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  • CHATBOTS EXPLAINED: Why businesses should be paying attention to the chatbot revolution (FB, AAPL, GOOG)

    bii chatbot ecosystem

    Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

    Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

    In a new report from BI Intelligence, we explore the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact. We outline the burgeoning bot ecosystem by segment, look at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. 

    The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, we compare the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

    Here are some of the key takeaways:Chatbots Explainer Report Cover

    • AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
    • Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
    • The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
    • Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

    In full, the report:

    • Breaks down the pros and cons of chatbots.
    • Explains the different ways businesses can access, utilize, and distribute content via chatbots.
    • Forecasts the potential impact chatbots could have for businesses.
    • Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.
    • And much more.

    Interested in getting the full report? Here are several ways to access it:

    1. Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >> Learn More Now
    2. Access the Ultimate Digital Media Reports Bundle and save 92% today. You will gain immediate access to the Chatbots Explainer and 45 other in-depth research reports covering the most important topics impacting the digital media space. >> Bundle & Save Now
    3. Access the Ultimate Mobile, Apps & Platforms Reports Bundle and save 95% today. You will gain immediate access to the Chatbots Explainer and 75 other comprehensive research reports covering the most important topics impacting the mobile. >> Bundle & Save Now
    4. Purchase & download the full report from our research store. >> Purchase & Download Now

    Learn more:

    Join the conversation about this story »

  • The top 50 dream companies for business students around the world

    Young people working at Google's office

    Google is known for offering appealing perks, great pay, and an exceptional workplace culture — so it's no surprise that undergraduate business students find the search behemoth to be the most desirable employer.

    Earlier this year, Universum, a global research and advisory firm, surveyed about 100,000 of these undergraduates across the globe and asked them to choose the companies and organizations they'd most like to work for.

    Universum then put together a ranking of the most desirable employers, based on the number of undergraduate business students who chose a company as one of their dream employers. 

    Google, which specializes in online advertising technologies, cloud computing, software, and, of course, search, landed at the top of the list for a second consecutive year.

    Apple, EY, Goldman Sachs, and PwC rounded out the top five.

    Here are the top 50:

    SEE ALSO: The 50 best companies to work for in America

    50. 3M

    The 3M Company is a multinational, Minnesota-based corporation specializing in products like adhesives and laminates.



    49. Dell

    With over 103,300 employees worldwide, Dell develops, sells, and supports personal computers. 



    48. Shell

    Royal Dutch Shell is considered one of the six oil and gas "supermajors."



    See the rest of the story at Business Insider
  • The EU is threatening to fine Google for violating antitrust regulations (googl)

    sundar pichai google ceo alphabet

    EU antitrust regulators plan to order Alphabet's Google to stop paying financial incentives to smartphone makers to pre-install Google Search exclusively on their devices and warned the company of a large fine, an EU document showed.

    The document, running to more than 150 pages, was sent to complainants last week for feedback. Google received a copy in April in which the European Commission accused it of using its dominant Android mobile operating system to shut out rivals.

    The EU competition enforcer in its charge sheet, known as a statement of objections, said it planned to tell the U.S. technology giant to halt payments or discounts to mobile phone manufacturers in return for pre-installing Google's Play Store with Google Search.

    The regulators also want to prevent Google from forcing smartphone makers to pre-install its proprietary apps if this restricts their ability to use competing operating systems based on Android.

    Google "cannot punish or threaten" companies for not complying with its conditions, according to the document seen by Reuters.

    The Commission's investigation followed a complaint by FairSearch, a lobby group supported by companies that want to ensure they are not disadvantaged by search engine market dominance, in March 2013.

    Google could face a large fine because the anti-competitive practices, which started from January 2011, are still ongoing, the document said.

    "The Commission intends to set the fine at a level which will be sufficient to ensure deterrence," it said.

    The penalty could be based on revenue generated from AdWords clicks by European users, Google Search product queries, Play Store apps purchases and AdMob's in-app advertisements.

    Commission spokesman Ricardo Cardoso declined to comment. Google which has previously denied any wrongdoing, did not immediately reply to a request for comment.

