Mobius Labs hat dies direkt geteilt
🚀 Optimizing AI Inference with Efficient and Multimodal Models As OpenAI shifts compute towards inference time, the demand for efficient and compact models has never been greater. At Mobius Labs, we’re addressing this need through our open-source solutions for quantization, sparsification, and fast kernels, all designed to enhance performance as Chain-of-Thought (CoT) processes increase inference compute requirements. 🔍 Our Focus Includes: • Small Models: Streamlining model sizes without compromising performance. • QV Cache Optimization: Enhancing caching mechanisms for faster inference. • Quantized Distilled Models: Developing robust, quantized models that maintain high accuracy and efficiency. • Multimodality: Integrating different perceptions to enable models to process and understand diverse data types seamlessly. • Long-Term Memory with RAG Systems: Leveraging Retrieval-Augmented Generation (RAG) to interact with long-term memory, enhancing the model’s ability to provide contextually relevant responses. These advancements are crucial for the future of AI, ensuring scalable and sustainable deployment of sophisticated models. By focusing on multimodal capabilities and robust memory interactions, we’re paving the way for more intelligent and adaptable AI systems. I’m excited to contribute to the upcoming OSS sequel and continue driving innovation in this space. 📖 Learn more about our work: blog.mobiuslabs.com