Before I go any further, I want to give a shoutout to Steve Eisman for suggesting this title in an interview. Eisman is the managing director at Neuberger Berman, but he's best known for being portrayed by Steve Carrell in 2015's the Big Short. Lately, he's been touting two key positions in his portfolio - a short position on Tesla (TSLA) and a long position in General Motors (GM). That latter bet is based on Eisman's belief that the company's turnaround is likely to be successful and that their self-driving car unit could already be worth more than the entire parent company. In the interview with ETN, he said someday a financial writer would write about this odd phenomenon, so that's exactly what I'm doing here.

OVER the last few years, retailers have been working hard to leverage AI in a way that maximizes customer loyalty and spends. According to one Juniper Research study, the retail industry is set to spend some US$7.3 billion on AI solutions in the next three years, as compared to US$2 billion last year. The study highlighted that more retailers are seeking to emulate Amazon.com's Smart shelves have the potential to boost the dwindling foot traffic to traditional brick and mortar outlet. These futuristic shelves, currently being piloted by Krogers features LED displays that will show targeted ads and promotions.

President TrumpDonald John TrumpTrump to sign executive order promoting artificial intelligence Trump's new Syria timetable raises concern among key anti-ISIS allies Trump officials considering Mar-a-Lago for next meeting with China's Xi: report MORE on Monday will sign an executive order dedicating resources to boost U.S. artificial intelligence (AI), a move that comes as the Trump administration seeks a leg up in its technological race with China. The executive order, titled Accelerating America's Leadership in Artificial Intelligence, will direct federal agencies to dedicate money and manpower towards researching and developing artificial intelligence (AI) while making government data available to the technology's developers. Artificial intelligence is defined as software that allows computers to emulate human intelligence. "This initiative will devote the full resources of the federal government to develop AI," a senior administration official told reporters on Sunday evening. The order directs federal agencies to prioritize funding AI initiatives and open up their troves of data to AI experts, a move that privacy advocates are certain to push back against.

TOKYO/PARIS - What kind of financial blow has the widening scandal surrounding Carlos Ghosn delivered to Nissan Motor Co. and Renault SA? Investors are about to get a glimpse when closely watched earnings releases come out this week. The alliance partners have spent the last two months coping with a major reputational hit from Ghosn's arrest, indictments by Tokyo prosecutors over alleged financial improprieties and an unflattering spotlight on both companies' corporate governance controls. Taken together, these negatives could leave the alliance partners falling behind competitors such as Volkswagen AG and Toyota Motor Corp. in the race to adapt to the changing terrain. The risks may be greater for Nissan since the lion's share of allegations against Ghosn reflect his tenure there, and its business challenges are tougher than Renault's.

As spring approaches in Japan, the country's weather forecasters face one of their biggest missions of the year: predicting exactly when the famed cherry blossoms will bloom. Japan's sakura (cherry blossom) season is feverishly anticipated by locals and visitors alike. Many tourists plan their entire trips around the blooms, and Japanese flock to parks in their millions to enjoy the seasonal spectacle. "People pay more attention to the cherry blossom season than any other flower in Japan," said Ryo Dojo, an official of the statistics unit at the Meteorological Agency. The most basic element of predicting when the delicate pink and white petals will begin to unfurl is a large data set of temperatures.

Naypyitaw is not a common destination for foreign tourists, but some curious visitors are drawn to its oversized official buildings and largely empty, runway-like roads. The junta constructed the city in secret and moved the country's administration there in the mid-2000s.

OVER the past few years, there have been several debates about whether or not private wealth managers would be disrupted by technology. Artificial intelligence (AI)-powered robo-advisors have been slowly becoming popular, attracting clients who want a better service, cheaper rates / lower commissions, and more transparent and unbiased advice about investments. As a result, new-age companies such as Wealthfront, Betterment, and traditional companies offering automated advice such as Charles Schwab and Vanguard are all winning a bigger share of the private wealth market. To fight this trend, banks and financial institutions such as UBS, Standard Chartered, and several others have been helping their private wealth teams bring in more technology into their offering, automate some of their routine tasks, and deliver a better digital-first experience to customers. However, a new survey from Intertrust says that those fighting robo-advisors aren't doing too well.

In a dangerous AI "arms race," China is exporting killer drone weapons and pilotless aircraft with AK-47 rifles to combat zones in the Middle East, Asia, and Africa, U.K.'s The Sun reported. Nicknamed "slaughterbots" in the report, the stealth weapons can deploy a targeted strike from the air "without a human pressing the fire button," per The Sun, citing a report by the U.S.'s Center for a New American Security (CNAS). "Though many current generation drones are primarily remotely operated, Chinese officials generally expect drones and military robotics to feature ever more extensive AI and autonomous capabilities in the future," the think tank's Gregory C. Allen claims, per the report. "Chinese weapons manufacturers already are selling armed drones with significant amounts of combat autonomy." The report pointed to a "Blowfish A2 drone" advertised as having "full autonomy all the way up to targeted strikes," according to Allen.

"Yes ma'am, Roll-Oh get," the robot says, as it goes to the kitchen to prepare dinner, opening a can of food and blowing fire to a candle. Roll-Oh walks clumsily, suspiciously like a man in an uncomfortable costume. Nonetheless, it ably frees the domestic housewife of all her daily chores, at the simple press of a button. This was the promise of robotics, demonstrated in the 1940 short film "Leave it to Roll-Oh", presented at the New York World's Fair. Mechanical robotics already automate so much of our lives, the film argues, that it will be only a matter of time before we can expect personal, four-limbed metal people as ready-made servants: watering our plants, greeting our mailman, helping cook dinner.

The detective will need to capture dependencies between sequential timeconstrained reason about the order in which these sub-goals are executed goal states because the state-space and may need to use knowledge of individual deadlines to must be prohibitively expanded to accommodate put constraints on the possible sub-goal sequences. For a history of successfully achieved sub-goals. Also, example, the detective knows that two key witnesses will policies and value functions derived with stationarity be leaving town for work in the morning and the two main assumptions are not readily decomposable, suspects will likely leave town later in the day. The detective leading to a tension between reward maximization will thus conclude that the witnesses must be questioned and task generalization. We demonstrate a logiccompatible first so that there is enough time and evidence to arrest and approach using model-based knowledge interrogate the suspects, as they cannot be held in custody of environment dynamics and deadline information for longer than a day. The order in which the two witnesses to directly infer non-stationary policies are questioned and the order in which the two suspects are composed of reusable stationary policies. The arrested does not matter for the satisfaction of the task which policies are constructed to maximize the probability only requires that all sub-goals are met before their individual of satisfying time-sensitive goals while respecting deadlines, leading to four distinct possible sequences of time-varying obstacles. Our approach explicitly sub-goals that can be executed. Furthermore, the difficulty maintains two different spaces, a high-level of this task is compounded by the fact that the detective must logical task specification where the task-variables have knowledge of the underlying movement constraints are grounded onto the low-level state-space of and knowledge of the dynamics of the environment.