DeepSeek’s conditional memory fixes silent LLM waste: GPU cycles lost to static lookups

Through systematic experiments DeepSeek found the optimal balance between computation and memory with 75% of sparse model ...
SDxCentral

AI inference crisis: Google engineers on why network latency and memory trump compute

Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
ExtremeTech

Microsoft's New Compact 1-Bit LLM Needs Just 400MB of Memory

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Hosted on MSN

AI tech can compress LLM chatbot conversation memory by 3–4 times

Seoul National University College of Engineering announced that a research team led by Professor Hyun Oh Song from the Department of Computer Science and Engineering has developed a new AI technology ...
Semiconductor Engineering

Pooling CPU Memory for LLM Inference With Lower Latency and Higher Throughput (UC Berkeley)

“The rapid growth of LLMs has revolutionized natural language processing and AI analysis, but their increasing size and memory demands present significant challenges. A common solution is to spill ...
InfoWorld

What is LangSmith? Tracing and debugging for LLMs

In my recent introduction to LangChain, I touched briefly on LangSmith. Here, we’ll take a closer look at the platform, which works in tandem with LangChain and can also be used with other LLM ...
Digi Times

Taiwan's Phison lends memory expertise to slingshot DeepMentor's LLM training

Taiwan's AI startup DeepMentor has teamed up with memory giant Phison Electronics to edge training servers for training large-scale language models (LLM). Save my User ID and Password Some subscribers ...