Remove AI Research Remove Inference Engine Remove Neural Network
article thumbnail

Meta AI Releases Meta’s Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models

Marktechpost

Researchers from Meta Fundamental AI Research (FAIR) have introduced the Open Materials 2024 (OMat24) dataset, which contains over 110 million DFT calculations, making it one of the largest publicly available datasets in this domain. If you like our work, you will love our newsletter.

article thumbnail

Refined Local Learning Coefficients (rLLCs): A Novel Machine Learning Approach to Understanding the Development of Attention Heads in Transformers

Marktechpost

Artificial intelligence (AI) and machine learning (ML) revolve around building models capable of learning from data to perform tasks like language processing, image recognition, and making predictions. A significant aspect of AI research focuses on neural networks, particularly transformers.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

DIFFUSEARCH: Revolutionizing Chess AI with Implicit Search and Discrete Diffusion Modeling

Marktechpost

Large Language Models (LLMs) have gained significant attention in AI research due to their impressive capabilities. Existing methods to address the challenges in AI-powered chess and decision-making systems include neural networks for chess, diffusion models, and world models.

article thumbnail

Setting Up a Training, Fine-Tuning, and Inferencing of LLMs with NVIDIA GPUs and CUDA

Unite.AI

According to NVIDIA's benchmarks , TensorRT can provide up to 8x faster inference performance and 5x lower total cost of ownership compared to CPU-based inference for large language models like GPT-3. This engine can then be used to perform efficient inference on the GPU, leveraging CUDA for accelerated computation.