IEEE

Computational Caching-Empowered Collaborative LLM Inference Framework in VEC Networks

Abstract: The overwhelming scale of large language models (LLMs) exhausts the on-device communication and computation resources in vehicular networks, limiting its application in performing inference ...
Microsoft

TENET: An Efficient Sparsity-Aware LUT-Centric Architecture for Ternary LLM Inference On Edge

Ternary quantization has emerged as a powerful technique for reducing both computational and memory footprint of large language models (LLM), enabling efficient real-time inference deployment without ...
Gizmochina

Xiaomi MiMo-V2-Flash LLM Just Dropped: These Are the Most Interesting Things About It

Xiaomi has unveiled its most advanced open-source large language model to date, called MiMo-V2-Flash, as part of its expanding push into foundation AI. The new model focuses on high-speed performance ...
blockchain

AutoJudge Revolutionizes LLM Inference with Enhanced Token Processing

AutoJudge introduces a novel method to accelerate large language model inference by optimizing token processing, reducing human annotation needs, and improving processing speed with minimal accuracy ...
InfoQ

NVIDIA Dynamo Addresses Multi-Node LLM Inference Challenges

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...
Mashable

DeepSeek v3.2: What's new and how does it compare to ChatGPT?

Remember DeepSeek, the large language model (LLM) out of China that was released for free earlier this year and upended the AI industry? Without the funding and infrastructure of leaders in the space ...
IEEE

Efficient KV Cache Spillover Management on Memory-Constrained GPU for LLM Inference

Abstract: The rapid growth of model parameters presents a significant challenge when deploying large generative models on GPU. Existing LLM runtime memory management solutions tend to maximize batch ...
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, ...
9to5Mac

Apple shows how much faster the M5 runs local LLMs compared to the M4

A new post on Apple’s Machine Learning Research blog shows how much the M5 Apple silicon improved over the M4 when it comes to running a local LLM. Here are the details. A couple of years ago, Apple ...
Psychology Today

LLM Mind-Reading Discovery May Lead to Better Performance

The human brain vastly outperforms artificial intelligence (AI) when it comes to energy efficiency. Large language models (LLMs) require enormous amounts of energy, so understanding how they “think" ...