Meta’s most popular LLM series is Llama. Llama stands for Large Language Model Meta AI. They are open-source models. Llama 3 was trained with fifteen trillion tokens. It has a context window size of ...
A cute-looking AI is quietly reshaping cybercrime. See how KawaiiGPT enables phishing and ransomware for anyone, and why ...
Department of Philosophy and Cognitive Science, Lund University, Lund, Sweden The use of Large Language Models (LLMs) such as ChatGPT is a prominent topic in higher education, prompting debate over ...
ZigFormer is a fully functional implementation of a transformer-based large language model (LLM) written in Zig programming language. It aims to provide a clean, easy-to-understand LLM implementation ...
[08/05] Running a High-Performance GPT-OSS-120B Inference Server with TensorRT LLM ️ link [08/01] Scaling Expert Parallelism in TensorRT LLM (Part 2: Performance Status and Optimization) ️ link [07/26 ...
IBM today announced the release of Granite 4.0, the newest generation of its homemade family of open source large language models (LLMs) designed to balance high performance with lower memory and cost ...
In this webcast, Dr. Mark Sherman summarizes the results of experiments that were conducted to see if various large language models (LLMs) could correctly identify problems with source code. Finding ...
Finding and fixing weaknesses and vulnerabilities in source code has been an ongoing challenge. There is a lot of excitement about the ability of large language models (LLMs, e.g., GenAI) to produce ...
Phage-host interaction prediction plays a crucial role in the development of phage therapy, particularly in combating antimicrobial resistance (AMR). Current in silico models often suffer from limited ...
Abstract: The use of SCADA and AMI systems in smart grid-based Industrial Internet-of-Things (SG-IIoT) networks for proper energy supply are noteworthy. Inaccurate energy load forecasts, cyber-threats ...
According to Stanford AI Lab, researchers have successfully optimized the classic K-SVD algorithm to achieve performance on par with sparse autoencoders for interpreting transformer-based language ...
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