cover of episode #190 - AI scaling struggles, OpenAI Agents, Super Weights

#190 - AI scaling struggles, OpenAI Agents, Super Weights

2024/11/28
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Andrey Kurenkov
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Jeremie Harris
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@Andrey Kurenkov 认为，当前AI发展面临瓶颈，单纯依靠扩大模型规模、增加数据和计算能力的策略，其改进效果正在递减。他认为，这并非意味着AI发展停滞，而是意味着单纯的规模化方法已不足以持续提升AI性能，需要探索新的方法。他同时指出，AI代理工具的出现和多模态模型的发展是AI领域的重要趋势。 @Jeremie Harris 补充指出，AI发展的瓶颈在于工业基础设施，例如能源供应和计算集群规模难以满足快速发展的需求。他认为，单纯的规模化方法已达到极限，需要从工业层面解决能源和算力问题。他强调，当前AI研究的重点已转向后训练阶段，包括强化学习和影响时间缩放定律，这些技术与训练时间缩放定律相结合，能够进一步提升AI性能。

Deep Dive

Chapters
Discussions around the potential slowdown in AI development, focusing on challenges faced by OpenAI, Google, and Anthropic in building more advanced AI models.
  • Next-generation models from OpenAI, Google, and Anthropic are not meeting performance expectations.
  • Pure scaling approaches are becoming challenging due to diminishing returns.
  • The community is divided on whether this signals a wall in AI improvement or just a temporary plateau.

Shownotes Transcript

Our 190th episode with a summary and discussion of last week's big AI news!

Hosted by Andrey Kurenkov and Jeremie Harris.

Note from Andrey: this one is coming out a bit later than planned, apologies! Next one will be coming out sooner.
Feel free to email us your questions and feedback at contact@lastweekinai.com and/or hello@gladstone.ai

Read out our text newsletter and comment on the podcast at https://lastweekin.ai/.

Sponsors:

  • The Generator - An interdisciplinary AI lab empowering innovators from all fields to bring visionary ideas to life by harnessing the capabilities of artificial intelligence

In this episode:
* OpenAI's pitch for a $100 billion data center and AI strategy plan outlines infrastructure and regulatory needs, emphasizing AI's foundational role akin to electricity. 
* Google's Gemini model challenges OpenAI's dominance, showing strong performance in chatbot arenas alongside generative AI advancements. 
* DeepMind's AlphaFold3 gets open-sourced for academic use, while new chips from NVIDIA and Google show significant performance boosts. 
* Anthropic and TSMC updates highlight strategic funding, regulation influences, and the complex dynamics of AI hardware and international policy.

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