Today we are announcing significant changes to Azure AI Search in support for customers building production ready generative AI applications. Azure AI Search has drastically increased storage capacity and vector index size at no additional cost, so customers can run retrieval augmented generation (RAG) at any scale, without having to compromise cost or performance. In …
Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. SageMaker Studio provides all the tools you need to take your models from data preparation to experimentation to production while boosting your productivity. Amazon SageMaker Canvas is a powerful …
As the pace of AI and the transformation it enables across industries continues to accelerate, Microsoft is committed to building and enhancing our global cloud infrastructure to meet the needs from customers and developers with faster, more performant, and more efficient compute and AI solutions. Azure AI infrastructure comprises technology from industry leaders as well …
Azure Maia for the era of AI: From silicon to software to systems Read More »
The rise of contextual and semantic search has made ecommerce and retail businesses search straightforward for its consumers. Search engines and recommendation systems powered by generative AI can improve the product search experience exponentially by understanding natural language queries and returning more accurate results. This enhances the overall user experience, helping customers find exactly what …
Today we’re releasing our “AI Sprinters” report, outlining ways for developing countries to take advantage of AI’s potential.
The generative artificial intelligence (AI) revolution is in full swing, and customers of all sizes and across industries are taking advantage of this transformative technology to reshape their businesses. From reimagining workflows to make them more intuitive and easier to enhancing decision-making processes through rapid information synthesis, generative AI promises to redefine how we interact …
In 2023, AWS announced an expanded collaboration with Hugging Face to accelerate our customers’ generative artificial intelligence (AI) journey. Hugging Face, founded in 2016, is the premier AI platform with over 500,000 open source models and more than 100,000 datasets. Over the past year, we have partnered to make it effortless to train, fine-tune, and …
Generative AI roadshow in North America with AWS and Hugging Face Read More »
This is a guest post co-written with Michael Feil at Gradient. Evaluating the performance of large language models (LLMs) is an important step of the pre-training and fine-tuning process before deployment. The faster and more frequent you’re able to validate performance, the higher the chances you’ll be able to improve the performance of the model. …
Gradient makes LLM benchmarking cost-effective and effortless with AWS Inferentia Read More »
Amazon SageMaker Canvas allows you to use machine learning (ML) to generate predictions without having to write any code. It does so by covering the end-to-end ML workflow: whether you’re looking for powerful data preparation and AutoML, managed endpoint deployment, simplified MLOps capabilities, or the ability to configure foundation models for generative AI, SageMaker Canvas …
Innovate, Connect, Cultivate The Cloud Cultures series is an exploration of the intersection between cloud innovation and culture across the globe. Last year, I visited Poland, Sweden, England, and Italy, and learned how the unique culture of each of these countries has shaped how they adopt and use technology, demonstrating the diverse ways in which …
Cloud Cultures, Part 5: Embracing innovation and preserving a vibrant identity in Mexico Read More »
