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Lemurian Labs CEO Jay Dawani

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Manage episode 444555430 series 3321644
Content provided by Rob Stevenson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rob Stevenson or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Jay breaks down the critical role of software optimizations and how they drive performance gains in AI, highlighting the importance of reducing inefficiencies in hardware. He also discusses the long-term vision for Lemurian Labs and the broader future of AI, pointing to the potential breakthroughs that could redefine industries and accelerate innovation, plus a whole lot more.

Key Points From This Episode:

  • Jay’s diverse professional background and his attraction to solving unsolvable problems.
  • How his unfinished business in robotics led him to his current work at Lemurian Labs.
  • What he has learned from being CEO and the biggest obstacles he has had to overcome.
  • Why he believes engineers with a problem-solving mindset can be effective CEOs.
  • Lemurian Labs: making AI computing more efficient, affordable, and environmentally friendly.
  • The critical role of software in increasing AI efficiency.
  • Some of the biggest challenges in programming GPUs.
  • Why better software is needed to optimize the use of hardware.
  • Common inefficiencies in AI development and how to solve them.
  • Reflections on the future of Lemurian Labs and AI more broadly.

Quotes:

“Every single problem I've tried to pick up has been one that – most people have considered as being almost impossible. There’s something appealing about that.” — Jay Dawani [0:02:58]

“No matter how good of an idea you put out into the world, most people don't have the motivation to go and solve it. You have to have an insane amount of belief and optimism that this problem is solvable, regardless of how much time it's going to take.” — Jay Dawani [0:07:14]

“If the world's just betting on one company, then the amount of compute you can have available is pretty limited. But if there's a lot of different kinds of compute that are slightly optimized with different resources, making them accessible allows us to get there faster.” — Jay Dawani [0:19:36]

“Basically what we're trying to do [at Lemurian Labs] is make it easy for programmers to get [the best] performance out of any hardware.” — Jay Dawani [0:20:57]

Links Mentioned in Today’s Episode:

Jay Dawani on LinkedIn

Lemurian Labs

How AI Happens

Sama

  continue reading

110 episodes

Artwork

Lemurian Labs CEO Jay Dawani

How AI Happens

11 subscribers

published

iconShare
 
Manage episode 444555430 series 3321644
Content provided by Rob Stevenson. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Rob Stevenson or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Jay breaks down the critical role of software optimizations and how they drive performance gains in AI, highlighting the importance of reducing inefficiencies in hardware. He also discusses the long-term vision for Lemurian Labs and the broader future of AI, pointing to the potential breakthroughs that could redefine industries and accelerate innovation, plus a whole lot more.

Key Points From This Episode:

  • Jay’s diverse professional background and his attraction to solving unsolvable problems.
  • How his unfinished business in robotics led him to his current work at Lemurian Labs.
  • What he has learned from being CEO and the biggest obstacles he has had to overcome.
  • Why he believes engineers with a problem-solving mindset can be effective CEOs.
  • Lemurian Labs: making AI computing more efficient, affordable, and environmentally friendly.
  • The critical role of software in increasing AI efficiency.
  • Some of the biggest challenges in programming GPUs.
  • Why better software is needed to optimize the use of hardware.
  • Common inefficiencies in AI development and how to solve them.
  • Reflections on the future of Lemurian Labs and AI more broadly.

Quotes:

“Every single problem I've tried to pick up has been one that – most people have considered as being almost impossible. There’s something appealing about that.” — Jay Dawani [0:02:58]

“No matter how good of an idea you put out into the world, most people don't have the motivation to go and solve it. You have to have an insane amount of belief and optimism that this problem is solvable, regardless of how much time it's going to take.” — Jay Dawani [0:07:14]

“If the world's just betting on one company, then the amount of compute you can have available is pretty limited. But if there's a lot of different kinds of compute that are slightly optimized with different resources, making them accessible allows us to get there faster.” — Jay Dawani [0:19:36]

“Basically what we're trying to do [at Lemurian Labs] is make it easy for programmers to get [the best] performance out of any hardware.” — Jay Dawani [0:20:57]

Links Mentioned in Today’s Episode:

Jay Dawani on LinkedIn

Lemurian Labs

How AI Happens

Sama

  continue reading

110 episodes

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