Speculative decoding accelerates large language model generation by allowing multiple tokens to be drafted swiftly by a lightweight model before being verified by a larger, more powerful one. This ...

Google Research has developed a new method that could make running large language models cheaper and faster. Here's what it has done. Large language models (LLMs) have taken the world by storm since ...

Just as people from different countries speak different languages, AI models also create various internal “languages” – a unique set of tokens understood only by each model. Until recently, there was ...

This figure shows an overview of SPECTRA and compares its functionality with other training-free state-of-the-art approaches across a range of applications. SPECTRA comprises two main modules, namely ...

Edge-Centric Generative AI: A Survey on Efficient Inference for Large Language Models in Resource-Constrained Environments ...

In a new paper titled Principled Coarse-Grained Acceptance for Speculative Decoding in Speech, Apple researchers detail an interesting approach to generating speech from text. While there are ...

“LLM decoding is bottlenecked for large batches and long contexts by loading the key-value (KV) cache from high-bandwidth memory, which inflates per-token latency, while the sequential nature of ...