ADL issues 'urgent call' alleging anti-Israel bias in 4 AI large language models
Artificial language models' responses to questions about Israel, the Jewish people, the Holocaust and more sets off alarm ...
New QwQ-32B AI Fully Tested : Small Open Source LLM Beats Deepseek R1
QwQ-32B challenges AI giants with innovative techniques, open-source accessibility, and exceptional reasoning capabilities.
Vibe Coding LangGraph Apps : Say Goodbye to Context Overload
Optimize your LLM applications with lm.txt and MCP – the ultimate tools for efficient, transparent, and scalable AI context ...
The Register on MSN1d
A closer look at Dynamo, Nvidia's 'operating system' for AI inference
GPU goliath claims tech can boost throughput by 2x for Hopper, up to 30x for Blackwell GTC Nvidia's Blackwell Ultra and ...
Sportschosun (English) on MSN4d
Seoul National University Hospital Develops Korea's First Korean Medical Giant Language Model (LLM)...Accuracy 86.2%
Seoul National University Hospital recently announced that it has developed the first Korean Medical Large Language Model ...
Aisera Introduces a Framework to Evaluate How Domain-Specific Agents Can Deliver Superior Value in the Enterprise
Aisera, a leading provider of Agentic AI for enterprises, announced today that it has completed a research study that introduces a new benchmarking framework for evaluating the performance of AI ...
InfoWorld10d
What is Llama? Meta AI’s family of large language models explained
Llama has evolved beyond a simple language model into a multi-modal AI framework with safety features, code generation, and ...
DIGITIMES11d
ByteDance open-sources COMET to boost MoE efficiency, accelerating LLM training by 1.7x
ByteDance's Doubao AI team has open-sourced COMET, a Mixture of Experts (MoE) optimization framework that improves large ...
GitHub14d
A Flexible Framework for Experiencing Cutting-edge LLM Inference Optimizations
KTransformers is a flexible, Python-centric framework designed with extensibility at its core ... is to serve as a flexible platform for experimenting with innovative LLM inference optimizations.
Chain-of-experts (CoE): A lower-cost LLM framework that increases efficiency and accuracy
Chain-of-experts chains LLM experts in a sequence, outperforming mixture-of-experts (MoE) with lower memory and compute costs.