GPT-6 Astra引入上下文压缩技术
Highly recommended. It's not obvious, but a bottleneck in even the most powerful models, like GPT-6 ...
GPT-6 Astra出了新配置，能解决上下文膨胀问题，让模型在长任务中保持记忆。
GPT-6 Astra模型引入了新的上下文压缩配置，解决了大模型中的上下文膨胀问题。该技术允许模型在长时间运行的任务中保持持久性，避免重复压缩上下文信息。Gabriel Chua表示，Astra能够在上下文窗口填满时保存和检索上下文，保留累积的细节。
Highly recommended. It's not obvious, but a bottleneck in even the most powerful models, like GPT-6 ...
Highly recommended. It's not obvious, but a bottleneck in even the most powerful models, like GPT-6 Astra, is context bloat and compaction. This new config can help keep Astra persistent across long-running tasks. If it helps, here is a little visual summary courtesy of GPT-6 Astra. Gabriel Chua @gabrielchua "With Astra, we’re introducing a new way for Codex to preserve and retrieve context when the context window fills ... In Codex, Astra can keep notes across context windows, preserving accumulated details without repeatedly compressing them into a single summary..." See the next post on how to enable it 👇 🔗 View Quoted Tweet 💬 7 🔄 4 ❤️ 26 👀 3894 📊 12 ⚡
