{"id":96585,"date":"2016-10-10T10:09:42","date_gmt":"2016-10-10T14:09:42","guid":{"rendered":"http:\/\/countingpips.com\/?p=96585"},"modified":"2016-10-10T07:10:13","modified_gmt":"2016-10-10T11:10:13","slug":"artificial-intelligence-the-race-is-on-to-smarten-our-cars","status":"publish","type":"post","link":"https:\/\/www.investmacro.com\/forex\/2016\/10\/artificial-intelligence-the-race-is-on-to-smarten-our-cars\/","title":{"rendered":"Artificial Intelligence: The Race Is On to Smarten Our Cars"},"content":{"rendered":"
October 10, 2016<\/div>
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By WallStreetDaily.com<\/u><\/a> \"Artificial<\/p>\n

Uber\u2019s Pittsburgh Experiment, featuring semi-autonomous vehicles, is up and running. If only its fleet could distinguish the proper path down a one-way street. And Google is reporting smashing results for its autonomous vehicle program.<\/strong><\/i><\/p>\n

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This is a public service alert for all you Yinzers out there: Get off the road; you\u2019re in danger.<\/p>\n

While we\u2019re at it, to unemployed tech bros desperate to get a foot in the Silicon Valley door: Don\u2019t take a gig as a Google autonomous vehicle test driver.<\/p>\n

There were no injuries in this incident, but one of Uber\u2019s self-driving cars went the wrong way down a one-way Pittsburgh street on September 26. Here\u2019s the video<\/strong><\/a>, posted to Facebook by Uber driver Nathan Stachelek.<\/p>\n

Here\u2019s more: A test driver \u201coperating\u201d a Google Lexus-model autonomous vehicle on September 23 was fortunate to escape with no serious damage.<\/p>

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But he did check himself into a local hospital for evaluation after getting T-boned by another car. The Google autonomous vehicle did have the green-light right-of-way through the intersection, and the other car did run a red light. The operator assumed control of the vehicle and tried to override the decision to stop mid-intersection. A collision ensued.<\/p>\n

Is the combination of these incidents cause to put the brakes to the runaway fervor about autonomous vehicles?<\/p>\n

It won\u2019t.<\/p>\n

This is a public service alert for all you Yinzers out there: Get off the road; you\u2019re in danger.<\/em><\/strong><\/p>\n

But events like this illustrate the complexity of artificial intelligence (AI)-human interaction in a real-world setting.<\/p>\n

This is really hard \u2013 as in \u201cdifficult\u201d \u2013 science. We\u2019re talking about solving and integrating concepts such as computer vision, deep learning, machine learning, and latency.<\/p>\n

Uber is field-testing its self-driving technology in Pittsburgh for a pretty solid reason: It\u2019s where Carnegie Mellon University is located, and Carnegie Mellon University is a hotbed for robotics research.<\/p>\n

It\u2019s where the three founders of Anki went to school. Marc Andreesen, the founder of Netscape and a successful venture capitalist, named Anki \u201cthe best robotics startup I\u2019ve ever seen.\u201d<\/p>\n

Anki\u2019s breakthrough is an AI robot named Cozmo.<\/p>\n

Robots and self-driving cars\/autonomous vehicles have a lot in common, including a central problem.<\/p>\n

As Chelsea Finn, a PhD candidate at the University of California, Berkeley, put it, \u201cThe number one challenge is to see the unstructured environment and make actions depending on the state of the environment.\u201d<\/p>\n

The importance of understanding and making decisions in an organic environment is perhaps best illustrated by an extreme example.<\/p>\n

Take the military context, where using self-driving cars and trucks could save lives and reduce burdens on soldiers.<\/p>\n

Dr. Bob Sadowski, Army Chief Roboticist at TARDEC Ground Vehicle Robotics, told Colin Clark of Breaking Defense<\/em> during the 2016 Association of the U.S. Army Annual Meeting and Exposition that his chief concerns are \u201chow you fuse the data\u201d and teaching robots how to do this, because \u201cthey don\u2019t know anything.\u201d<\/p>\n

Clark\u2019s interview with Dr. Sadowski is here<\/strong><\/a>.<\/p>\n

This is really hard \u2013 as in \u201cdifficult\u201d \u2013 science. We\u2019re talking about solving and integrating concepts such as computer vision, deep learning, machine learning, and latency.<\/em><\/strong><\/p>\n

The Army\u2019s current system integrates cameras and sensors to gather data and computers to process same. Cameras \u201care great for giving you visual information.\u201d<\/p>\n

\u201cBut,\u201d as Dr. Sadowski notes, \u201cthey\u2019re not good at giving you 3D depth.\u201d That problem is solved with a remote sensing method known as LIDAR, or \u201clight detection and ranging.\u201d<\/p>\n

An AI sees \u201cdot plots\u201d created via LIDAR that represent objects in the distance. It has to learn, or be taught, to distinguish trees from humans, for example, or something else it doesn\u2019t want to run into.<\/p>\n

Visual information and the LIDAR information are \u201cfused\u201d to establish a \u201ccost map,\u201d which illustrates where the vehicle does or doesn\u2019t want to go \u2013 into a tree or through a human, for example.<\/p>\n

The potential applications are compelling, hauling equipment or even conducting reconnaissance.<\/p>\n

