Databricks 推出 Astra 模型，工程师复杂任务效率提升 60%
源:https://t.co/ykphYTsAmW
Databricks 给工程师用上了 Astra，复杂任务效率提升 60%，比 Opus 5 和 Sol 5.6 强，但日常任务没明显提升，适合挑复杂活儿用。
Databricks 为工程师推出 Astra 模型，该模型在复杂系统设计等任务上显著优于前代模型 Opus 5 和 Sol 5.6，使工程师整体编码时间增加约 60%。公司通过试点测试了约 200 名用户，并使用 Unity Gateway 进行分组实验。工程师可混合使用不同模型，Astra 用于复杂任务，其他模型用于日常任务。
源:https://t.co/ykphYTsAmW
源: x.com/pwendell/statu… Patrick Wendell @pwendell Today we rolled out Astra to every engineer at Databricks (N=~3500). Some notes that may be helpful to others: 1. Astra unambiguously out performs our previous highest-end models (Opus 5, Sol 5.6) on highly complex tasks, especially those related to high level system design or long range horizontal tasks. 2. Engineers given Astra increased overall coding spend by around 60% compared to baseline. 3. It is not clear Astra meaningfully improves on medium/low complexity coding tasks compared to earlier models. We suspect those tasks are mostly saturated (i.e. perfectly executed) by existing models. 4. We learned above by piloting Astra with around 200 users to gain signal on both quality and cost. We use Unity Gateway to do cohort-based experiments for all new models. 5. We give engineers a sub-budget specific to Astra to encourage them to use Astra selectively on complex tasks while preferring lower cost models for everyday tasks. Our engineers are able to mix-and-match tools and models within their overall budget envelope (we also allow for increased budgets through various mechanisms). These budgets are defined in Unity Gateway and regularly revisited. Note: We do not have robust comparisons of Astra-vs-Fable because we have net yet rolled out Fable widely due to data retention policies. 🔗 View Quoted Tweet 💬 0 🔄 0 ❤️ 0 👀 221 ⚡
