As enterprises rely more heavily on AI integration to compile research and summarize things like meetings and email threads, the need for contextual search has become increasingly important. AI startup Cohere has released Embed 4 to make the task easier. Embed 4 is a multimodal embedding model that transforms text, images and mixed data (like PDFs, slides or tables) into numerical representations (or “embeddings”) for tasks including semantic search, retrieval-augmented generation (RAG) and classification. Supporting over 100 languages, Embed 4 has an extremely large context window of up to 128,000 tokens. Continue reading Cohere’s Multimodal Embed Model Organizes Enterprise Data

Microsoft and Nvidia have trained what they describe as the most powerful AI-driven language model to date, the Megatron-Turing Natural Language Generation model (MT-NLG), which has “set the new standard for large-scale language models in both model scale and quality,” the firms say. As the successor to the companies’ Turing NLG 17B and Megatron-LM, the new MT-NLG has 530 billion parameters, or “3x the number of parameters compared to the existing largest model of this type” and demonstrates unmatched accuracy in a broad set of natural language tasks. Continue reading Microsoft and Nvidia Debut World’s Largest Language Model