Manifold-Constrained Hyper-Connections: The Architectural Breakthrough That Might Redefine LLM Training

If mHC scales the way early benchmarks suggest, it could reshape how we think about model capacity, compute budgets and the ...
VentureBeat

New LLM optimization technique slashes memory costs up to 75%

Researchers at the Tokyo-based startup Sakana AI have developed a new technique that enables language models to use memory more efficiently, helping enterprises cut the costs of building applications ...
SiliconANGLE

Kneron’s new AI chip brings LLM performance out of the cloud and onto devices

San Diego-based startup Kneron Inc., an artificial intelligence company pioneering neural processing units for the edge, today announced the launch of its next-generation KL1140 chip Founded in 2015, ...
InfoQ

Meta Open-Sources Byte Latent Transformer LLM with Improved Scalability

Meta open-sourced Byte Latent Transformer (BLT), an LLM architecture that uses a learned dynamic scheme for processing patches of bytes instead of a tokenizer. This allows BLT models to match the ...
Semiconductor Engineering

Transformers At The Edge: Efficient LLM Deployment

Since the groundbreaking 2017 publication of “Attention Is All You Need,” the transformer architecture has fundamentally reshaped artificial intelligence research and development. This innovation laid ...
VentureBeat

Microsoft’s Differential Transformer cancels attention noise in LLMs

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