GTC—Powering a new era of computing, NVIDIA on Monday 18th of March 2024 announced that the NVIDIA Blackwell platform has arrived — enabling organizations everywhere to build and run real-time generative AI on trillion-parameter large language models at up to 25x less cost and energy consumption than its predecessor.
Transformers are at the forefront of modern artificial intelligence, powering systems that understand and generate human language. They form the backbone of several influential AI models, such as Gemini, Claude, Llama, GPT-4, and Codex, which have been instrumental in various technological advances. However, as these models grow in size & complexity, they often exhibit unexpected behaviors, some of which may be problematic. This challenge necessitates a robust framework for understanding and mitigating potential issues as they arise.
In natural language processing (NLP), researchers constantly strive to enhance language models’ capabilities, which play a crucial role in text generation, translation, and sentiment analysis. These advancements necessitate sophisticated tools and methods for evaluating these models effectively. One such innovative tool is Prometheus-Eval.
The Llama Impact Grants program offers $500,000 in grants to projects using Llama 2, an open-source large language model, to address significant challenges in education, the environment, and social innovation.
The key innovation behind QLoRA lies in its ability to backpropagate gradients through a frozen, 4-bit quantized pretrained language model into Low Rank Adapters (LoRA). The resulting model family, aptly named Guanaco, surpasses all previously released models on the Vicuna benchmark, achieving an impressive 99.3% of the performance level of ChatGPT. Notably, this feat is accomplished within a mere 24 hours of fine-tuning on a single GPU.
Hugging Face has recently introduced LeRobot, a machine learning (ML) model created especially for practical robotics use. LeRobot provides an adaptable platform with an extensive library for advanced model training, data visualization, and sharing. This release represents a major advancement in the goal of increasing robots’ usability and accessibility for a broad spectrum of users.
