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· · 来源:tutorial资讯

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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iPhone 17e features the latest-generation A19 built with advanced 3-nanometer technology, delivering powerful performance. The faster, more efficient 6-core CPU — up to 2x faster than iPhone 11 — handles everything from simple tasks like scrolling through photos to advanced Apple Intelligence capabilities like Clean Up. The 4-core GPU with Neural Accelerators unlocks console-level gaming on the go, supporting demanding AAA titles and hardware-accelerated ray tracing for more realistic lighting and reflections. The upgraded 16-core Neural Engine is optimized for large generative models and, combined with Neural Accelerators built into each GPU, enables Apple Intelligence and other AI models to run faster than on the previous generation.