Hong Kong/Beijing: Megvii Inc., a Chinese developer of facial-recognition technology, has raised at least $100 million from investors including Foxconn Technology Group and CCB International Holdings Ltd, according to people with direct knowledge of the matter. The owner of Face is still in talks with other investors for more funding, the people said, asking not to be named because the matter is private. Megvii confirmed it's raising funds while declining to comment on the specific amount. It plans to work with investors to improve facial recognition technology, especially in the financial industry, smart cities and robotics, the company said in an e-mailed statement. Megvii provides face-scanning systems to Ant Financial, which operates the dominant payments service on Alibaba Group Holding Ltd's online shopping platforms.

Newswire) Research and Markets has announced the addition of the "Global Artificial Intelligence Market (2016 - 2022)" report to their offering. The global artificial intelligence market is estimated to reach USD 16,274.0 The report aims at estimating the size and future growth potential of the market across different segments such as technology, application, and region. With the rise in adoption of AI in the media & advertising, retail, finance, and healthcare sectors, the machine learning and natural language processing technologies are expected to play a key role in propelling the growth of the AI market in the next five years. Artificial intelligence (AI) could double annual economic growth rates within two decades by changing the nature of work and spawning a new relationship between man and machine.

Sure, you know your mobile phone is essential, but exactly how much can you rely on it? A few days ago in Japan, Google threw down a gauntlet: how far can you get in a foreign country, where you can't be sure of finding an English speaker, where the words, even the alphabet, are unfamiliar, and where the address system is notoriously tricky? So there I was, in Tokyo, charged with solving a series of puzzles using a smartphone and nothing more. First, I had to get myself from bustling Tokyo (where English speakers are plentiful and, because they are Japanese, endlessly helpful) to the distant city of Kanazawa. I had a JR train pass, which is the best way to get around Japan for a foreigner and which offers fantastic value, though you must buy it before you arrive in the country.

To companies grappling with complex data projects powered by artificial intelligence, a system that Nvidia calls an "AI supercomputer in a box" is a welcome development. Early customers of Nvidia's DGX-1, which combines machine-learning software with eight of the chip maker's highest-end graphics processing units (GPUs), say the system lets them train their analytical models faster, enables greater experimentation, and could facilitate breakthroughs in science, health care, and financial services. Data scientists have been leveraging GPUs to accelerate deep learning--an AI technique that mimics the way human brains process data--since 2012, but many say that current computing systems limit their work. Faster computers such as the DGX-1 promise to make deep-learning algorithms more powerful and let data scientists run deep-learning models that previously weren't possible. It costs $129,000, more than systems that companies could assemble themselves from individual components.

When building large, cloud-based applications that operate at a high scale, it's important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. "Fly two mistakes high" is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Lee Atchison, Principal Cloud Architect and Advocate at New Relic, discussed how this same philosophy can be applied to highly scaled applications, and can dramatically increase your resilience to failure.

To companies grappling with complex data projects powered by artificial intelligence, a system that Nvidia calls an "AI supercomputer in a box" is a welcome development. Early customers of Nvidia's DGX-1, which combines machine-learning software with eight of the chip maker's highest-end graphics processing units (GPUs), say the system lets them train their analytical models faster, enables greater experimentation, and could facilitate breakthroughs in science, health care, and financial services. Data scientists have been leveraging GPUs to accelerate deep learning--an AI technique that mimics the way human brains process data--since 2012, but many say that current computing systems limit their work. Faster computers such as the DGX-1 promise to make deep-learning algorithms more powerful and let data scientists run deep-learning models that previously weren't possible. It costs $129,000, more than systems that companies could assemble themselves from individual components.

Amazon has started its drone delivery trial in Cambridge, UK, the company announced Wednesday. In a tweet, Amazon CEO Jeff Bezos revealed Amazon Prime Air, which promises to deliver packages with small drones in 30 minutes or less after placing an order. The company did not say when the service will be available. "We will deploy when and where we have the regulatory support needed to safely realize our vision," said Amazon. "We're excited about this technology and one day using it to deliver packages to customers around the world in 30 minutes or less."

Late one Friday night in early November, Jun Rekimoto, a distinguished professor of human-computer interaction at the University of Tokyo, was online preparing for a lecture when he began to notice some peculiar posts rolling in on social media. Apparently Google Translate, the company's popular machine-translation service, had suddenly and almost immeasurably improved. Rekimoto visited Translate himself and began to experiment with it. He had to go to sleep, but Translate refused to relax its grip on his imagination. Rekimoto wrote up his initial findings in a blog post. First, he compared a few sentences from two published versions of "The Great Gatsby," Takashi Nozaki's 1957 translation and Haruki Murakami's more recent iteration, with what this new Google Translate was able to produce. Murakami's translation is written "in very polished Japanese," Rekimoto explained to me later via email, but the prose is distinctively "Murakami-style."

It emphasizes flexibility through the elegant use of object-oriented design patterns.

'Tis the season for the public relations exercise known as "here's what we think (or hope) will happen in the tech sector next year," flooding my inbox with predictions for 2017. No one knows what will happen tomorrow, let alone over the next 12 months, but the exercise yields interesting insights into what's hot (and what's not) in technology today. Artificial intelligence (and machine/deep learning) is the hottest trend, eclipsing, but building on, the accumulated hype for the previous "new big thing," big data. The new catalyst for the data explosion is the Internet of Things, bringing with it new cybersecurity vulnerabilities. The rapid fluctuations in the relative temperature of these trends also create new dislocations and opportunities in the tech job market. The hottest segment of the hottest trend--artificial intelligence--is the market for chatbots.