The former task requires \u201cjust a little autonomy,\u201d because soldiers will always be nearby, escorting the load, as it were. The Army is \u201cwithin five to 10 years\u201d of deploying such technology.<\/p>\n

Reconnaissance is another matter entirely. The whole point is to spare soldiers from dangerous, life-threatening work. That\u2019s full autonomy. And the AI would have to be able to assimilate an \u201cunstructured environment.\u201d<\/p>\n

Google, Uber, Tesla, and other entities working on autonomous vehicle technology have the benefit of working in what Dr. Gadowski describes as \u201cstructured environments.\u201d<\/p>\n

San Francisco and downtown Pittsburgh, he notes, probably aren\u2019t going to change too much. They can be mapped, reliably, with help from the GPS network and the continuously evolving \u201ccloud\u201d network that\u2019s full of more and more usable information.<\/p>\n

The potential applications are compelling, hauling equipment or even conducting reconnaissance.<\/em><\/strong><\/p>\n

The Army\u2019s environment is \u201cill-defined,\u201d and there are \u201cusually people shooting back at you.\u201d<\/p>\n

There\u2019s also the problem of sabotage. During World War II, the German Wehrmacht\u2019s Operation Grief included a scheme to reverse and otherwise muck up road and traffic signs and signals to confuse advancing Allied forces.<\/p>\n

Consider, then, the recent difficulties Uber and Google have encountered in \u201cstructured\u201d environments with stop signs, red lights, and other mechanisms that establish some control and predictability.<\/p>\n

Autonomous vehicles are an exciting concept. According to Lux Research, self-driving cars will represent \u201can $87 billion opportunity in 2030.\u201d<\/p>\n

At the same time, even Lux concedes \u201cnone reach full autonomy\u201d by that date.<\/p>\n

It boils down to AI and machine learning.<\/p>\n

And according to Carnegie Mellon computer scientist Phillip Koopman, an automotive industry specialist, \u201cYou just can\u2019t assume this stuff is going to work.\u201d<\/p>\n

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Upticks, Downticks<\/h2>\n

\"Uptick\" The Russell 2000 Index stumbled last week, posting a decline over the five trading days ended Friday, October 7, of 1.2%. The Nasdaq Composite was off 0.3%, while the broad-based S&P 500 was off by 0.7% amid more uncertainty about when the Federal Reserve will finally announce its next interest-rate hike.<\/p>\n

\"Uptick\" S&P 500 companies posted aggregate dividend growth of 5.24% for the three months ended September 30, 2016, the 26th consecutive quarter of positive dividend growth.<\/p>\n

\"Uptick\" According to the U.S. Department of Labor Bureau of Labor Statistics, nonfarm payrolls grew by 156,000 during September, below a consensus forecast of 170,000. August payrolls were revised downward by 7,000, while July\u2019s were 23,000 lower than first reported. Payrolls averaged 192,000 during the third quarter, compared to 146,000 during the second quarter and 196,000 during the first. During 2015 job growth averaged 229,000 per month.<\/p>\n

\"Uptick\" Private-sector wages were up 0.2% month over month and 2.6% year over year. The labor force participation rate rose to 62.9% in September from 62.8% in August, as the unemployment rate ticked up to 5.0% from 4.9% in August.<\/p>\n

\"Uptick\" Jon Hilsensrath of The Wall Street Journal<\/em>, a reporter with particularly strong sources inside the Marriner S. Eccles Federal Reserve Board Building, wrote Friday morning<\/strong><\/a>, \u201cThe subdued September jobs report ensures the Federal Reserve won\u2019t be raising short-term interest rates at its November meeting, a week before the U.S. presidential election, and creates a new thread of uncertainty about its action in mid-December.\u201d<\/p>\n

\"Uptick\" A product of a near half-century\u2019s worth of work, Terrence Malick\u2019s \u201cVoyage of Time: The IMAX Experience\u201d<\/strong><\/a> reflects that level of nurturing and is well worth the effort to see it as the artist intended \u2013 on the very big screen. According to Boing Boing<\/strong><\/a>, \u201cIt\u2019s a psychedelic meditation on the history of the cosmos that\u2019s very kid-friendly, and a wonderful reminder of the big, big<\/em> picture.\u201d<\/p>\n

Smart Investing,<\/p>\n

David Dittman
\nEditorial Director, Wall Street Daily<\/i><\/p>\n

The post Artificial Intelligence: The Race Is On to Smarten Our Cars<\/a> appeared first on Wall Street Daily<\/a>.<\/p>\n

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 <\/p>\n","protected":false},"excerpt":{"rendered":"

By WallStreetDaily.com Uber\u2019s Pittsburgh Experiment, featuring semi-autonomous vehicles, is up and running. If only its fleet could distinguish the proper path down a one-way street. And Google is reporting smashing results for its autonomous vehicle program. This is a public service alert for all you Yinzers out there: Get off the road; you\u2019re in danger. […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-96585","post","type-post","status-publish","format-standard","hentry","no-post-thumbnail"],"_links":{"self":[{"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/posts\/96585","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/comments?post=96585"}],"version-history":[{"count":2,"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/posts\/96585\/revisions"}],"predecessor-version":[{"id":96598,"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/posts\/96585\/revisions\/96598"}],"wp:attachment":[{"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/media?parent=96585"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/categories?post=96585"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.investmacro.com\/forex\/wp-json\/wp\/v2\/tags?post=96585"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}