AI Vibe Check: The Actual Bottleneck In Research, SSI’s Mystique, & Spicy 2026 Predictions

In a panel discussion featuring Ari Morcos, Jacob, and Rob Toews, the group analyzes the current state and future trends of AI. They discuss the possibility of plateauing in LLMs, the shift towards closed-source models, and the rise of Chinese AI innovation. The conversation covers the potential of continual learning, recursive self-improvement, and the importance of data efficiency. They also debate the implications of recent events, including OpenAI's "code red," the Disney partnership, and the restrictions on chip sales to China. The group concludes with bold predictions for 2026, including a potential change in OpenAI's leadership and the dominance of Chinese open-source models.

Outlines

Part 1: AI Trends, Plateaus, and Research

Part 2: Lab Dynamics and Market Competition

Part 3: Policy, Infrastructure, and Future Outlook

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Unsupervised Learning with Jacob Effron

Part 1: AI Trends, Plateaus, and Research

Introduction to Neolabs, Model Progress, and NeurIPS Reflections

LLM Plateauing, the Role of RL, and Enterprise Adoption

Continual Learning, Recursive Self-Improvement, and Data Efficiency

Part 2: Lab Dynamics and Market Competition

NeoLabs, SSI, and the Bull Case for New AI Companies

Market Dynamics, OpenAI's "Code Red," and Google's Advantages

OpenAI's Partnerships, Meta's Superintelligence Lab, and Chip Restrictions on China

Part 3: Policy, Infrastructure, and Future Outlook

Chip Policy, Amazon's NovaForge, and Enterprise AI in 2026

End-of-Year Reflections and Predictions for 2026

AI Vibe Check: The Actual Bottleneck In Research, SSI’s Mystique, & Spicy 2026 Predictions

Unsupervised Learning with Jacob Effron

Part 1: AI Trends, Plateaus, and Research

00:00Introduction to Neolabs, Model Progress, and NeurIPS Reflections

Introduction to Neolabs, Model Progress, and NeurIPS Reflections

07:51LLM Plateauing, the Role of RL, and Enterprise Adoption

LLM Plateauing, the Role of RL, and Enterprise Adoption

16:13Continual Learning, Recursive Self-Improvement, and Data Efficiency

Continual Learning, Recursive Self-Improvement, and Data Efficiency

Part 2: Lab Dynamics and Market Competition

28:40NeoLabs, SSI, and the Bull Case for New AI Companies

NeoLabs, SSI, and the Bull Case for New AI Companies

37:38Market Dynamics, OpenAI's "Code Red," and Google's Advantages

Market Dynamics, OpenAI's "Code Red," and Google's Advantages

45:08OpenAI's Partnerships, Meta's Superintelligence Lab, and Chip Restrictions on China

OpenAI's Partnerships, Meta's Superintelligence Lab, and Chip Restrictions on China

Part 3: Policy, Infrastructure, and Future Outlook

57:26Chip Policy, Amazon's NovaForge, and Enterprise AI in 2026

Chip Policy, Amazon's NovaForge, and Enterprise AI in 2026

1:03:39End-of-Year Reflections and Predictions for 2026

End-of-Year Reflections and Predictions for 2026