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The Best Way to Achieve AGI Is to Invent It

Nov 4, 2024

Pedro Domingos, a machine-learning pioneer and author, joins Martin Casado for an intriguing discussion on the quest for Artificial General Intelligence (AGI). They delve into the costs associated with scaling AI and the feasibility of reaching human-level intelligence without astronomical investments. The conversation also touches on the importance of embracing non-traditional perspectives to spark innovation, and Domingos shares insights from his satirical novel that critiques the intersection of AI and society, blending humor with deep philosophical questions.

38:02

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Pedro Domingos

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Quick takeaways

The journey towards achieving AGI necessitates innovative ideas beyond mere scaling, as traditional models may lead to diminishing returns.

The evolving role of large language models highlights both their potential and limitations, suggesting a need for significant advancements in understanding.

Deep dives

The Long Journey to AGI

The development of Artificial General Intelligence (AGI) is likened to Einstein's decade-long effort to formulate general relativity, highlighting the complexity and time required for groundbreaking advancements. Current AI research is characterized by rapid progress towards local optima, yet there is a growing belief that such advances will not lead to human-level intelligence without truly innovative ideas. While improvements in models, like making Transformers more efficient, can yield significant immediate benefits, they will ultimately not reach the full potential of AGI. Achieving just 10% progress toward AGI could still have a transformative impact on society, underscoring the importance of a robust research direction.

Intro

2min

Navigating the AI Research Landscape

13min

Comparative Growth: AI and the Early Internet

3min

Nobel Prize and AI: Implications and Controversies

8min

Math and Creativity in AI

3min

Challenging Consensus: The Role of Non-Traditional Perspectives in AI

2min

Satire and Society: The AI Narrative

7min

Longtime machine-learning researcher, and University of Washington Professor Emeritus, Pedro Domingos joins a16z General Partner Martin Casado to discuss the state of artificial intelligence, whether we're really on a path toward AGI, and the value of expressing unpopular opinions. It's a very insightful discussion as we head into an era of mainstream AI adoption, and ask big questions about how to ramp up progress and diversify research directions.

Here's an excerpt of Pedro sharing his thoughts on the increasing cost of frontier models and whether that's the right direction:

"if you believe the scaling laws hold and the scaling laws will take us to human-level intelligence, then, hey, it's worth a lot of investment. That's one part, but that may be wrong. The other part, however, is that to do that, we need exploding amounts of compute.

"If if I had to predict what's going to happen, it's that we do not need a trillion dollars to reach AGI at all. So if you spend a trillion dollars reaching AGI, this is a very bad investment."

Learn more:

The Master Algorithm

2040: A Silicon Valley Satire

The Economic Case for Generative AI and Foundation Models

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Pedro Domingos

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