如何进一步激发超大规模市场潜力？坚持惠民生和促消费、投资于物和投资于人紧密结合，努力提高国民经济循环质量和效率……
Since the initial release, community contributions have pushed data efficiency from ~2.4x to 5.5x against modded-nanogpt, more than doubling in a few days. The key changes are: shuffling at the start of each epoch, which had outsized impact on multi-epoch training; learned projections for value embeddings instead of separate embedding tables; swapping squared ReLU for SwiGLU activation; and ensembling multiple models. 10x data efficiency seems reachable in the short term. 100x might be feasible by the end of the year, given how many directions remain unexplored, but it will require serious exploration on the algorithms side.
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이란 “하메네이 시신, 기도 광장에 안치해 일반 공개”
手机上看 Bot 消息，让 Claude 改个小逻辑、跑测试，结果直接回传到 Telegram
The data annotators also work with transcriptions, where they are to check that the AI assistant in Meta’s glasses has answered users’ questions correctly.