47 分鐘
Building AI Infrastructure with Benchmark-backed Fireworks AI Co-Founder Lin Qiao "Autopilot" with Will Summerlin
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- 科技
In this episode, Will Summerlin is joined by Lin Qiao who shares her journey from leading the PyTorch team at Meta to founding Fireworks, a company focused on specialized, customized AI models for enterprise companies and startups. They explore the challenges of training and inference costs in building AI infrastructure, the potential of multimodal models, and the strategic shift from 'one model fits all' to a diverse set of specialized models. They also cover how to think about efficiency in model deployment, the advantages of open-source vs. closed-source and why her philosophy is opposite to OpenAI's.
RECOMMENDED PODCAST:
The AI Daily Brief If you’re looking for an edge to stay up to date on everything AI, subscribe to Nathaniel Whittemore's AI Daily Brief which delivers tight episodes covering all things AI from legislation to new technologies to the philosophical debates around generalized intelligence.
Spotify: https://open.spotify.com/show/7gKwwMLFLc6RmjmRpbMtEO
Apple: https://podcasts.apple.com/us/podcast/the-ai-daily-brief-formerly-the-ai-breakdown/id1680633614
LINKS:
https://fireworks.ai/
X/SOCIAL:
@WillSummerlinAI (Will)
@lqiao (Lin)
TIMESTAMPS:
(00:00) Preview and Intro
(02:22) From Meta to Building Fireworks AI
(04:29) Challenges and Innovations in AI at Scale
(06:53) Navigating the Tidal Wave of Generative AI
(08:27) The Evolution from Large to Specialized Models
(16:30) Open Source vs. Closed Source
(31:33) Optimizing AI from Training to Inference Costs
(37:54) The Future of Customization
(44:48) Customer Obsession
(46:20) Wrap
In this episode, Will Summerlin is joined by Lin Qiao who shares her journey from leading the PyTorch team at Meta to founding Fireworks, a company focused on specialized, customized AI models for enterprise companies and startups. They explore the challenges of training and inference costs in building AI infrastructure, the potential of multimodal models, and the strategic shift from 'one model fits all' to a diverse set of specialized models. They also cover how to think about efficiency in model deployment, the advantages of open-source vs. closed-source and why her philosophy is opposite to OpenAI's.
RECOMMENDED PODCAST:
The AI Daily Brief If you’re looking for an edge to stay up to date on everything AI, subscribe to Nathaniel Whittemore's AI Daily Brief which delivers tight episodes covering all things AI from legislation to new technologies to the philosophical debates around generalized intelligence.
Spotify: https://open.spotify.com/show/7gKwwMLFLc6RmjmRpbMtEO
Apple: https://podcasts.apple.com/us/podcast/the-ai-daily-brief-formerly-the-ai-breakdown/id1680633614
LINKS:
https://fireworks.ai/
X/SOCIAL:
@WillSummerlinAI (Will)
@lqiao (Lin)
TIMESTAMPS:
(00:00) Preview and Intro
(02:22) From Meta to Building Fireworks AI
(04:29) Challenges and Innovations in AI at Scale
(06:53) Navigating the Tidal Wave of Generative AI
(08:27) The Evolution from Large to Specialized Models
(16:30) Open Source vs. Closed Source
(31:33) Optimizing AI from Training to Inference Costs
(37:54) The Future of Customization
(44:48) Customer Obsession
(46:20) Wrap
47 分鐘