#大佬观点

at perplexity we are really excited about multi-agent collaboration! we recently explored a simple instantiation of this with advisor escalation from a local model to a remote frontier model, where we showed it can significantly boost the local model's performance. an alternative way i like to think about this: the local model becomes a **gateway** to remote models. its main job is to preprocess all the raw tokens, package them into fewer, more information-dense tokens, and send only those to the server. this preprocessing has several advantages: it reduces cost and latency, enables personalization, and allows privacy controls. already such approaches can save 50% of tokens, but imagine a future where 90%+ of tokens are processed locally and only 10% are sent to the server for the last-mile hardest reasoning. that is a 10x cost reduction and a much more pleasant UX due to low latency. training such a multi-agent system is not an easy problem and still requires a lot of research in multi-agent RL, but we are making good progress and actively hiring for this. if this sounds interesting please DM me

OpenAI and Anthropic are currently taking a third of the incremental world compute supply, and Dylan thinks that this will go up to half next year. At the current rate of physical compute scaling and algorithmic progress, we're a single-digit number of years away from having individual AI companies with a greater effective workforce than there are humans on the planet. So many forces are barrelling us towards centralization in AI - the economies of scale in training (where you get to amortize any learnings across billions of sessions), the fact that being slightly ahead allows you to better economize on ever-more-expensive compute. And this isn’t even accounting for the fact that eventually you’ll have models that are capable of learning from deployment and doing proper RSI One of the key questions of our age, in my view, is how we can have broad empowerment and control over AI despite the structural factors favoring centralization.

OpenAI decided to keep the chip team small and use AI for a an improvement loop Early stages of Hardware in the loop RSI?

HOW THE “AI DETECTOR” GRIFT WORKS—THE GATEKEEPERS OF KNOWLEDGE Here is the real game. These detectors are being sold to the university machine so it can protect its monopoly on knowledge. The academy has always controlled what counts as legitimate knowledge production. Now that AI threatens to let anyone generate competent text, the system reaches for tools that can taint anything not produced inside its approved channels as “AI Slop.” Flag the outsider writing. Flag the independent researcher. Flag the student who writes too cleanly or too formally. Keep the credentialed pipeline pure. Pantagram and its competitors sell that service while waving their elite resumes. Read this again and understand: AI threatens to let anyone generate competent text, the system reaches for tools that can taint anything not produced inside its approved channels as “AI Slop.” Read more below:

@charlieholtz so good!!! my agents have been using this for all their work since sunday and it's incredible. thanks for making it!