麻省理工学院与Asari AI研究人员开发了EnCompass框架，帮助程序员更高效地构建AI智能代理。该框架通过自动回溯和并行搜索功能，减少了高达80%的编程工作量。EnCompass将搜索策略与代理工作流程分离，让开发者能轻松测试不同搜索策略，显著提升AI代理在代码翻译、规则发现等任务中的表现，为大规模应用奠定基础。

Whether you're a scientist brainstorming research ideas or a CEO hoping to automate a task in human resources or finance, you'll find that artificial ...

Pocket TTS delivers high-quality text-to-speech on standard CPUs. No GPU, no cloud APIs. It is the first local TTS with voice ...

In 2026, artificial intelligence skills sit on the short list for promotions in analytics, product, and operations. Teams want people who can frame the right problem, choose workable models, and ...

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As AI coding tools become more sophisticated, engineers at leading AI companies are stopping writing code altogether ...

Naming their tech MorphoChrome, the team from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) has ...

For the last few years, the narrative around Generative AI in science has largely focused on administrative efficiency – ...

不管大模型宣称自己的上下文窗口有多大，它们处理超长文本时，都会遇到文本越长，模型对早期信息的记忆越模糊，推理性能直线下滑的问题。 比如，GPT-5.2-Codex采用的就是窗口内的原生上下文压缩技术，在持续数周的大型代码仓库协助任务中保持全上下文信息。

在人工智能领域，处理超长文本一直是一个棘手的问题。MIT计算机科学与人工智能实验室（CSAIL）最近发布的研究成果，提出了一种名为递归语言模型（RLM）的新方法，成功让大模型在不改变架构的情况下，解锁了千万级的上下文处理能力。这一创新将极大提高如GPT-5和Qwen-3等顶尖模型的推理效率，开启了大模型处理文本的新纪元。

Not everyone can declare themselves “benevolent dictator for life” of a company, but such was the nature of Guido van Rossum, the Dutch programmer who invented an entire programming language from ...