@garrytan Despite his biases & flaws, he did some great reporting over his career. I’ll always feel nostalgia for the glory days of TV news.
I don’t know if we’ll see correspondents airdropped into war zones in this next era of the show.
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 🙏
https://t.co/mLuvbODJxA
@IanMalcolm84 No idea, but followers fluctuate a lot. X has a big target on its back: an open door to reach thousands of people with a few lines of code.
Grok Build tip of the day: worktrees!
If you're unfamiliar with worktrees, they're essentially lightweight copies of your repo, allowing you to run parallel agents within their own workspaces. Try it either in the home screen or using `grok -w`!