Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten ...
Through systematic experiments DeepSeek found the optimal balance between computation and memory with 75% of sparse model ...
Generative AI applications don’t need bigger memory, but smarter forgetting. When building LLM apps, start by shaping working memory. You delete a dependency. ChatGPT acknowledges it. Five responses ...
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 ...
A new technical paper titled “Mind the Memory Gap: Unveiling GPU Bottlenecks in Large-Batch LLM Inference” was published by researchers at Barcelona Supercomputing Center, Universitat Politecnica de ...
The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and ...
SNU researchers develop AI technology that compresses LLM chatbot ‘conversation memory’ by 3–4 times
In long conversations, chatbots generate large “conversation memories” (KV). KVzip selectively retains only the information useful for any future question, autonomously verifying and compressing its ...
Large language models (LLMs) like GPT and PaLM are transforming how we work and interact, powering everything from programming assistants to universal chatbots. But here’s the catch: running these ...
Imagine having a conversation with someone who remembers every detail about your preferences, past discussions, and even the nuances of your personality. It feels natural, seamless, and, most ...
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