Venture capital firm Octopus Ventures has raised a £120 million fund to invest in UK technology startups, The Financial Times reports. The London-based investment company, part of UK fund management firm Octopus Group, has reportedly now raised a total of £660 million, fuelled in part by a string of successful UK startup exits. Natural language processing pioneer Evi Technologies, predictive keyboard startup SwiftKey, and AI video startup Magic Pony are all in the Octopus Ventures portfolio, as are companies like LoveFilm and property website Zoopla. "Evi Technologies in Cambridge was sold to Amazon and now powers Alexa, the voice-activated speaker," Alex Macpherson, chief executive of Octopus Ventures, told the FT. "We also backed Swiftkey which went to Microsoft last year [for $250 million; £200 million] and made a seed investment in Magic Pony, which went to Twitter [for $150m; £120 million].

BEIJING – A years-long crime spree by Chinese toilet paper thieves may have reached the end of its roll after park officials in southern Beijing installed facial recognition technology to flush out bathroom bandits. Park managers at the Temple of Heaven, an expanse of imperial landmarks in the capital, spent three years testing ways to foil the toilet looters, including fingerprinting and laser sensors, before they settled on the new technology, which was introduced over the weekend. Elderly square dancers taking their bathroom breaks on Tuesday were greeted by a robotic voice: "Welcome! Please stand in the recognition zone." One by one, they obediently positioned themselves on a yellow square marking and watched their faces pop up on a blinking blue screen mounted to the wall.

Similar to the voice search features on Rokus, Amazon Fire TV streamers et al, Sky Qers can search through live TV and all on-demand content simply by speaking the names of actors, shows, films and directors into the Touch Remote's microphone. You can also search by genre, age rating, average reviews and other descriptors, as well as compound these for more specific searches -- Sky gives examples such as "Tom Hank's movies rated five stars" and "films with Arnold Schwarzenegger and Sylvester Stallone." It gets a little bit smarter than that, too. Phrases such as "live cricket on this weekend," "what's on Sky Atlantic tonight" and "Liverpool game" should turn up the search results you're after, so there's some contextual leeway. Sky has even thrown a bunch of easter eggs, letting you to track down classics by reciting popular lines.

Machine learning is increasingly being seen as the solution, dealing - or at least appearing to deal - with a number of the problems organizations are having implementing their cybersecurity initiatives. Former Department of Defense Chief Information Officer, Terry Halvorsen, believes that'within the next 18-months, AI will become a key factor in helping human analysts make decisions about what to do.' This point of view is being reinforced by significant investment in the field by the world's largest technology companies. MIT has been experimenting with it for some years, while IBM is training its AI-based Watson in security protocols and has now made it available to customers. Amazon also recently acquired AI-based cyber-security company Harvest.ai,

At the CeBIT Global Conferences, he explained what VW is working on and what role artificial intelligence will play for the car of tomorrow. Let's start with what Jungwirth did NOT speak about at the Sakura Stage in Hall 8: alternative engines. Instead, the Volkswagen CDO showed, in fast-forward, how the corporation is digitizing its core business. The key term here was artificial intelligence. "AI is everywhere and it will take on a central role in the car of the future," states Jungwirth.

Andrew Ng, a leading figure in the world of artificial intelligence, is leaving his post as chief scientist at China's Baidu and says he wants to find ways of advancing AI beyond the technology world. Ng is known for playing a leading role in formulating the AI strategy of both Baidu and Google. He says is leaving the Chinese company on good terms and simply wants to find a new challenge. "I've decided to step away from this role while everything is going well and look at some other things," he told MIT Technology Review. "I don't know precisely what I'll do, but I think AI offers a lot of opportunities, not just at big companies like Baidu but for entrepreneurs, and for advancing basic research," Ng added.

Mythic is one of them, and it claims to be taking a different approach than the others. The Austin, Texas-based startup wants to move away from the cloud and a dependence on network connections by putting AI-on-a-chip inside smart devices like security cameras and health wearables. DFJ believes in the potential of this approach to AI and led an $8.8 million round that was announced today. The startup has developed both software and microchips to make its AI smarter and faster. Today, artificial neural networks need big server racks powered by graphics processing units (GPUs) to handle complex algorithms.

I spend a lot of time reading articles on the internet and started wondering whether I could develop software to automatically discover and recommend articles relevant to my interests. There are various aspects to this problem but I have decided to concentrate first on the core part of the problem: the analysis and classification of the articles. To illustrate the problem, lets consider the following string representing an article for the purpose of this example. We will attempt to use this article as a query to find similar or related articles from the following set of strings (usually referred to as a'corpus'), where each string also represents an article. The approaches we will consider for this example will work with any type of query equally whether the query is itself an article as above or simply a short string of words.

This is the 2nd installment of a new series called Deep Learning Research Review. Every couple weeks or so, I'll be summarizing and explaining research papers in specific subfields of deep learning. This week focuses on Reinforcement Learning. Before getting into the papers, let's first talk about what reinforcement learning is. The field of machine learning can be separated into 3 main categories.

The University of Alberta's Computer Poker Research Group created DeepStack, an artificial intelligence program that defeated professional human poker players at heads-up, no-limit Texas hold'em. Apart from this win being the first of its kind, it bares significance in assisting to make better medical treatment recommendations to developing improved strategic defense planning, stated DeepStack: Expert-level artificial intelligence in heads-up no-limit poker, which was published in Science. DeepStack brings together approaches involving games of perfect information, meaning both players see what is on the board, and imperfect information, where it reasons while playing, using intuition through learning to reassess its strategy with every decision. Computing scientist Michael Bowling, professor in the University of Alberta's Faculty of Science and principal investigator on the study, said poker has presented an ongoing challenge to artificial intelligence. "It is the quintessential game of imperfect information in the sense that the players don't have the same information or share the same perspective while they're playing," explained Bowling.