Jev 引入新模型架构优化通用分类任务
In my mind, the excitement and potential around Jev is related to that of model routing and posttrai...
Jev 是一个新模型架构，专门为通用分类任务设计，能优化模型性能。
Jev 是一种新的模型架构，旨在优化通用分类任务。它通过模型路由和后训练技术，在准确率、成本和延迟之间取得平衡。这种架构可以协调前沿模型和开源模型，并针对特定任务进行微调。
In my mind, the excitement and potential around Jev is related to that of model routing and posttrai...
In my mind, the excitement and potential around Jev is related to that of model routing and posttraining - in a world where intelligence is abundant, how do you best optimize it for a specific task? By optimizing the harness, model weights, or model architecture itself, you can push the frontier of accuracy / cost / latency - model routing orchestrates frontier and open weight models at the harness layer - posttraining tunes an existing model towards a given task evals - jev introduces an entire new model architecture that is optimized for the class of tasks that fall under generalized classification I see a world where frontier intelligence direct and orchestrate knowledge work, and then perform any of these optimizations and more to help optimize various subtasks 💬 1 🔄 0 ❤️ 0 👀 395 📊 1 ⚡
