In the world of machine learning, there’s been a notable trade-off between accuracy and intelligibility. Either the models are accurate but difficult to make sense of, or easy to understand but prone to error. That’s why Dr. Rich Caruana, Principal Researcher at Microsoft Research, has spent a good part of his career working to make the simple more accurate and the accurate more intelligible.

Today, Dr. Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

With 7 billion people on the planet, you might be surprised to learn that approximately a billion of those people experience some form of disability. Enter Principal Researcher and Research Manager, Dr. Merrie Ringel Morris, and the Ability Group at Microsoft Research. They’re working to remove accessibility barriers both to and through technology, empowering people with disabilities to better perform their daily tasks.

Today, Dr. Morris gives us some fascinating insights into the world of “ability,” talks about how technology is augmenting not only sensory and motor abilities, but cognitive and social abilities as well, and shares how Microsoft, through its AI for Accessibility initiative, is committed to extending the capabilities and enhancing the quality of life for every person on the planet.

Humans are wired to communicate, but we don’t always understand each other. Especially when we don’t speak the same language. But Arul Menezes, the Partner Research Manager who heads MSR’s Machine Translation team, is working to remove language barriers to help people communicate better. And with the help of some innovative machine learning techniques, and the combined brainpower of machine translation, natural language and machine learning teams in Redmond and Beijing, it’s happening sooner than anyone expected.

Today, Menezes talks about how the advent of deep learning has enabled exciting advances in machine translation, including applications for people with disabilities, and gives us an inside look at the recent “human parity” milestone at Microsoft Research, where machines translated a news dataset from Chinese to English with the same accuracy and quality as a person.

Some of the world’s leading architects are people that you’ve probably never heard of, and they’ve designed and built some of the world’s most amazing structures that you’ve probably never seen. Or at least you don’t think you have. One of these architects is Dr. Doug Burger, Distinguished Engineer at Microsoft Research NExT. And, if you use a computer, or store anything in the Cloud, you’re a beneficiary of the beautiful architecture that he, and people like him, work on every day.

Today, in a fast-paced interview, Dr. Burger talks about how advances in AI and deep machine learning have placed new acceleration demands on current hardware and computer architecture, offers some observations about the demise of Moore’s Law, and shares his vision of what life might look like in a post-CPU, post-von-Neumann computing world.

Autonomous flying agents – or flying robots – may seem like the stuff of sci-fi to the average person, but to Dr. Ashish Kapoor, Principal Researcher and Research Manager of the Aerial Informatics and Robotics Group at Microsoft Research, they’re much closer to science than to fiction. And, having built – and flight tested – his own airplane, complete with state-of-the-art avionics designed to run AI and ML algorithms, he has the street cred – or should we say flight cred – to prove it.

Today, Dr. Kapoor talks about how cutting-edge machine learning techniques are empowering a new generation of autonomous vehicles, and tells us all about AirSim, an innovative platform that’s helping bridge the simulator-to-reality gap, paving the way for safer, more robust real-world AI systems of all kinds