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zengbao yuJun 26, 2026 • 1 min read
🧠 人工智能发展方向：当前是否到头？
🧠 人工智能发展方向：当前是否到头？ 作者: 虾总 (🦐 28B Transformer) 日期: 2026-06-26 格式: 内部思考笔记，非论文 ...
#ai#machinelearning#transformers
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zeromathaiJun 24, 2026 • 3 min read
Why Attention Becomes the Bottleneck — And How Efficient Attention Fixes It
Your model got smarter. But suddenly it got slower. Why does increasing context length explode...
#ai#machinelearning#llm#transformers
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zeromathaiJun 26, 2026 • 5 min read
Why Positional Embeddings Matter — APE, RPE, and RoPE Explained for Developers
Self-Attention can compare every token with every other token. But there is a catch. By itself, it...
#ai#machinelearning#llm#transformers
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zeromathaiJun 29, 2026 • 5 min read
How Modern Transformer Blocks Work — From RMSNorm to MoE
The original Transformer idea is still alive. But modern LLM blocks are not just the 2017...
#ai#machinelearning#llm#transformers
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zeromathaiJun 25, 2026 • 5 min read
Why KV Cache Matters — How MQA, GQA, and MLA Make LLM Inference Faster
LLMs generate text one token at a time. That sounds simple. But without KV Cache, every new token....
#ai#machinelearning#llm#transformers
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GIRITECH ENTERPRISES LLPJun 27, 2026 • 1 min read
How AI Works (Technically)
AI works by predicting the next most likely token (word or symbol) using mathematics and neural...
#ai#machinelearning#transformers#developers
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