Ethan He 对 AI 前沿的预判直击要害，做视频生成、智能体或世界模型的开发者看完会有启发——尤其是关于迭代速度和智能体方向的洞察，值得点开细品。
Ethan He 在 Latent Space 播客中分享了对视频生成、世界模型、LLM、智能体和持续学习的看法。他认为视频模型的大部分智能来自语言而非视频数据，idea-to-code 的速度已经很快，瓶颈在于计算资源。他强调迭代速度在模型开发中几乎压倒一切，下一个飞跃将是视频智能体而非更好的视频模型。他还预测扩散模型将成为 AGI 的前端，LLM 作为后端，生成式 UI 将取代 HTML/CSS，物理具身可能成为强大 AI 的工具。
@EthanHe_42 @xai @nvidia more from Ethan: https://t.co/glYeRX4ste
@EthanHe_42 @xai @nvidia more from Ethan: x.com/EthanHe_42/sta… Ethan He @EthanHe_42 In @latentspacepod podcast, I shared my view on video generation, world models, LLMs, agents, continual learning and where the next frontier is. 1. Video models get most of their intelligence from language, not from video data. 2. Idea-to-code is fast now. The bottleneck is back to having enough compute to try every idea. 3. Iteration speed beats almost everything else in model development. 4. The next leap won't be a better video model. It'll be a video agent. 5. Diffusion will be the frontend of AGI, the LLM the backend. Generative UI will replace HTML/CSS: user intent straight to pixels. 6. Physical embodiment may become a tool a powerful AI picks up. Robotics may get solved by video-capable LLMs. 7. Continual learning may look like models that manage their own context, and even rewrite their own harness at test time. Thanks @swyx and @vibhuuuus for having me 🙏 youtube.com/watch?v=jPtQlI… A 🔗 View Quoted Tweet 💬 0 🔄 0 ❤️ 1 👀 193 ⚡