    Separately, the Commission is investigating whether Google favors its own shopping service over those of rivals, and could also fine it in that case.

    Google may have to rank rival comparison shopping services in the same way as its own services, the charge sheet sent in July said. The document, close to 150 pages, was heavily edited, with large sections of confidential information redacted by Google.

    The Commission said it would decide at a later stage whether to let Google charge competitors for displaying their services prominently, with the amount corresponding to Google's operating cost or a nominal amount based on the lowest reserve price for AdWords which is currently 0.01 euro per click.

    SEE ALSO: Google might release a new laptop and tablet that run on a completely new operating system

    Join the conversation about this story »

    NOW WATCH: Columbia law professor argues that 'privacy has been privatized'

  • 24 mouthwatering photos of Google’s legendary free food

    google food

    One of the many perks of working at Google is the food: free breakfast, lunch, and dinner.

    At the Googleplex headquarters in Mountain View, California, approximately 30 different cafés serve more than 40,000 gourmet meals a day.

    From juicy hot dogs to strawberry roses, here are 24 mouthwatering meals served inside Google's cafeterias, according to Instagrammers.

     

    SEE ALSO: One of Apple's most important execs just joined the board of a $25 billion genetics company

    For breakfast, Googlers can head to the Stock Market Café for Crab Benedict ...

    Instagram Embed:
    http://instagram.com/p/dXJXIpNdIz/embed/
    Width: 800px

     



    ... chocolate French toast with Nutella sauce ...

    Instagram Embed:
    http://instagram.com/p/1Q1FR6jHRI/embed/
    Width: 800px

     



    ... or house-pickled trout on a slice of crostini.

    Instagram Embed:
    http://instagram.com/p/lXTuOcDHTQ/embed/
    Width: 800px

     



    See the rest of the story at Business Insider
  • California revises stance on self-driving car testing following criticism from Google

    Google driverless car

    California will allow companies more leeway in testing self-driving cars on public roads while restricting how the nascent technology is advertised under revised draft regulations released on Friday.

    In one of the biggest changes, the new regulations would allow for the absence of a driver in some instances, provided there is two-way communication with the vehicle.

    The original draft regulations by the Department of Motor Vehicles were criticized by some tech companies, such as Alphabet Inc's Google, and other automakers as being overly restrictive and stifling innovation. Moreover, disabled groups complained that the requirement of a driver in the car hurt the very people that autonomous vehicles would most benefit.

    California has been at the forefront of the fast-growing autonomous vehicle industry, fueled by technology companies in Silicon Valley, and is one of a handful of states to have passed regulations enabling self-driving car testing on public roads.

    data-bi-ad="" data-ad-container="" data-adunit="desktop/reuters/reuters/post" data-authors="" data-pagetype="post" data-region="Desktop In Post Ad" data-responsive="[[[1240,0],[[728,90],[800,100],[800,480],[550,300]]],[[0,0],[[300,250],[600,100],[550,300]]]]" data-sizes="300x250,550x300,600x100,728x90,800x100,800x480" data-tag="reuters" data-url="/r-california-proposes-giving-more-freedom-to-test-self-driving-cars-2016-9" data-views="0-5000" id="ad-b9ff9a91-64e0-4527-f451-05f624033118" data-google-query-id="CNm8sbvXuc8CFYK_swodDFMAOQ">

    Currently, 15 companies have permits to drive autonomous vehicles on public roads in the state provided there is a licensed driver in the car.

    Now, carmakers will have to certify that they have met a 15-step safety assessment issued by the National Highway Traffic Safety Administration. That safety assurance means self-driving cars will no longer be required to be tested by a third-party, as in the original proposal.

    The changes also prohibit advertising semi-autonomous systems, like enhanced cruise control and lane-assist systems, using terms like "autonomous" or "self-driving." The systems help steer and keep vehicles in lanes but still require a human to remain engaged.

    Such partially autonomous systems, which transfer control of the vehicle between the driver and the car and vice versa, have come under scrutiny since a May fatality involving a Tesla Motors Inc driver using the company's Autopilot semi-autonomous system.

