Japanese gaming company Nintendo has unveiled the Nintendo Switch console at a presentation in Tokyo. The new gaming platform wants to do everything at once, executives said, from the old-school fantasy of its flagship launch title, Zelda: Breath of the Wild, to party games played face-to-face rather than in front of a screen. The Switch "inherited all of Nintendo's entertainment DNA" across the company's broad line of products, said Shinya Takahashi, Nintendo's head of software development. The presentation ended with a surprise: the long-delayed Breath of the Wild, originally planned as an exclusive to the Wii U platform, will go on sale with the new console. The Switch will go on sale on 3 March in Europe, Japan and the US, at a cost of $299.99.

AFP-JIJI – Nintendo is unveiling its new Switch game console Friday as it looks to offset disappointing Wii U sales and go head to head with rival Sony's hugely popular PlayStation 4. The hybrid device -- it can be played at home and on the go -- comes as Nintendo dips its toe into the mobile gaming market after scoring a big win for its brand in the summer with the success of Pokemon Go. But Switch got off to an inauspicious start in October when a sneak peak at the console left gamers and analysts underwhelmed and with many unanswered questions. Nintendo's Tokyo-listed stock dived after it released a three-minute video about the product on its YouTube channel. The shares fell 2.24 percent to ¥24,635 Friday ahead of an event in Tokyo where the company is expected to release more details, including the price. The Canadian unit of retail giant Wal-Mart has listed Nintendo Switch for sale on its online shopping site for $399 Canadian dollars, or roughly $300 -- the level some analysts have said could make or break demand for the device.

President of Nintendo Tatsumi Kimishima reacts after his speech during a presentation event of Nintendo Switch in Tokyo, Friday, Jan. 13, 2017. Nintendo Co. said Friday that its Nintendo Switch video game console will sell for 29,980 yen (about $260) in Japan, starting March 3. (AP Photo/Koji Sasahara) The Associated Press

Viki, an artificial intelligence assistant is allegedly under development to strengthen smartphone giant Nokia. While it is unclear where did Nokia got the name Viki, but suspicions point to 1989 TV character VICI who is a child android. According to GSM Info, Nokia just requested European Union for trademark protection of Viki and its product description suggests that this software will combine all data sources into a single chat and voice-based interface. Nokia Viki will therefore become the new interface similar to Siri and the likes. Question now is how will Viki fare in contrast to Apple Siri AI assistant or other support that competitors feature.

A future in which human workers are replaced by machines is about to become a reality at an insurance firm in Japan, where more than 30 employees are being laid off and replaced with an artificial intelligence (AI) system that can calculate payouts to policyholders. Fukoku Mutual Life Insurance believes it will increase productivity by 30 per cent and see a return on its investment in less than two years. The firm said it would save about 140 million yen (€1.15 million) a year after the 200 million yen (€1.64 million) AI system is installed this month. Maintaining it will cost about 15 million yen (€123,000) a year. The move is unlikely to be welcomed, however, by 34 employees who will be made redundant by the end of March.

Every day, "Artificial Intelligence" (A.I.) becomes more prevalent in the press, business and emerging technology. But we should regard all claims of Artificial Intelligence innovation with a healthy level of skepticism. "What exactly do you mean by A.I.? What do the systems do?" is a great way to open an A.I. discussion of any kind. Generally speaking, there are two main varieties of A.I., one of which is still squarely in the domain of science fiction and one that is already in use across hundreds of industries With the Computational Intelligence A.I., humans are a requirement in the process and workflow as they impart subject matter expertise and provide feedback on the output of algorithms leading to what can be regarded as Augmented Intelligence[1]. In the case of machine learning, human feedback improves accuracy and precision.

Within the last 10 years, there has been a rapid growth of new jobs and industries that have never existed, and jobs that are going by the wayside due to technology. The advancement in technology has transformed our way of life in how we communicate, do business, work, travel, buy, sell, bank, in transportation, and in our careers. Technology has touched almost every area of our lives and it will be what transforms our education system. Technology is driving these rapid changes in our society, however the education system has not felt the full effects of how technology will transform the system that has been in place for decades. The system is worried more about test scores and how these test scores reflect a school, a district, a city, and the state.

We study large-scale kernel methods for acoustic modeling in speech recognition and compare their performance to deep neural networks (DNNs). We perform experiments on four speech recognition datasets, including the TIMIT and Broadcast News benchmark tasks, and compare these two types of models on frame-level performance metrics (accuracy, cross-entropy), as well as on recognition metrics (word/character error rate). In order to scale kernel methods to these large datasets, we use the random Fourier feature method of Rahimi and Recht (2007). We propose two novel techniques for improving the performance of kernel acoustic models. First, in order to reduce the number of random features required by kernel models, we propose a simple but effective method for feature selection. The method is able to explore a large number of non-linear features while maintaining a compact model more efficiently than existing approaches. Second, we present a number of frame-level metrics which correlate very strongly with recognition performance when computed on the heldout set; we take advantage of these correlations by monitoring these metrics during training in order to decide when to stop learning. This technique can noticeably improve the recognition performance of both DNN and kernel models, while narrowing the gap between them. Additionally, we show that the linear bottleneck method of Sainath et al. (2013) improves the performance of our kernel models significantly, in addition to speeding up training and making the models more compact. Together, these three methods dramatically improve the performance of kernel acoustic models, making their performance comparable to DNNs on the tasks we explored.

HTC may have taken a bolder approach in the smartphone world with its new U Ultra and U Play, but it's decided to play it safe with its roadmap for the rest of the year. After today's launch event in Taipei, I caught up with President of Smartphone and Connected Devices Business, Chialin Chang, who confirmed that HTC will only be releasing six to seven smartphones this year. While that's a drastic cut from last year's eleven to twelve models, he claims this has so far allowed the company to focus on its smartphones' core features, in a bid to put up a better fight against other brands. In the case of the two newest phones, Chang sees machine learning as their main selling point. The exec described the so-called Sense Companion virtual assistant as a combination of Google's Awareness API, device information and third-party data.

Think about your typical day. Your phone alarm wakes you up (maybe after hitting snooze a couple of times), you check the weather as your coffee is brewing, and you get traffic alerts about your commute to work. How many times do you think artificial intelligence (AI) is a part of your day? It's definitely more often than you think. During a conversation with President Barack Obama, technologist Joi Ito, director of the MIT Media Lab, predicted that 2016 would be the "year artificial intelligence becomes more than just a computer science problem." In 2016, AI's fast progress led to acquisition deals topping $1 billion, and the White House released its first report on artificial intelligence and the economy.