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Why Nvidia, Google And Microsoft Are Betting Billions On Biotech’s AI Future

Mar 13, 2024 - forbes.com
Tech giants like Nvidia, Google DeepMind, Microsoft, Amazon, and Salesforce are increasingly investing in AI for drug discovery and digital biology, seeing it as the next frontier in technology. Nvidia, which has built a $60 billion a year business on the AI boom, has been investing heavily in drug discovery, with its VP of Healthcare, Kimberly Powell, stating that the company aims to provide chips, cloud infrastructure, and other tools to more biotech firms. Similarly, Google DeepMind's AlphaFold model, a tool for predicting protein structures, has been used for various applications, from developing a "molecular" syringe to researching pesticide-independent crops.

The interest in biotech is driven by the potential of AI to handle the complexity of the field, especially in predicting protein structures based on amino acid sequences. This ability can be used to design everything from new drugs to improved crops and biodegradable plastics. However, despite the promise and hype around AI drug discovery, challenges remain, including the lengthy process of getting drugs through clinical trials and the need for high-quality training data for AI models.

Key takeaways:

  • Major tech companies like Nvidia, DeepMind, Microsoft, and Amazon are increasingly investing in biotech and drug discovery, viewing it as the next frontier in artificial intelligence.
  • Nvidia's CEO Jensen Huang has touted digital biology as the “next amazing revolution” in technology, and the company has been investing heavily in drug discovery firms.
  • DeepMind's AlphaFold model, a tool for predicting protein structures, has been used in significant research projects, including the development of a 'molecular' syringe and crops less dependent on pesticides.
  • Despite the promise and hype around AI in drug discovery, there are challenges including the lengthy process of getting drugs through clinical trials and the need for high-quality training data for AI models.
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