@levie: If you want to know where all the tokens will get consumed in the future, here it is. Agent swarms will have massive im…

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Summary

Aaron Levie 借 Prime Intellect 的最新实验指出，AI 智能体群将是未来 token 消耗的主要场景，可在软件开发、网络安全、生命科学等企业领域并行协作，实现人类无法企及的执行方式，这也是未来需要 1000 倍算力的原因。Prime Intellect 的 Prime Agent 此前指挥超过 2000 个智能体在两周内用 Rust 重写自身，消耗了 2000 亿以上 GLM-5.3 token。

If you want to know where all the tokens will get consumed in the future, here it is. Agent swarms will have massive implications in a number of enterprise domains like software development, cyber, life sciences research, AI research, finance, and more. The ability to parallelize agents against a unified goal where the volume of work is large, or where the search space not entirely known upfront, is going to be massive. Agents can fan out and coordinate work together on a specific mission in completely different ways from what humans are able to do. Today even in the most resource-abundant organizations, your ability to parallelize work on most projects is quite limited. Humans run into constraints on being able to communicate with one another, share status, deal with conflicts in work, keep shared context, and so on. As AI models can handle larger context without getting confused, and as they’re able to communicate effectively across their work with shared infrastructure, they can avoid many of the pitfalls that people have. You can see how this can lead to not just faster execution of tasks, but qualitatively different outcomes in medicine, research or defending against cyber attacks, scientific and math discoveries, and so on. This is why we’re going to need 1,000X more compute.
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If you want to know where all the tokens will get consumed in the future, here it is. Agent swarms will have massive implications in a number of enterprise domains like software development, cyber, life sciences research, AI research, finance, and more.

The ability to parallelize agents against a unified goal where the volume of work is large, or where the search space not entirely known upfront, is going to be massive.

Agents can fan out and coordinate work together on a specific mission in completely different ways from what humans are able to do. Today even in the most resource-abundant organizations, your ability to parallelize work on most projects is quite limited. Humans run into constraints on being able to communicate with one another, share status, deal with conflicts in work, keep shared context, and so on.

As AI models can handle larger context without getting confused, and as they’re able to communicate effectively across their work with shared infrastructure, they can avoid many of the pitfalls that people have.

You can see how this can lead to not just faster execution of tasks, but qualitatively different outcomes in medicine, research or defending against cyber attacks, scientific and math discoveries, and so on. This is why we’re going to need 1,000X more compute.

Prime Intellect (@PrimeIntellect): Over two weeks, Prime Agent orchestrated a swarm of over 2,000 agents to rewrite itself in Rust.

With 10,000+ sandboxes, 200B+ GLM-5.3 tokens, and 16,000 agent-to-agent messages, this was our largest test yet of Prime Agent’s multi-agent capabilities and our infrastructure

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