    Some consumer groups and others have criticized the Silicon Valley electric car maker for the choice of the name Autopilot, which could suggest that the technology does not require a driver's intervention.

    The draft regulations face a new period of public comment before being finalized.

    SEE ALSO: A Tesla Model S was driving with Autopilot when it got into a bus crash in Germany

    Join the conversation about this story »

    NOW WATCH: We got a ride in a self-driving Uber — here's what it was like

  • CHATBOTS EXPLAINED: Why businesses should be paying attention to the chatbot revolution (FB, AAPL, GOOG)

    bii chatbot ecosystem

    Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes. 

    Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

    In a new report from BI Intelligence, we explore the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact. We outline the burgeoning bot ecosystem by segment, look at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer. 

    The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, we compare the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

    Here are some of the key takeaways:Chatbots Explainer Report Cover

    • AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
    • Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
    • The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies. 
    • Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.  

    In full, the report:

    • Breaks down the pros and cons of chatbots.
    • Explains the different ways businesses can access, utilize, and distribute content via chatbots.
    • Forecasts the potential impact chatbots could have for businesses.
    • Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.
    • And much more.

    Interested in getting the full report? Here are several ways to access it:

    1. Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >> Learn More Now
    2. Access the Ultimate Digital Media Reports Bundle and save 92% today. You will gain immediate access to the Chatbots Explainer and 45 other in-depth research reports covering the most important topics impacting the digital media space. >> Bundle & Save Now
    3. Access the Ultimate Mobile, Apps & Platforms Reports Bundle and save 95% today. You will gain immediate access to the Chatbots Explainer and 75 other comprehensive research reports covering the most important topics impacting the mobile. >> Bundle & Save Now
    4. Purchase & download the full report from our research store. >> Purchase & Download Now

    Learn more:

    Join the conversation about this story »

  • THE TRANSFORMATION OF THE AUTOMOBILE 2016: Forecasts, trends, and analyses on the disruption of the automotive industry

    Estimated Connected Car Shipments

    Over the past year, there has been a significant uptick in the number of connected cars on the road. And as internet integration becomes more commonplace, the automobile as we know it will transform.

    Over the next five to 10 years, this internet integration is expected to change the car ownership model, create a new platform for consumers to access content, lead to fully autonomous vehicles, and revolutionize the auto industry.

    The market position of the car today is similar to where the smartphone was in 2010 — it's just taken off and is ready to explode. 

    In a new report from BI Intelligence, we examine the transformation of the automobile. We examine all areas of the changing automotive market, including the market size for connected cars, automakers benefits and connection strategies, market leaders, consumer demand, and more.

    Here are some of the key takeaways from the report:

    • Over 380 million connected cars will be on the road by 2021. The market has seen a significant increase in automakers plans to connect the majority of the vehicles they sell and as a result, we've increased our 2015 forecast.
    • Automakers are connecting the vehicles they sell because the connection offers clear business opportunities.
    • Consumers are adopting the connected car faster than expected. We identify the 3 factors that causing the increase in demand.
    • Tech companies will play a major role in the future of the automotive market. The big question is whether tech companies will eventually manufacture cars?
    • Fully autonomous cars are only a few years away. Technological, regulatory, and consumer adoption hurdles still remain, but there have been many strides towards a car that can drive itself from point A to point B with little to no human interaction.

    In full the report:

    • Forecasts connected car shipments
    • Identifies automakers strategy for connection
    • Analyzes consumer interest in the connected car
    • Examines Apple CarPlay and Android Auto
    • Discusses the potential changing car ownership model
    • Describes the evolution of the self-driving car
    • Identifies top connected car and fully autonomous car barriers

    Interested in getting the full report? Here are two ways to access it:

    1. Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >> Learn More Now
    2. Purchase & download the full report from our research store. >> Purchase & Download Now

    Join the conversation about this story »

  • Machine learning has boosted Google's translation capabilities to near-human levels

    Google TranslateNo one would accuse Google Translate, the favored tool of unscholarly high school language students everywhere, of being an inaccurate interpreter. 

