#training
The bidirectional design idea turns agent evaluation data into training rewards, a concrete recipe for closing the loop between deployment and model improvement. Researchers and framework builders can experiment with reward signals derived from real agent traces rather than static benchmarks. The framing also clarifies where projects like PyTorch and the Agentic AI Foundation sit relative to each other in the stack.
一条关于 DeepSeek V4.1 的训练观察：没做 dense warmup 也能训练顺利，作者解释了为什么这种设计值得 scale up。
For developers looking to prepare for technical interviews, this article offers a structured overview of core LLM optimization concepts, including KV cache management and speculative decoding, which are critical for improving model efficiency.
朋友，Fireworks 新增了 GLM-5.3 的训练支持，这个模型适合做复杂编码和长时程代理，你可以在他们的专用平台上试试。
摩尔线程把256张GPU连成一体，延迟压到亚微秒，两柜顶别人一堆。还跑通了万亿参数MoE，实打实的国产算力。
