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Mistral, a French AI start-up, has announced a new model for its API along with an Azure partnership. Mistral Large excels at multilingual tasks, is within a few percent of GPT-4 on MMLU, and generally has powerful performance. The startup also added a new mistral-small model to its API.
Scale AI has received a one-year contract to develop a testing and evaluation framework for the Pentagon's large language AI models. The company aims to bolster safe AI deployment and robustness within military applications. The project involves creating specialized datasets for model assessment and an iterative process to refine AI systems for secure environments. This collaboration will help the Department of Defense understand and responsibly deploy generative AI technology.
Meta has proposed a 350m parameter language model with strong reasoning performance, even approaching Llama 7B on correctness in API function calling tasks. The model has not been released, but the innovation in fixed parameter models is worth exploring.
ConceptMath is a new bilingual benchmark for testing LLMs’ math skills in both English and Chinese. It's unique because it breaks down math problems into specific concepts, allowing for a more detailed assessment of an AI's strengths and weaknesses in math.
DreamRec introduced a novel 'learning-to-generate' approach to sequential recommendation where instead of the traditional method of classifying user preferences from a mix of positive and negative items, it creates an 'oracle' item that represents the ideal next choice for the user.
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FlowMDM is a new model for generating long, continuous human motion sequences from text descriptions. This first-of-its-kind diffusion-based model uses Blended Positional Encodings for realistic motion creation without extra denoising steps, excelling in accuracy and realism on key datasets.
The VSP-LLM framework introduces a new approach to visual speech recognition and translation by integrating LLMs. It efficiently processes video inputs by deduplicating embedded visual features and employing Low-Rank Adaptors for cost-effective training.
This project introduces a framework for Multi-View 3D reconstruction that doesn't require prior knowledge of scene depth. It intelligently selects the most relevant source frames, making it applicable to diverse scenarios including large-scale outdoor and top-view building environments.
Spiking Neural Networks is a new efficient model for autonomous vehicles. It achieves high performance with up to 85% less energy.
San Francisco Compute Company is now offering the world's cheapest H100 training clusters with flexible short-term rental options, targeting customers needing intensive compute for AI model training without long-term commitments. Its first cluster, Angel Island, is currently online, with another, Bay Bridge, coming soon. SF Compute's model is unprecedented as it prioritizes accessibility and affordability for AI startups without demanding lengthy contracts.
Axolotl is a powerful library for fine-tuning language models.
Craft ads that click and convert.
A powerful merged and tuned model that scores well in elo and static benchmarks. It is designed for multi-turn and instruction following tasks.