We are at an incredibly exciting technology inflection point. The virtually limitless computing power of the cloud, combined with increasingly connected and perceptive devices at the edge of the network, create possibilities we could only have dreamed of just a few years ago – possibilities made up of millions of connected devices, infinite data, and the ability to create truly immersive multi-sense, multidevice experiences.
AI is fueling the next wave of transformative innovations that will change the world. With Azure AI, our goal is to empower organizations to apply AI across the spectrum of their business to engage customers, empower employees, optimize operations and transform products. To make this a reality, we have three guiding investment principles.
Recommendation systems are used in a variety of industries, from retail to news and media. If you’ve ever used a streaming service or ecommerce site that has surfaced recommendations for you based on what you’ve previously watched or purchased, you’ve interacted with a recommendation system.
We are truly at a unique tipping point in the history of technology. The pace of growth is more rapid than ever before, with estimates of more than 150B connected devices and data growth up to 175 Zettabytes by 2025.
Do you have an idea that could improve and empower the lives of everyone in a more accessible way? Or perhaps you have an idea that would help create a sustainable balance between modern society and the environment? Even if it’s just the kernel of an idea, it’s a concept worth exploring with the AI for Good Idea Challenge!
The QnA Maker service lets you easily create and manage a knowledge base from your data, including FAQ pages, support URLs, PDFs, and doc files. You can test and publish your knowledge base and then connect it to a bot using a bot framework sample or template.
In a few weeks, over 22,000 people from around the globe will converge in Orlando, Florida from May 7-9, 2019 for the SAP Sapphire NOW and ASUG Annual Conference.
DevOps is the union of people, processes, and products to enable the continuous delivery of value to end users. DevOps for machine learning is about bringing the lifecycle management of DevOps to Machine Learning.
When it comes to executing a machine learning project in an organization, data scientists, project managers, and business leads need to work together to deploy the best models to meet specific business objectives.
Whether you’re just starting off in tech, building, managing, or deploying apps, gathering and analyzing data, or solving global issues —anyone can benefit from using cloud technology. Below we’ve gathered five cool examples of innovative artificial intelligence (AI) to showcase how you can be a catalyst for real change.