    The 10-year-old internet interpreter can fluently translate more than 100 tongues, recognize foreign restaurant menus and signage, and differentiate between dialects in real time.

    But there’s always room for improvement, and in Translate’s case, it’s occurring through machine learning.

    The project is called Google Neural Machine Translation, or GNMT, and it isn’t strictly speaking new. It was first employed to improve the efficiency of single-sentence translations, explained Google engineers Quoc V. Le and Mike Schuster, and did so ingesting individual words and phrases before spitting out a translation. But the team discovered that the algorithm was just as effective at handling entire sentences — even reducing errors by as much as 60 percent. And better still, it was able to fine-tune the accuracy over time. “You don’t have to make design choices,” Schuster said. “The system can entirely focus on translation.”

    In a whitepaper published on Monday, the Google Brain team detailed the ins and outs of GNMT. Under the hood is long short-term memory, or LSTM, a neural networking technique that works a bit like human memory. Conventional translation algorithms divides a sentence into individual words which are matched to a dictionary, but LSTM-powered systems like Google’s new translation algorithm are able to “remember,” in effect, the beginning of a sentence when they reach the end. Translation is thus tackled bilaterally: GNMT breaks down sequences of words into their syntactical components, and then translates the result into another language.

    GNMT’s approach is a boon for translation accuracy, but historically, such methods haven’t been particularly swift. Google, however, has employed a few techniques that dramatically boost interpretation speed.

    As Wired explains, neural networks usually involve layered calculations — the results of one feeds into the next — a speed bump which Google’s model mitigates by completing what calculations it can ahead of time. Simultaneously, GNMT leverages the processing boost provided by Google’s specialized, AI-optimized computer chips it began fabricating in May. The end result? The same sentence that once took ten seconds to translate via this LSTM model now takes 300 milliseconds.

    And the improvements in translation quality are tangible. In a test of linguistic precision, Google Translate’s old model achieved a score of 3.6 on a scale of 6. GNMT, meanwhile ranked 5.0 — or just below the average human’s score of 5.1.

    It’s far from perfect, Schuster wrote. “GNMT can still make significant errors that a human translator would never make, like dropping words … mistranslating proper names or rare terms … and translating sentences in isolation rather than considering the context of the paragraph or page.” And prepping it required a good deal of legwork. Google engineers trained GNMT for about a week on 100 graphics processing units — chips optimized for the sort of parallel computing involved in language translation. But Google is confident the model will improve. “None of this is solved,” Schuster said. “But there is a constant upward tick.”

    Google isn’t rolling out GNMT-powered translation broadly, yet — for now, the method will remain relegated to Mandarin Chinese. But the search giant said it’ll begin AI-powered translations of new languages in the coming months.

    GNMT may be the newest product of Google’s machine learning experiments, but it’s hardly the first. Earlier this year, AlphaGo, software produced by the company’s DeepMind division, became the first AI in history to beat a human grand master at the ancient game of Go. Earlier this summer, Google debuted DeepDream, a neural network with an uncanny ability to detect faces and patterns in images. And in August, Google partnered with England’s National Health Service and the University College London Hospital to improve treatment techniques for head and neck cancer.

    Not all of Google’s artificial intelligence efforts are as high-minded. Google Drive uses machine learning to anticipate the files you’re most likely to need at a given time. Calendar ‘s AI-powered Smart Scheduling suggests meeting times and room preferences based on the calendars of all parties involved. And Docs Explore shows text, images, and other content Google thinks is relevant to the document on which you’re working.

    SEE ALSO: A man went on a rampage in an Apple Store, smashing a bunch of iPhones with a metal ball

    Join the conversation about this story »

    NOW WATCH: These secret codes let you access hidden iPhone features

  • Google is developing an algorithm to replace one of the most complex parts of treating cancer

    cancer tumor

    Working out how to zap a tumor with radiation is a laborious process for physicians.

    Google’s machine-learning division, DeepMind, thinks AI can help ease the burden.

