NVIDIA CEO Jensen Huang discusses the state of AI as we begin 2026, covering rapid improvements in reasoning, the profitability of inference, why AI will increase productivity without taking jobs, the future of robotics, the importance of open source, and which sectors are poised for their 'ChatGPT moment'.
Zhang Yuxuan from Z.ai details the technical roadmap behind the GLM-4.6 model series, which has achieved top performance on the LMSYS Chatbot Arena. The summary covers their 15T token data recipe, the SLIME framework for efficient agent RL, key lessons in single-stage long-context training, and the architecture of the multimodal GLM-4.5V model.
The experts discuss OpenAI's GPT-5.1, focusing on its shift towards conversational style and user experience over raw benchmarks. They contrast this with the release of Moonshot AI's Kimi K2 Thinking, a powerful open-source model that challenges the dominance of proprietary systems. Finally, they analyze the profound security, organizational, and cultural risks of Microsoft's plan to introduce 'agentic users' as autonomous employees in the enterprise.
David Sacks details the Trump administration's strategy for AI and crypto, focusing on unleashing permissionless innovation, combating regulatory capture, and winning the global AI race through infrastructure and open source, while warning against the rise of "Orwellian AI."
The panel discusses the shifting AI hardware landscape as Oracle and OpenAI bet on AMD, challenging Nvidia's dominance. They also analyze a US government report on the risks of the DeepSeek model, debate the viability of Reflection AI's new $2B open-source venture, and dissect the story of a VC fund replacing analysts with AI agents.
A deep dive into the latest AI model releases, including IBM's hyper-efficient Granite 4.0, Anthropic's code-focused Claude 4.5, and OpenAI's consumer-centric Sora 2. The discussion covers the strategic differentiation between major AI labs, the future of open-source, the rise of AI e-commerce agents, and the emerging cybersecurity challenges of social engineering AI.