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cover of episode Ep 49: OpenAI Researcher Noam Brown Unpacks the Full Release of o1 and the Path to AGI

Ep 49: OpenAI Researcher Noam Brown Unpacks the Full Release of o1 and the Path to AGI

2024/12/6
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Unsupervised Learning
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我观察到大型语言模型能力的扩展，包括预训练方面，仍然具有潜力。然而，每一次能力的提升都需要付出越来越高的成本。从GPT-2到GPT-4，模型所需的资源从数千美元到数百万美元不等，甚至可能达到数亿美元。虽然投入更多资金、资源和数据可以获得更好的模型，但这种扩展模式最终会受到经济效益的限制。当模型扩展到一定程度后，继续提升的成本将变得难以承受。因此，我认为存在一个软性的限制，即经济效益最终会限制模型规模的进一步扩大。 相比之下，我对测试时计算感到非常兴奋。我认为我们正处于类似GPT-2时代的早期阶段，当时模型的扩展规律非常清晰，只需简单地扩大规模就能获得更好的模型。虽然现在预训练的规模扩展变得更加困难，但测试时计算仍然处于早期阶段，有很大的提升空间。算法改进也更容易，存在大量低垂的果实。这并不意味着预训练已经完成，只是测试时计算的提升空间更大。 我认为测试时计算的潜力巨大。目前一次查询的成本大约为几分钱，但对于某些重要问题，人们可能愿意支付数百万美元甚至更多。这意味着成本可以提高数个数量级。此外，算法改进也可以进一步提升测试时计算的效率。因此，我认为测试时计算的潜力巨大，并且有很大的提升空间。

Deep Dive

Shownotes Transcript

Noam Brown, renowned AI researcher and key figure at OpenAI, joins us for a deep dive into the o1 release. Recorded just one day before o1’s full public debut, this episode explores the groundbreaking advancements and challenges behind this innovative test-time compute model.

We discuss the technical breakthroughs that set o1 apart, its unique capabilities compared to previous models, and how it disrupts traditional paradigms in AI development. Noam also shares insights into OpenAI’s approach to innovation, the economic realities of scaling AI, and what the future holds for the field.

 

[0:00] Intro

[0:50] Scaling Model Capabilities and Economic Constraints

[2:48] Excitement Around Test Time Compute

[4:50] Challenges and Future Directions in AI Research

[8:11] Noam Brown's Journey and OpenAI's Research Focus

[16:08] The Role of Specialized Models and Tools

[21:18] Unexpected Use Cases and Future Milestones

[23:44] Proof of Concept: o1's Capabilities

[24:48] The Bitter Lesson: Insights from Richard Sutton

[25:59] Scaffolding Techniques and Their Future

[27:56] Challenges in Academia and AI Research

[30:30] Evaluating AI Models: Metrics and Trends

[34:47] The Role of AI in Social Sciences

[39:39] AI Agents and Emergent Communication

[40:17] Future of AI Robotics

[41:13] Advancing Scientific Research with AI

[43:30] Quickfire

 

With your co-hosts: 

@jacobeffron 

  • Partner at Redpoint, Former PM Flatiron Health

 

@patrickachase 

  • Partner at Redpoint, Former ML Engineer LinkedIn

 

@ericabrescia 

  • Former COO Github, Founder Bitnami (acq’d by VMWare)

 

@jordan_segall 

  • Partner at Redpoint