Nvidia has released NeMo microservices into general availability with version 25.4, pivoting its profile from a modular toolkit for creating custom generative AI models to emphasizing it as a platform for building AI agents at scale. As AI agents have become an in-demand commodity, Nvidia is leveraging the fact that NeMo’s capabilities seem purpose built to help them grow and thrive. Built around the Kubernetes open-source container management system, NeMo microservices are offered as “an end-to-end developer platform for creating state-of-the-art agentic AI systems,” according to Nvidia. Continue reading Nvidia Positions Its NeMo Microservices for AI Agent-Building

Microsoft, which has been developing small language models (SLMs) for some time, has announced its most-capable SLM family, Phi-3. SLMs can accomplish some of the same functions as LLMs, but are smaller and trained on less data. That smaller footprint makes them well suited to run in a local environment, which means they’re ideal for smartphones, where in theory they would not even need an Internet connection to run. Microsoft claims the Phi-3 open models can outperform “models of the same size and next size up across a variety of benchmarks that evaluate language, coding and math capabilities.” Continue reading Microsoft Small Language Models Are Ideal for Smartphones

Microsoft is releasing Phi-2, a text-to-text small language model (SLM) that outperforms some LLMs, yet is light enough to run on a mobile device or laptop, according to Microsoft CEO Satya Nadella. The 2.7 billion-parameter SLM beat Meta Platforms’ Llama 2 and Mistral 7B from France (each with 7 billion parameters) says Microsoft, emphasizing its complex reasoning and language comprehension are exceptional for a model with less than 13 billion parameters. For now, Microsoft is making it available “for research purposes only” under a custom license. Continue reading Microsoft Says Phi-2 Can Outperform Large Language Models