Get smart on machine learning before the machines beat you to it

Call for papers opens for M3 conference on AI, ML

logo for mcubed conference

Reg Events 2017 looks like being the year of AI. Or at least that’s what a friendly computer keeps telling us.

So we’re partnering with our friends at Heise to bring you M3, a conference which aims to bring together researchers, academics and, crucially, practitioners, to show you how to put the latest in artificial intelligence, machine learning algorithms, and deep learning, to work in your organisation.

The conference will take place from October 9 to 11, at 30 Euston Square, Central London. This is a stunningly comfortable venue in which to ponder some of the most intellectually, and ethically, challenging issues facing the tech community today.

Yes, we will have visionaries and engineers working at the cutting edge of what’s possible - and a few working on the seemingly impossible too. But we also aim to highlight real world examples of businesses putting silicon brains to work, whether it’s helping medical researchers make sense of data, or analysts make sense of markets, managing customer support systems, or helping you decide exactly which flat pack furniture you want to buy - before you even decided you needed any.

While algorithms, frameworks, cognitive systems and UX will undoubtedly be on the agenda, we’ll also be examining the underlying hardware and networks that make these systems possible. And we’ll be taking a wider view, considering the security, privacy and ethical implications of computers and robots that can do what we can, but, arguably, better.

That’s the plan. Now, it’s up to you. The call for papers is open, and we’d love to hear your proposals for conference sessions and workshops that illustrate the rapid advances in this field - and how they are being applied to real world business and academic problems.

Oh, and that name? M3 stands for Minds Mastering Machines - because ultimately, we think it’s the humans that should stay in charge. Until the machines tell us different, of course. ®


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