Join DataPhoenix and 10,000 tech leaders, investors, and founders at TechCrunch Disrupt in San Francisco on Sept 19-21. Don’t miss interviews and sessions with trailblazing visionaries from Anthropic, DeepMind, Salesforce, Sequoia Capital, and more on AI Stage!
This talk will dive into “data frameworks” like LlamaIndex, and demonstrate how to create hierarchical indexes from different data sources.
Cohere unveils Coral, an enterprise-grade knowledge assistant designed to boost productivity and streamline workflows. Backed by Cohere's Command model and focused on data privacy, Coral's customized and conversational capabilities can significantly streamline various business functions.
NVIDIA's DGX Cloud is now widely accessible, boasting thousands of NVIDIA GPUs on Oracle Cloud and NVIDIA's infrastructure in the U.S. and U.K. The service equips enterprises with the necessary tools for training advanced AI models, each DGX Cloud instance featuring eight GPUs.
Join the Data Phoenix webinar in which Supreet Kaur (AI Product Manager at Morgan Stanley) will talk about synthetic data, its most impactful use cases, and the challenges companies face while harnessing its power.
Join the Data Phoenix webinar in which Nils Reimers (Director of Machine Learning at Cohere) will talk about why multilingual semantic search is amazing, how respective models are trained, and the new use cases this unlocks.
Preply plans to use the funds to assist its rapid expansion into AI and launch new teaching assistants to enhance language learning.
Tractable’s AI automates the insurance claims and damage assessment process, enabling real-time condition assessment and accurate repair estimates based on images captured via smartphone
Meta has released Llama 2, its next-generation, open-source large language model, represented by 7 billion, 13 billion, and 70 billion parameter versions. The company has made this model accessible for research and commercial applications, fostering further development in the field.
Join us for an insightful talk as we delve deep into the intricacies of assessing the performance and quality of LLMs and discover the best practices to ensure the reliability and accuracy of your LLM applications.
