transformer-architecture

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#transformer-architecture

@simplifyinAI: DeepSeek has dropped a fundamental rewrite of the Transformer architecture. And it solves the "identity crisis" that br…

X AI KOLs Timeline · 2026-05-09

DeepSeek has published a paper introducing mHC (Manifold-Constrained Hyper-Connections), a fundamental rewrite of the Transformer architecture that stabilizes large models by replacing standard residual connections with mathematically constrained multi-stream pathways.

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#transformer-architecture

@tetsuoai: Forty minutes of whiteboard. The full transformer architecture. Then open vim and write it in C.

X AI KOLs Timeline · 2026-05-08 Cached

A 40-minute walkthrough explains the complete Transformer architecture via whiteboard diagrams and demonstrates a practical implementation in C using Vim.

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#transformer-architecture

@AYi_AInotes: Mind blown—22-year-old founder open-sources what Anthropic kept locked away: the Claude Mythos black box

X AI KOLs Timeline · 2026-04-19 Cached

A 22-year-old founder claims to have cracked open the architecture black box of Anthropic’s Claude Mythos model via an open-source project, speculating it uses a recurrent-depth Transformer design instead of simply scaling parameters.

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#transformer-architecture

ResBM: a new transformer-based architecture for low-bandwidth pipeline-parallel training, achieving 128× activation compression [R]

Reddit r/MachineLearning · 2026-04-16

ResBM introduces a transformer-based architecture with residual encoder-decoder bottlenecks for pipeline-parallel training, achieving 128× activation compression while maintaining convergence. The work advances decentralized, internet-grade distributed training by reducing inter-stage communication overhead.

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#transformer-architecture

Three-Phase Transformer

Hugging Face Daily Papers · 2026-04-15 Cached

A research paper introducing Three-Phase Transformer (3PT), which applies Tesla's polyphase geometry to transformer architectures by organizing the residual stream into three 120° offset phases. The approach achieves 7.2% perplexity improvement on WikiText-103 with minimal parameters (0.00124% overhead) and 1.93× convergence speedup.

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#transformer-architecture

Motif-Video 2B: Technical Report

Hugging Face Daily Papers · 2026-04-14 Cached

Motif-Video 2B is a 2B parameter text-to-video generation model that achieves 83.76% on VBench, surpassing Wan2.1 14B while using 7x fewer parameters and trained on fewer than 10M clips with less than 100,000 H200 GPU hours. The model uses a specialized architecture with shared cross-attention and a three-part backbone to separate prompt alignment, temporal consistency, and detail refinement.

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