Machine learning is the scientific study of algorithms and statistical models that result in devices automatically learning and improving from experiences without being explicitly programmed. With so much success integrating machine learning into our everyday lives, the obvious next step is to integrate machine learning into even more systems.
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. In this post, we will explore some practical examples where Azure AI is driving innovation.
Where would you find all three (AI, ML and DS) at work? The most common place today is in autonomous driving vehicles. All three disciplines work together to help train an algorithm to recognize obstacles (MS), then to provide real-time actions (AI) to the vehicle, all based on large amounts of information that data science (DS) can analyze.
In this post, Principal Consultant/ADM Larry Duff discuss some ethical challenges in Artificial Intelligence. Artificial intelligence has been a dream of computer scientists for many years. I remember my early days of programming I had a Commodore Pet. I was excited that I had a book of programs, I typed them in and saved to my tape drive. One...
Ever wondered how to integrate speech and AI into your application? It’s easy with this tutorial from Premier Developer consultants Adel Ghabboun and Kunal Sinha!
Have you ever wondered what are some of the technologies behind personal home assistants such as Cortana, Alexa and Home? Whether you want to tell your personal AI to open...
Senior Application Development Manager, Justin Scott, launched a new podcast this month you will want to check out. AI exposed looks at the world of Artificial Intelligence-- discussing some of the latest trends, interviewing industry experts, and having fun in the process.
In Episode#1, Justin Scott sits with one of our Microsoft ...