and scientific knowledge with Nvidia's computational power and model-building expertise could reinvent drug discovery as we know it," said David Ricks, chair and CEO of Lilly. "By bringing together world-class talent in a startup environment, we're creating the conditions for breakthroughs that neither company could achieve alone"4
. Nvidia's vice president of healthcare, Kimberly Powell, confirmed that both firms are dedicating incremental resources to the new facility, with its specific location to be announced in March3
. The collaboration positions both companies to accelerate drug discovery timelines and potentially slash the years it takes to bring new treatments to market, addressing a critical need in life sciences as drugmakers increasingly rely on sophisticated AI models to design and discover new therapies.References
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