    When medics apply radiotherapy to a cancer patient, they have to carefully determine which parts of the body should be exposed to radiation in order to kill the tumor while ensuring that as much healthy surrounding tissue as possible is preserved.

    The process, known as segmentation, requires the doctor to manually draw areas that can and can’t be treated onto a 3-D scan of the patient’s tumor site.

    The process is particularly complex for head and neck cancers, in which the tumor often sits immediately next to many important anatomical features.

    Now, though, DeepMind will work with University College Hospital in London to develop an artificial-intelligence system that can automate the process. DeepMind will analyze 700 anonymized scans from former patients who suffered from head and neck cancers.

    hospitalThey hope to create an algorithm that can learn how physicians make decisions about this part of the treatment process, ultimately segmenting the scans automatically.

    “Clinicians will remain responsible for deciding radiotherapy treatment plans, but it is hoped that the segmentation process could be reduced from up to four hours to around an hour,” explains DeepMind.

    In time, the DeepMind team hopes, the same algorithm might find application in treating cancers elsewhere in the body.

    IBM’s Watson supercomputer has also been applying machine learning to personalized cancer treatment, though its approach is a little more bookish.

    It’s currently drawing on 600,000 medical evidence reports and 1.5 million patient records and clinical trials to help doctors develop better treatment plans for cancer patients.

    This isn’t DeepMind’s first foray into medical research, either—in fact, this is the third project that it’s announced in collaboration with the U.K.’s National Health Service.

    After coming under fire earlier in the year when an app project appeared to provide DeepMind with free access to 1.6 million patients’ records, the research outfit recently announced that it was helping to spot the early signs of visual degeneration by sifting through a million eye scans.

    Perhaps it’s working its way down the body.

    (Read more: DeepMind, “DeepMind’s First Medical Research Gig Will Use AI to Diagnose Eye Disease”)

    Join the conversation about this story »

  • Ever needed a private meeting space in an open office? MIT and Google invented one

    Open office spaces look cool and offer a more open workspace, but disruption and lack of privacy are ongoing issues. Inspired by a conversation with Google, MIT’s Self-Assembly Lab designed a drop-down cubicle that creates a private meeting area in open space, according to ZDNet.

    The Transformable Meeting Space can be installed in existing open office spaces or factory floors without significant structural or electromechanical requirements. You just need a high enough ceiling and the means to hang the retractable shell at a sufficient height from the floor.

    The self-forming meeting pod is comprised of 36 felt-lined fiberglass rods woven together. The structure remains suspended above the floor until needed. When someone wants to call a private meeting, or simply have a place to focus or work without disruption, the transformation is easy. The felt lining on the rods keeps noise from traveling outside the pod.

    A counter weighted, mechanical pulley system with two handles hangs from the retractable shell. Pull one handle and the shell gradually drops down. The concept design example forms an enclosure with space for six to eight people that measures 8 feet tall and 10 feet in diameter. When the meeting is over, or you no longer need private space, pull the second handle and the structure rises out of the way.

    Employee backlash about open space offices is growing, according to Fortune.  The list of complaints include constant disruption, decreased productivity, the increased spread of communicable diseases, and, in a cited Bloomberg article, “being forced to listen to phone calls about the veterinary issues of your co-workers’ cats.”

    So if open offices are falling out of favor, the lure of the open concept boosting collaboration and joint creativity is still strong. Startups adding and changing employees and work groups on the fly are drawn to the versatility of offices without walls.

    Alternative solutions like the Transformable Meeting Space could be one method to have it both ways without disruptive structural change or high expense. A suspended gridwork with multiple retractable pods of different sizes that could be repositioned would enable a large, open space to be reconfigured for private work and group meeting spaces as needed.

    The Self-Assembly Lab is a “cross-disciplinary research lab at MIT inventing self-assembly and programmable material technologies aimed at reimagining construction, manufacturing, product assembly and performance,” according to the lab’s website.

    SEE ALSO: We tried cryotherapy, the crazy treatment that plunges you to -100C and makes your body think it's dying

    Join the conversation about this story »

    NOW WATCH: Scientists discovered something 'shocking' that could rewrite a key part of human evolution

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