Experts from across the AI world came together in New York for the O'Reilly AI Conference in New York 2016. Below you'll find links to highlights from the event. Building reliable, robust software is hard, says Peter Norvig. It's even harder when we move from deterministic domains, such as balancing a checkbook, to uncertain domains, such as recognizing speech or objects in an image. Tim O'Reilly explains why we can't just use technology to replace people; we must use it to augment them so that they can do things that were previously impossible.

Object recognition is one of the most exciting areas in machine learning right now. Computers have been able to recognize objects like faces or cats reliably for quite a while, but recognizing arbitrary objects within a larger image has been the Holy Grail of artificial intelligence. Maybe the real surprise is that human brains recognize objects so well. We effortlessly convert photons bouncing off objects at slightly different frequencies into a spectacularly rich set of information about the world around us. Machine learning still struggles with these simple tasks, but in the past few years, it's gotten much better.

Watch highlights covering artificial intelligence, machine learning, intelligence engineering, and more.

Bots are a growing segment of software that acts as an agent on a human's behalf. These tasks range from ordering online, to making dinner reservations, to handling customer service requests, to helping employees be more productive in the workplace. Historically, most bots have used simple rules-based approaches to present an output for a given input (such as presenting the weather). But today, with advances in server-side processing power and improvements in implementing artificial intelligence (AI) and machine learning (ML), bots are starting to provide real value to consumers. The tide has finally turned and bots are entering the mainstream consciousness, especially after the recent announcements at Facebook's annual conference F8.

Experts from across the AI world came together in New York for the O'Reilly AI Conference in New York 2016. Below you'll find links to highlights from the event. Building reliable, robust software is hard, says Peter Norvig. It's even harder when we move from deterministic domains, such as balancing a checkbook, to uncertain domains, such as recognizing speech or objects in an image. Watch "Software engineering of systems that learn in uncertain domains."

Shivon Zilis will participate in a panel discussion at Strata Hadoop World New York 2016, "Where's the puck headed?," considering the big trends in big data and explaining what the field will look like down the road. A year ago today, I published my original attempt at mapping the machine intelligence ecosystem. So much has happened since. I spent the last 12 months geeking out on every company and nibble of information I can find, chatting with hundreds of academics, entrepreneurs, and investors about machine intelligence. This year, given the explosion of activity, my focus is on highlighting areas of innovation, rather than on trying to be comprehensive.

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