Proteins are molecular machines that must first assemble themselves to function. But how does a protein, which is produced as a linear string of amino acids, assume the complex three-dimensional structure needed to carry out its job? That's where Folding at Home comes in. Folding at Home is a sophisticated computer program that simulates the way atoms push and pull on each other, applied to the problem of protein dynamics, aka "folding". These simulations help researchers understand protein function and to design drugs and antibodies to target them. Folding at Home is currently studying key proteins from the virus that causes COVID-19 to help therapeutic development. Given the extreme complexity of these simulations, they require an astronomical amount of compute power. Folding at Hold solves this problem with a distributed computing framework: it breaks up the calculations in the smaller pieces that can be run on independent computers. Users of Folding at Home - millions of them today - donate the spare compute power on their PCs to help run these simulations. This aggregate compute power represents the largest super computer in the world: currently 2.4 exaFLOPS!Folding at Home was launched 20 years ago this summer in the lab of Vijay Pande at Stanford. In this episode, Vijay (now a general partner at a16z) is joined by his former student and current director of Folding at Home, Greg Bowman, an associate professor at Washington University in St. Louis, and Lauren Richardson. We discuss the origins of the Folding at Home project along with its connection to SETI@Home and Napster; also the scientific and technical advances needed to solve the complex protein folding and distributed computing problems; and importantly what does understanding protein dynamics actually achieve? Stay Updated:Find a16z on XFind a16z on LinkedInListen to the a16z Podcast on SpotifyListen to the a16z Podcast on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.
No persons identified in this episode.
This episode hasn't been transcribed yet
Help us prioritize this episode for transcription by upvoting it.
Popular episodes get transcribed faster
Other recent transcribed episodes
Transcribed and ready to explore now
SpaceX Said to Pursue 2026 IPO
10 Dec 2025
Bloomberg Tech
Don’t Call It a Comeback
10 Dec 2025
Motley Fool Money
Japan Claims AGI, Pentagon Adopts Gemini, and MIT Designs New Medicines
10 Dec 2025
The Daily AI Show
Eric Larsen on the emergence and potential of AI in healthcare
10 Dec 2025
McKinsey on Healthcare
What it will take for AI to scale (energy, compute, talent)
10 Dec 2025
Azeem Azhar's Exponential View
Reducing Burnout and Boosting Revenue in ASCs
10 Dec 2025
Becker’s Healthcare -- Spine and Orthopedic Podcast