infoq.com / .infoq-com-ai-ml-data-eng / Page 3

Denys Linkov's QCon San Francisco 2024 talk dissected the complexities of evaluating large language models (LLMs). He advocated for nuanced micro-metrics, robust observability, and alignment with business objectives to enhance model performance. ...

In this podcast Shane Hastie, Lead Editor for Culture & Methods spoke to Maria Apazoglou, Head of AI, BI & Data Platforms at Thomson Reuters, about as her experience in building great teams and democratizing the use of large language models across .. ...

The Allen Institute for AI research team has introduced OLMo 2, a new family of open-source language models available in 7 billion (7B) and 13 billion (13B) parameter configurations. Trained on up to 5 trillion tokens, these models redefines training ...

Rachael Greaves provides a summary of the requirements for data lifecycle management, the technology approaches, and the risks, and includes a Data Minimization Best Practice Checklist.

Mistral AI released Pixtral Large, a 124-billion-parameter multimodal model designed for advanced image and text processing with a 1-billion-parameter vision encoder. Built on Mistral Large 2, it achieves leading performance on benchmarks like ...

Recently announced by Andrew Ng, aisuite aims to provide an OpenAI-like API around the most popular large language models (LLMs) currently available to make it easy for developers to try them out and compare results or switch from one LLM to another ...

Nexa AI unveiled Omnivision, a compact vision-language model tailored for edge devices. By significantly reducing image tokens from 729 to 81, Omnivision lowers latency and computational requirements while maintaining strong performance in tasks like ...

Physical Intelligence recently announced 0 (pi-zero), a general-purpose AI foundation model for robots. Pi-zero is based on a pre-trained vision-language model (VLM) and outperforms other baseline models in evaluations on five robot tasks.

AWS has introduced Multi-Agent Orchestrator, a framework designed to manage multiple AI agents and handle complex conversational scenarios. The system routes queries to the most suitable agent, maintains context across interactions, and integrates .. ...

Microsoft has announced the release of Magentic-One, a new generalist multi-agent system designed to handle open-ended tasks involving web and file-based environments. This system aims to assist with complex, multi-step tasks across various domains, ...