Is the prevailing approach to Artificial General Intelligence (AGI) missing a crucial step – deep, focused specialization?
For the first time since co-founding Poolside, CEO Jason Warner & CTO Eiso Kant reunite on a podcast articulating their distinct vision for AI's future with our host, Conor Bronsdon. Poolside has intentionally diverged from general-purpose models, developing highly specialized AI meticulously designed for the specific, complex task of coding, viewing it as a direct and robust pathway towards achieving AGI, and revolutionizing how software is created.
Jason and Eiso dive deep into the core tenets of their strategy: an unwavering conviction in reinforcement learning through code execution feedback and the burgeoning power of synthetic data, which they believe will help expand the surface area of software by an astounding 1000x. They candidly discuss the "devil's trade" of data privacy, Poolside's commitment to enterprise-grade AI for high-consequence systems, and why true innovation requires moving beyond flashy demos to solve real-world, critical challenges.
Looking towards the horizon, they also share their insights on the evolving role of software engineers, where human agency, taste, and judgment become paramount in a landscape augmented by AI "coworkers." They also explore the profound societal implications of their work and the AI industry more generally, touching upon the "event horizon" of intelligent systems and the immense responsibility that comes with being at the forefront of this technological wave.
Chapters
00:00 Introduction and Guest Welcome
01:19 Founding of Poolside
02:56 Vision for AGI and Reinforcement Learning
05:36 Defining AGI and Its Implications
10:03 Training Models for Software Development
17:08 Scaling and Synthetic Data
20:12 Focus on High-Consequence Systems
26:17 Privacy and Security in AI Solutions
28:09 Earning Trust with Developers
31:08 Reinforcement Learning and Compute
34:29 The Vision for AI's Future
39:50 Will Developers Still Exist?
47:07 Poolside Cloud's Ambitions
49:37 Conclusion
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Website: poolside.ai
LinkedIn: Jason Warner
LinkedIn: Eiso Kant
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