l AI tools came out of the lab in 2016
itMYti.com < New IT WebNews
Category: news    |    Added: 2016-12-23 08:55:03    |    View: 128

The kinds of tools that built one of the most remarkable AIs of the year are now available for any business to use

Roboy angry robot

The projector in Roboy's head can be used to express emotions -- here, the mouth turns down and the robot's eyes and cheeks turn red in a cartoon-like expression of anger.

Credit: Peter Sayer / IDG News Service
"; adDivString = "
" + adString + "
"; IDG.GPT.defineGoogleTagSlot(slotName ,[[320,50],[300,250],[300,50]]); } placementDiff = applyInsert($(this), adDivString); if (DEBUG) { console.log("Just placed an ad and the placementDiff is: " + placementDiff); } placementTarget = cumulativeHeight + placementDiff + INTERMODULE_HEIGHT + AD_HEIGHT_BUFFER; } else if (moduleCounter < articleDRRModuleList.length){ var elementId = "drr-mod-"+moduleCounter; var moduleDivString = "
"; modules.push(elementId); placementDiff = applyInsert($(this), moduleDivString); if (DEBUG) { console.log("Just placed a module and the placementDiff is: " + placementDiff); } placementTarget = cumulativeHeight + placementDiff + INTERMODULE_HEIGHT + MODULE_HEIGHT_BUFFER; moduleCounter++; } loopCounter++; } // Avoid placing elements too soon due to non-large figures inflating the cumulative height if ($(this).is("figure") && !$(this).is("figure.large")) { cumulativeHeight += GRAF_HEIGHT; } else { cumulativeHeight += $(this).height() + GRAF_HEIGHT; } } }); // end $("#drr-container").children().each() // clone Related Stories module to come in after eighth para in article body for mobile breakpoint display var $relatedStories = $('.related-promo-wrapper'); if ($relatedStories.length) { var $relatedStoriesClone = $relatedStories.clone(); $relatedStoriesClone.insertAfter( "#drr-container > p:eq(7)"); } // For mobile only, place ad after second paragraph. if (firstMobileAdHtml) { $(firstMobileAdHtml).insertAfter("#drr-container > p:eq(1)"); } var $insiderPromo = $('.insider-promo-wrapper'); if ($insiderPromo.length) { var $insiderPromoClone = $insiderPromo.clone(); $insiderPromoClone.insertAfter( "#drr-container > p:eq(1)"); } IDG.GPT.trackOmniture(); // Add Right rail module content var placeModule = function( data ) { var placementId = $(data).attr("data-placement-id"); $( "#"+placementId ).html( data ); }; for (i=0; i" + adString + "
"; } /** * @param jqo Original jquery object target * @param divString The div to be inserted. * @return Difference in height between original placement target and final target. * Checks first 6 elements for an allowable placement (600 pixel window). * If none, place element in first location that does not follow a reject element. */ function applyInsert(jqo, divString) { if (DEBUG) { console.log("applyInsert at top and jqo index is: " + jqo.index()); } for (var i=0; i<=6; i++) { $thisElement = jqo.nextAll().andSelf().slice(i, i+1); if (DEBUG) { console.log("Checking first six and i is: " + i + " and this element index is " + $thisElement.index() ); } if ($thisElement.index() < 0) { break; } if (allowPlacement($thisElement)) { return addElement(jqo, $thisElement, divString); } } if (DEBUG) { console.log("No nearby allows so just place in first spot that is not after reject."); } var numElements = jqo.nextAll().length; var startIndex = jqo.index(); for (var i=startIndex; i<=numElements; i++) { var $element = $("#drr-container").children().eq(i); // This element is eligible when not null, not in placement index, and previous element is not reject if ($element != null && (placementIndex == null || placementIndex.indexOf(i) == -1) && !isReject($element.prev())) { return addElement(jqo, $element, divString); } } if (DEBUG) { console.log("Not going to place element: return 0."); } return 0; } /** * @param jqo Original jquery object * @param allowElement Element that is good placement for module/ad * @param divString The div to be inserted before the good element * @return placementHeightDiff Diff in height between original placement target and current target. * * If element is not too close to the end the insert the div before allowable element. * Add element index to placementIndex to keep track of which elements already have placements */ function addElement(jqo, allowElement, divString) { var offset = allowElement.index() - jqo.index(); if (DEBUG) { console.log("addElement: jqo index is " + jqo.index() + " allowElement index is " + allowElement.index()); } if (elementNotNearEnd(allowElement, RIGHT_PIXEL_WINDOW)) { allowElement.before(divString); if (DEBUG) { console.log("addElement: Adding " + allowElement.index() + " to placementIndex."); } placementIndex.push(allowElement.index()); if (offset == 0) { return 0; } else { return getHeightDifference(jqo,allowElement); } } else { if (DEBUG) { console.log("addElement: Near the end so do NOT add."); } return 0; } } function getHeightDifference(jqo,allowElement) { var offset = allowElement.index() - jqo.index(), height = 0, children = null; if (offset > 0) { children = $("#drr-container").children().slice(jqo.index(), allowElement.index()); } else { children = $("#drr-container").children().slice(allowElement.index(), jqo.index()); } if (children != null) { children.each(function(i) { if (DEBUG) { console.log("About to add this element's height to heigh diff offset"); console.log($(this)); } height += $(this).height() + GRAF_HEIGHT; }); } if (offset < 0) { height *= -1; } if (DEBUG) { console.log("getHeightDifference: offset was " + offset + " and height diff is : " + height); } return height; } function allowPlacement(jqo) { if (jqo.prev() != null && isReject(jqo.prev())) { return false; } return true; } function isReject(jqo) { if (jqo != null) { if (jqo.is('h2') || jqo.is('h3') || jqo.is('h4') || jqo.is('h5')) { if (DEBUG) { console.log("isReject: found header"); } return true; } } return false; } // Returns true if height of all elements after this one is more than 500; false otherwise function elementNotNearEnd(element, pixelWindow) { if (pixelWindow === null) { pixelWindow = 500; } if (element === null) { return false; } var remainingHeight = 0, children = $("#drr-container").children().slice(element.index()); if (children === null) { return false; } children.each(function(i){ remainingHeight += $(this).height(); }); if ( remainingHeight > pixelWindow) { return true; } else { if (DEBUG) { console.log("Element too close to end. Remaining height is: " + remainingHeight + " and window is " + pixelWindow); } return false; } } } // end function executeDRRMobile() function executeDRRDesktop() { var heroImgHeight = $('figure.hero-img').outerHeight(true); if (heroImgHeight === null) { heroImgHeight = 0; } var galleryItemHeight = $('figure.thm-gallery').outerHeight(true); if (galleryItemHeight === null) { galleryItemHeight = 0; } var atAglanceTop = $('.at-a-glance.top').height(); if (atAglanceTop === null) { atAglanceTop = 0; } var drrContainerHeight = $('div#drr-container').outerHeight(true); var topIMUheight = $('#topimu').height(); if (topIMUheight === 0) { topIMUheight = 600; } var relatedPromoHeight = $('div.related-promo-wrapper').outerHeight(true); if (relatedPromoHeight === null) { relatedPromoHeight = 0; } var videoHowtoHeight = $('div#video-howto-wrapper').outerHeight(true); if (videoHowtoHeight === null) { videoHowtoHeight = 0; } var teadsInreadHeight = $('div.teads-inread').height(); if (teadsInreadHeight === null) { teadsInreadHeight = 0; } var unrulyAdHeight = $('.unruly_in_article_placement').height(); if (unrulyAdHeight === null) { unrulyAdHeight = 0; } //just in case the in article ads are picked up... var collapsibleAdHeight = unrulyAdHeight + teadsInreadHeight; var workingRRheight = ( (heroImgHeight + galleryItemHeight + atAglanceTop + drrContainerHeight) - (topIMUheight + relatedPromoHeight + videoHowtoHeight) ); workingRRheight = workingRRheight - collapsibleAdHeight; var DEBUG = false; if (DEBUG) { console.log('-----working RR height = ' + workingRRheight); } var articleDRRModuleList = ["dealposts","products.latest-reviews"], moduleUrls = [], modules = [], moduleCounter = 0, loopCounter = 0; var adPositions = new Array(0,1,3); // IMU, IMU, module, IMU, module if (false) { var dealpostsIdx = articleDRRModuleList.indexOf("dealposts"); if (dealpostsIdx > -1) { articleDRRModuleList.splice(dealpostsIdx, 1); adPositions = [0, 1, 2]; } } for (var i=0; i 650) { numItems = 1; } if (workingRRheight > 1350) { numItems = 2; } if (workingRRheight > 2300) { numItems = 3; } if (workingRRheight > 2950) { numItems = 4; } if (workingRRheight > 3650) { numItems = 5; } for (var currIndex=0;currIndex
"; adDivString = "
" + adString + "
"; IDG.GPT.defineGoogleTagSlot(slotName ,[[320,50],[300,250],[300,50]]); } //$('#drr-container > p').first().before(adDivString); //$('#drr-top-ad').append(adDivString); $(adDivString).appendTo('#drr-top-ad'); if (DEBUG) { console.log("-----Just placed an AD currIndex = " + currIndex); } } else if (moduleCounter < articleDRRModuleList.length){ var elementId = "drr-mod-"+moduleCounter; var moduleDivString = "
"; modules.push(elementId); //$('#drr-container > p').first().before(moduleDivString); $('#drr-top-ad').append(moduleDivString); if (DEBUG) { console.log("-----Just placed a MODULE and currIndex = " + currIndex); } moduleCounter++; } } //end for loop IDG.GPT.trackOmniture(); // Add Right rail module content var placeModule = function( data ) { var placementId = $(data).attr("data-placement-id"); $( "#"+placementId ).html( data ); }; for (i=0; i" + adString + "
"; } } // end function executeDRRDesktop()

