Microsoft has announced updates for its Phi-3 generative AI models and Azure cloud services.

Microsoft has announced updates for its Phi-3 generative AI models and Azure cloud services.

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Microsoft has announced several updates to its Phi-3 generative AI models and Azure cloud platform. Developers can now swiftly create customized AI solutions using Microsoft’s Phi-3 models and leverage Azure’s platform to access additional AI models from companies like Meta, the parent company of Facebook and Instagram.

“Developing and deploying AI applications at scale requires a robust and flexible platform that can handle the complex and diverse needs of modern enterprises and allow them to create solutions grounded in their organizational data,” Microsoft stated in its announcement.

Updates to Microsoft’s AI Models and Cloud Platform

– Serverless Fine-Tuning: Microsoft has introduced serverless fine-tuning for Phi-3-mini and Phi-3-medium models, enabling developers to customize these models for cloud and edge scenarios without needing dedicated computational resources.
– Model Improvements: The Phi-3-mini model has received updates to enhance core quality, instruction-following, and structured output, allowing developers to use a more efficient model at no extra cost.
– New AI Models: Earlier this month, Microsoft also announced same-day shipping for the latest models from OpenAI (GPT-4o mini), Meta (Llama 3.1 405B), and Mistral (Large 2) on Azure AI.

About Phi-3 Models

In April, Microsoft introduced the Phi-3 family of small, open models, highlighting them as the most capable and cost-effective small language models (SLMs) available. The company claims that Phi-3 models outperform both similarly sized models and those just one size larger.

“As developers seek to tailor AI solutions to specific business needs and enhance response quality, fine-tuning a small model like Phi-3-mini or Phi-3-medium provides a high-performance alternative without sacrificing efficiency,” Microsoft added. This fine-tuning allows developers to create AI experiences that are more relevant to their users, both safely and economically.

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