🚨 AI News | TestingCatalog@testingcatalog
38AI 编辑部评分,满分 100
2026-08-06 07:02· 28分钟前
AI 导读

Prime Intellect 推出 Prime Agent,一个面向编码和长时自主任务的自改进 RLM 框架,在 ARC-AGI-3 上得分 95.5%。该框架将上下文视为变量、子代理委派视为 REPL 内的函数调用,并允许代理对其提示词、技能、记忆和子代理状态进行 CRUD 操作,实现自我修改。

Prime Intellect announced Prime Agent, a new self-improving RLM harness for coding and long-running autonomous tasks.

Prime Agent scored 95.5% on ARC-AGI-3! 🤯

The Recursive Language Model (RLM) treats context as a variable and subagent delegation as function calls inside a REPL.

Continual Harness treats the harness's own state, abstracted as its prompts, skills, memory, and sub-agents, as something the agent can create, read, update, and delete (CRUD) from its own trajectory.

The next level of abstraction 👀

Prime IntellectIntroducing Prime Agent: A self-improving RLM harness for coding and long-running autonomous tasks. Designed to be both token-efficient and expressive through p...

来源:🚨 AI News | TestingCatalog · x.com

🚨 AI News | TestingCatalog · @testingcatalog · X·2026-08-06 07:02·28分钟前
AI 导读

Prime Intellect 推出 Prime Agent,一个面向编码和长时自主任务的自改进 RLM 框架,在 ARC-AGI-3 上得分 95.5%。该框架将上下文视为变量、子代理委派视为 REPL 内的函数调用,并允许代理对其提示词、技能、记忆和子代理状态进行 CRUD 操作,实现自我修改。

Prime Intellect announced Prime Agent, a new self-improving RLM harness for coding and long-running autonomous tasks.

Prime Agent scored 95.5% on ARC-AGI-3! 🤯

The Recursive Language Model (RLM) treats context as a variable and subagent delegation as function calls inside a REPL.

Continual Harness treats the harness's own state, abstracted as its prompts, skills, memory, and sub-agents, as something the agent can create, read, update, and delete (CRUD) from its own trajectory.

The next level of abstraction 👀

Prime IntellectIntroducing Prime Agent: A self-improving RLM harness for coding and long-running autonomous tasks. Designed to be both token-efficient and expressive through p...

来源:🚨 AI News | TestingCatalog· x.com