You shouldn't anthropomorphize computers: They don't like it.

That joke is at least as old as Deep Blue's 1997 victory over then world chess champion Garry Kasparov, but even with the great strides made in the field of artificial intelligence over that time, we're still not much closer to having to worry about computers' feelings.

Computers can analyze the sentiments we express in social media, and project expressions on the face of robots to make us believe they are happy or angry, but no one seriously believes, yet, that they "have" feelings, that they can experience them.

Other areas of AI, on the other hand, have seen some impressive advances in both hardware and software in just the last 12 months.

Deep Blue was a world-class chess opponent -- and also one that didn't gloat when it won, or go off in a huff if it lost.

Until this year, though, computers were no match for a human at another board game, Go. That all changed in March when AlphaGo, developed by Google subsidiary DeepMind, beat Lee Sedol, then the world's strongest Go player, 4-1 in a five-match tournament.

AlphaGo's secret weapon was a technique called reinforcement learning, where a program figures out for itself which actions bring it closer to its goal, and reinforces those behaviors, without the need to be taught by a person which steps are correct. That meant that it could play repeatedly against itself and gradually learn which strategies fared better.

Reinforcement learning techniques have been around for decades, too, but it's only recently that computers have had sufficient processing power (to test each possible path in turn) and memory (to remember which steps led to the goal) to play a high-level game of Go at a competitive speed.

Better performing hardware has moved AI forward in other ways too.

In May, Google revealed its TPU (Tensor Processing Unit), a hardware accelerator for its TensorFlow deep learning algorithm. The ASICs (application-specific integrated circuit) can execute the types of calculations used in machine learning much faster and using less power than even GPUs, and Google has installed several thousand of them in its server racks in the slots previously reserved for hard drives.

The TPU, it turns out, was one of the things that made AlphaGo so fast, but Google has also used the chip to accelerate mapping and navigation functions in Street View and to improve search results with a new AI tool called RankBrain.

Google is keeping its TPU to itself for now, but others are releasing hardware tuned for AI applications. Microsoft, for example, has equipped some of its Azure servers with FPGAs (field-programmable gate arrays) to accelerate certain machine learning functions, while IBM is targeting similar applications with a range of PowerAI servers that use custom hardware to link its Power CPUs with Nvidia GPUs.

For businesses that want to deploy cutting-edge AI technologies without developing everything from scratch themselves, easy access to high-performance hardware is a start, but not enough. Cloud operators recognize that, and are also offering AI software as a service. Amazon Web Services and Microsoft's Azure have both added machine learning APIs, while IBM is building a business around cloud access to its Watson AI.

The fact that these hardware and software tools are cloud-based will help AI systems in other ways too.

Being able to store and process enormous volumes of data is only useful to the AI that has access to vast quantities of data from which to learn -- data such as that collected and delivered by cloud services, for example, whether its information about the weather, mail order deliveries, requests for rides or peoples' tweets.

Access to all that raw data, rather than the minute subset, processed and labelled by human trainers, that was available to previous generations of AIs, is one of the biggest factors transforming AI research today, according to a Stanford University study of the next 100 years in AI.

And while having computers watch everything we do, online and off, in order to learn how to work with us might seem creepy, it's really only in our minds. The computers don't feel anything. Yet.

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