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.

BOSTON: Many businesses are failing to extract actionable insights from the huge volumes of data they track due to the systemic failure of their approach to machine learning, a leading academic has argued. "If companies want to get value from their data, they need to focus on accelerating human understanding of data, scaling the number of modelling questions they can ask of that data in a short amount of time, and assessing their implications," according to Kalyan Veeramachaneni, Principal Research Scientist in the Laboratory for Information and Decision Systems at MIT. He made this assertion in the Harvard Business Review where he observed that machine-learning experts and their business counterparts were frequently speaking different languages and had different expectations. So, for example, when the former complain that "the data is a mess", this often turns out to refer less to its quality than its granularity. "Machine learning experts are used to working with data that's already been aggregated into useful variables," he noted, "such as the number of website visits by a user, rather than a table of every action the user has ever taken on the site."

It's difficult to predict how artificial intelligence technology will change over the next 10 to 20 years, but there are plenty of gains to be made. By 2018, robots will supervise more than 3 million human workers; by 2020, smart machines will be a top investment priority for more than 30 percent of CIOs. Everything from journalism to customer service is already being replaced by AI that's increasingly able to replicate the experience and ability of humans. What was once seen as the future of technology is already here, and the only question left is how it will be implemented in the mass market. Over time, the insights gleaned from the industries currently taking advantage of AI -- and improving the technology along the way -- will make it ever more robust and useful within a growing range of applications.

Microsoft's AI Is Not Just About Being Smart On December 13th at a very announcement-packed event in San Francisco, Microsoft shared its views of Artificial Intelligence and the progress it has made thus far. Back in September, Microsoft created a new AI and research group of about 5,000 people under the leadership of Harry Shum and they have certainly been busy. A new chatbot called Zo.ai that is integrated into messenger app Kik Cortana Devices SDK so Cortana can be on all kind of devices including what looked to be an Echo-like smart speaker manufactured and branded by Harman/Kardon Calendar.help The list of achievements is significant but it's the picture that develops when looking at them in total that really shows how invested Microsoft is in AI. Nobody would argue that Microsoft missed the whole "app economy" craze.

It looks like 2017 is shaping up to be an interesting year in the embedded-technology space--for a variety of reasons. We're coming off a year that saw a number of large mergers, and the change in the U.S. political climate is significant. Tom Starnes, analyst with Objective Analysis, notes, "One country's loss is another's gain as corporations try to hold on to as much of their revenues as they can in very complex and competitive markets for sophisticated technology. Meantime, the very-global chip industry has been consolidating at a rate and with a mass not seen before, with all but a few companies struggling for profitability." Jim Handy says, "Objective Analysis expects the memory business to be highly profitable in 2017, followed by a collapse beginning in mid-2018."

IBM Watson is known for its work in identifying cancer treatments and beating contestants on Jeopardy! But now the computing system has expertise in a new area of research: neuroscience. Watson discovered five genes linked to ALS, sometimes called Lou Gehrig's disease, IBM announced on Wednesday. The tech company worked with researchers at the Barrow Neurological Institute in Phoenix, Arizona. The discovery is Watson's first in any type of neuroscience, and suggests that Watson could make discoveries in research of other neurological diseases.

Evernote set off a minor fracas on Twitter Tuesday when it announced an upcoming change to its privacy policy that would enable company employees to "exercise oversight of machine learning technologies applied to account content" in order to improve the service. The changes, which will take effect January 23rd, 2017, did not sit well with some of the service's users despite the company's explanation that it was only as oversight for the machine learning process. I need a good replacement for @evernote. Preferably one that lets me import existing notes & works on desktop, iOS and Android. According to the company's policy update notice, "Only employees who are fulfilling one of the customer or business needs... will be able to access your data."

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."

American Express introduced an "Add a Card" feature to its Amex Bot in Facebook Messenger, which will enable eligible US consumers to make purchases on the social media website. These card members will be able to effortlessly make purchases in games and on shop sections of business pages and participate in Messenger commerce experiences. This added feature will help bolster Amex's chatbot offerings, which already includes giving users notifications about balances, benefits, and recent purchases. The bot will keep Amex engaged with its consumers at their convenience. Using a chatbot is aiding Amex in engaging customers.

No one likes standing in line at the Department of Motor Vehicles (DMV), not even Uber. The ride-hailing app launched a fleet of self-driving cars in San Francisco on Tuesday but opted not to go through the vetting process put in place by the California DMV, according to a report from TechCrunch. Uber isn't the first company to test autonomous vehicles in the state, and the DMV has a process for granting permission to companies who would like to put those computer-guided cars on the road. Twenty companies, including Tesla, Google, BMW and Ford have gone through the DMV's Autonomous Vehicle Tester Program, which is administered by the department's occupational licensing branch. Uber is not one of them.