Legal tech start-up, Juro, this week announced it had received significant funding to help grow its AI-powered contract system (see story here). Artificial Lawyer caught up with co-founder and former Freshfields lawyer, Richard Mabey to find out more. We discussed how Juro works, the difference between selling legal tech to lawyers and non-lawyers and where the UK-based company is headed. First, congratulations on the $750k in seed funding for Juro, that is a great sign of confidence from what are experienced tech investors. Can you set out for the readers broadly what Juro does?

If your job involves inputting reams of data for a company, you might want to think about retraining in a more specialised field. After industrial robots and international trade put paid to many manufacturing jobs in the West, millions of white-collar workers could now be under threat from new technology such as artificial intelligence (AI). The issue of how best to face up to this "Fourth Industrial Revolution" has been exercising politicians and business leaders this week at the World Economic Forum in the Swiss Alpine town of Davos. The progress of artificial intelligence has been "staggering" in recent years, said Vishal Sikka, chief executive of Indian IT services giant Infosys. "But in many ways we are at the beginning of this evolution and we face the prospect of leaving a larger part of humanity behind than in any other (industrial) advance," he warned.

How Millennials and Baby Boomers Consume User-Generated Content [Infographic] 47% of millennials trust user-generated content, vs. 36% of their baby boomer counterparts. However, each generation shared a relative distrust of content created by brands. This infographic shows the generation gap of UGC. Survey: 60 percent of voice users want more answers and fewer search results People who use voice search -- the majority of whom prefer to do so in private vs. public -- use it because it's fast, doesn't require reading, and gives you fewer answers to sort through. What does voice search mean for the future of search marketing?

Fears that accelerating automation is going to eat its lion's share of jobs continue to plague corporate sectors. However, new research from McKinsey Global Institute may talk folks afflicted with automation phobias down from the ledge. The research group says that although half of today's work activities could be automated, it may not happen until 2055. Where the statistic falls along the S curve depends on various factors, such as breakthroughs in artificial intelligence and economic conditions, says Michael Chui, a McKinsey Global Institute partner and an author of the report. Chuiand other researchers analyzed 800 occupations and 2,000 job tasks.

Fears that accelerating automation is going to eat its lion's share of jobs continue to plague corporate sectors. However, new research from McKinsey Global Institute may talk folks afflicted with automation phobias down from the ledge. The research group says that although half of today's work activities could be automated, it may not happen until 2055. Where the statistic falls along the S curve depends on various factors, such as breakthroughs in artificial intelligence and economic conditions, says Michael Chui, a McKinsey Global Institute partner and an author of the report. Chuiand other researchers analyzed 800 occupations and 2,000 job tasks.

Have you recently had a frustrating or confusing conversation with a computer? It's silly to admit, but once in while I find myself screaming at Alexa (i.e., the persona of my Amazon Echo) because I don't like what she's telling me. Rationally, I know it's not her fault that my vacation plans are probably ruined by impending thunderstorms, but it's easy to get caught up in the role-play when your computer is talking to you like a human. For artificial intelligence architects, this is known as Natural Language Generation or NLG. A bigger challenge for solution developers embracing NLG in their designs is communicating in the best way for their customers to appreciate and understand.

Computers and robots can be biased too and it likely stems from the majority-focused photos used to train them. Researchers at the Massachusetts Institute of Technology are helping to pinpoint why facial recognition software is not accurate across all races -- and the issue likely stems from both recycled code and a Caucasian-dominated computer engineering field. Joichi Ito, MIT's Media Lab director, said during an artificial intelligence panel held this week at the World Economic Forum Annual Meeting that the software's apparent trouble with recognizing diversity is likely because the engineers, and the faces used to train the software, are mostly white. More: Google Photos' 'racist' error highlights facial recognition's limits The issue goes back to the basics of artificial intelligence. Machine learning programs are based on teaching a computer with a set of data.

Nvidia (NASDAQ:NVDA) has the hardware lead in deep learning, full stop. I have explained why this is so in an article I published last May. Since then, Nvidia investors have enjoyed outsized gains, which recently has brought about a number of articles speculating about an imminent reversal. This article is a rebuttal on a recent piece about Nvidia's AI perspectives, and possible threats from specialty deep learning hardware. Giving my opinion as a deep learning researcher, the recent piece contains a number of technical inaccuracies.

Last week I read Abadi and Andersen's recent paper [1], Learning to Protect Communications with Adversarial Neural Cryptography. I thought the idea seemed pretty cool and that it wouldn't be too tricky to implement, and would also serve as an ideal project to learn a bit more Theano. This post describes the paper, my implementation, and the results. The authors set up their experiment as follows. We have three neural networks, named Alice, Bob, and Eve.

Intel is the king of a shrinking kingdom. Almost every traditional desktop or laptop PC runs on the Santa Clara company's processors, but that tradition is fast being eroded by more mobile, ARM-powered alternatives. Apple's most important personal computers now run iOS, Google's flagship Chromebook has an ARM flavor, and Microsoft just announced Windows for ARM. And what's more, the burden of processing tasks is shifting away from the personal device and distributed out to networks of server farms up in the proverbial cloud, leaving Intel with a big portfolio of chips and no obvious customer to sell millions of them to. If you want to talk about the most influential chip company in history, Intel's name is the one you want.