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NVIDIA's NVLink and NVSwitch technologies boost large language model inference, enabling faster and more efficient multi-GPU processing. (Read More)
The investment includes modular data centers and high-performance AI infrastructure for advancements in deep neural networks and large language models.
Explore NVIDIA's strategies for deploying trillion-parameter AI models, including parallelism techniques and the Blackwell architecture. (Read More)
Apple has reportedly been luring experts from Google in its efforts to catch up with Big Tech companies in the race to develop and deploy high-level AI models.
NVIDIA announces the general availability of its Secure AI solution, focusing on protecting large language models with enhanced security features. (Read More)
Researchers from Microsoft Research and Peking University have developed groundbreaking methods to enhance LLMs' ability to follow complex instructions and generate high-quality graphic designs, showcasing significant advancements in AI operational efficiency. (Read More)
Big Tech firms Meta and Microsoft have teamed up to launch Llama 2, an open-source large language model from Meta that will feature on Microsoft’s Windows and cloud computing platform Azure. The pair announced the collaboration on July 18 saying Llama 2 was made free for research and commercial use while also being optimized to [...]
The post Meta and Microsoft launch open-source AI model Llama 2 appeared first on Crypto Breaking News.
A dwindling consumer interest in chatbots caused a drop in AI-sector revenues during the second business quarter of 2024.
Explore NVIDIA's methodology for optimizing large language models using Triton and TensorRT-LLM, while deploying and scaling these models efficiently in a Kubernetes environment. (Read More)
Explore the development and key learnings from NVIDIA's AI sales assistant, leveraging large language models and retrieval-augmented generation to streamline sales workflows. (Read More)
NVIDIA introduces new KV cache optimizations in TensorRT-LLM, enhancing performance and efficiency for large language models on GPUs by managing memory and computational resources. (Read More)
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