Making LLMs Smart With Transformers: It’s A Really Big Deal

Here’s how: prior to the transformer, what you had was essentially a set of weighted inputs. You had LSTMs (long short term memory networks) to enhance backpropagation – but there were still some ...
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 ...
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 ...
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 ...
Mid-Day

How ChatGPT Works vs. Atomesus AI’s Hybrid Intelligence: A Clear Technical Comparison for India’s AI Future

ChatGPT’s transformer model vs Atomesus AI’s hybrid architecture: a technical comparison for enterprise AI use.
VentureBeat

Microsoft’s Differential Transformer cancels attention noise in LLMs

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