New embedding models and API updates
We are launching a new generation of embedding models, new GPT-4 Turbo and moderation models, new API usage management tools, and soon, lower pricing on GPT-3.5 Turbo.
Similar Posts
This AI Paper from the University of Cambridge and UCL Unveils ‘Blending’: A Breakthrough in Efficiently Achieving ChatGPT-level Performance with Smaller Models
In the realm of conversational AI, the trend toward larger models, exemplified by behemoths like ChatGPT, Bard, and Gemini, has been palpable. The understanding is that increasing model parameters and training data significantly enhances language models’ quality and capabilities. However, the computational demands of these colossal models raise concerns about efficiency. When intelligently combined, can…
Researchers from Washington University in St. Louis Propose Visual Active Search (VAS): An Artificial Intelligence Framework for Geospatial Exploration
In the challenging fight against illegal poaching and human trafficking, researchers from Washington University in St. Louis’s McKelvey School of Engineering have devised a smart solution to enhance geospatial exploration. The problem at hand is how to efficiently search large areas to find and stop such activities. The current methods for local searches are limited…
AI News Weekly – Issue #364: The top 12 AI people – Dec 21st 2023
ByWeb Dev
Introducing Horizons … Artificial Intelligence Weekly Powered by superai.com In the News The top 12 people in AI policy, ethics, and research AI presents an ethical minefield that’s pushed researchers, tech companies, and policymakers into opposing camps. businessinsider.com Sponsor Where AI meets the world: SuperAI | 5-6 June 2024, Singapore Join Edward Snowden, Benedict Evans,…
Zyphra Open-Sources BlackMamba: A Novel Architecture that Combines the Mamba SSM with MoE to Obtain the Benefits of Both
Processing extensive sequences of linguistic data has been a significant hurdle, with traditional transformer models often buckling under the weight of computational and memory demands. This limitation is primarily due to the quadratic complexity of the attention mechanisms these models rely on, which scales poorly as sequence length increases. The introduction of State Space Models…
Researchers from the University of Washington Developed a Deep Learning Method for Protein Sequence Design that Explicitly Models the Full Non-Protein Atomic Context
A team of researchers from the University of Washington has collaborated to address the challenges in the protein sequence design method by using a deep learning-based protein sequence design method, LigandMPNN. The model targets enzymes and small molecule binder and sensor designs. Existing physically based approaches like Rosetta and deep learning-based models like ProteinMPNN are…
Meet CompAgent: A Training-Free AI Approach for Compositional Text-to-Image Generation with a Large Language Model (LLM) Agent as its Core
Text-to-image (T2I) generation is a rapidly evolving field within computer vision and artificial intelligence. It involves creating visual images from textual descriptions blending natural language processing and graphic visualization domains. This interdisciplinary approach has significant implications for various applications, including digital art, design, and virtual reality. Various methods have been proposed for controllable text-to-image generation,…
