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350: What Comes After AGI? A Vision for a Freedom-Based Economy with Jad Tarifi, Co-Founder of Integral AI
Manage episode 502363550 series 2986762
Dr. Jad Tarifi is the co-founder of Integral AI, a company he launched in 2021 after holding senior AI roles at Google. He earned his PhD in Computer Science and AI from the University of Florida and completed his undergraduate studies at the University of Waterloo. A returning guest to the podcast, Jad is a leading thinker on world models in AI and often shares insights on the science of longevity and the future of intelligence.
In this conversation, we discuss:
- Why Jad believes the goal of AGI isn't intelligence but freedom, and how that redefinition reframes both ethics and alignment
- The role of world models in achieving AGI, and why video prediction alone isn't enough for robust, reliable reasoning
- What it means to design AI that can autonomously learn new skills with minimal energy and data, matching or exceeding human learning efficiency
- How Integral AI is building AGI-capable models by focusing on unsupervised abstraction and embodied, open-ended agents
- How Jad defines superintelligence and what it reveals about the evolving relationship between humans and machines
- A glimpse into Integral’s long-term roadmap, including recursive superfactories and post-AGI economies
Resources:
305 에피소드
Manage episode 502363550 series 2986762
Dr. Jad Tarifi is the co-founder of Integral AI, a company he launched in 2021 after holding senior AI roles at Google. He earned his PhD in Computer Science and AI from the University of Florida and completed his undergraduate studies at the University of Waterloo. A returning guest to the podcast, Jad is a leading thinker on world models in AI and often shares insights on the science of longevity and the future of intelligence.
In this conversation, we discuss:
- Why Jad believes the goal of AGI isn't intelligence but freedom, and how that redefinition reframes both ethics and alignment
- The role of world models in achieving AGI, and why video prediction alone isn't enough for robust, reliable reasoning
- What it means to design AI that can autonomously learn new skills with minimal energy and data, matching or exceeding human learning efficiency
- How Integral AI is building AGI-capable models by focusing on unsupervised abstraction and embodied, open-ended agents
- How Jad defines superintelligence and what it reveals about the evolving relationship between humans and machines
- A glimpse into Integral’s long-term roadmap, including recursive superfactories and post-AGI economies
Resources:
305 에피소드
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