Tag / microsoft
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Selon la dernière étude Ovum . La planète comptera plus d’assistants digitaux vocaux que d’êtres humains en 2021.
A cette date estime l’étude, Google Assistant, présent sur une majorité de terminaux mobiles (contrairement à Alexa d’Amazon) dominera le marché des Assistants digitaux vocaux doublés d'Intelligence artificielle avec 23,3% de parts de marché devant Bixby de Samsung à 14,5%, Siri d’Apple à 13,1%, Amazon Alexa à 3,9% et Microsoft Cortana à 2,3%.
Ovum qui souligne l’importance de la généralisation de l’assistant Google pour le futur des recherches sponsorisées du géant de Mountain View anticipe - au delà des smartphones et tablettes -une généralisation massive des assistants virtuels sur toute une gamme de nouveaux terminaux : wearables, smart TV, set top boxes et media streamers.
Malgré la vogue des smart speakers comme Alexa/Echo d'Amazon, Ovum précise que les terminaux TV Intelligents (Smart TV, Set top boxes et Media streamers) ..
Using data science to predict how people in companies are changing may sound futuristic. As we wrote recently, change management remains one of the few areas largely untouched by the data-driven revolution. But while we may never convert change management into a “hard science,” some firms are already benefiting from the potential that these data-driven techniques offer.
One of the key enablers is the analysis of email traffic and calendar metadata. This tells us a lot about who is talking to whom, in what departments, what meetings are happening, about what, and for how long. These sorts of analyses are helping EY, where some of us work, by working with Microsoft Workplace Analytics to help clients to predict the likelihood of retaining key talent following an acquisition and to develop strategies to maximize retention. Using email and calendar data, we can identify patterns around who is engaging with whom, which parts of the organization are under stress, and which individuals are m..
There is no argument about whether artificial intelligence (AI) is coming. It is here, in automobiles, smartphones, aircraft, and much else. Not least in the online search abilities, speech and translation features, and image recognition technology of my employer, Alphabet.
The question now moves to how broadly AI will be employed in industry and society, and by what means. Many other companies, including Microsoft and Amazon, also already offer AI tools which, like Google Cloud, where I work, will be sold online as cloud computing services. There are numerous other AI products available to business, like IBM’s Watson, or software from emerging vendors.
Whatever hype businesspeople read around AI — and there is a great deal — the intentions and actions of so many players should alert them to the fundamental importance of this new technology.
This is no simple matter, as AI is both familiar and strange. At heart, the algorithms and computation are dedicated to unearthing novel patter..
Tim Evans for HBR This summer marks 50 years since the publication of John Kenneth Galbraith’s The New Industrial State and its quick rise to the top of the New York Times Best Seller list. The book was one of the rare instances where an economist was able to capture public imagination and focus debate on big-picture economic issues. We have only rarely seen its like since — although Thomas Piketty gave it a great go in 2014, with Capital in the Twenty-First Century.
Galbraith’s book is worth revisiting, since its subject is back in the news. Like many people today, he was worried about unchecked corporate power. Yet with the benefit of hindsight, we can see his worries were largely wrong. And therein lies a lesson for economists and policy makers today.
Of course, you would be hard-pressed to find an economist today who has read the book, and you might even find some who have never heard of Galbraith. I’m not one of them. As an undergraduate in Australia, I was exposed to a nonstand..
Many companies begin an internet of things (IoT) journey with great expectations, only to end up with disappointing business results. Gartner recently estimated that through 2018 “80% of IoT implementations will squander transformational opportunities” and fail to monetize IoT data. And a new survey by Cisco found that one-third of all completed IoT projects were not considered a success. In my experience with dozens of organizations implementing IoT solutions, those that achieved their expected ROI changed their traditional business approaches in one or more of the following ways:
They Developed a Partner Ecosystem The essence of IoT is interconnectivity. Interconnectivity is about more than the connections between devices — it is about the connections between customers, partners, and suppliers.
Accordingly, IoT is driving a shift in business structures from a one-company-does-it-all model to a let’s-work-together approach. This means that companies must leave behind traditional mod..
Vincent Tsui for HBR When it comes to creating a more data-and-analytics-driven workforce, many companies make the mistake of conflating analytics training with data adoption. While training is indeed critical, having an adoption plan in place is even more essential.
Any good adoption plan should focus on continual learning. This might include online or recorded refresher sessions; mentors; online resources for questions, feedback, and new ideas; or a certification process. It might even mean rethinking your organization’s structure or core technologies. Based on my experience, here are three ways leaders can shift a company culture from a one-and-done focus on “training” employees in analytics to an “always on” focus on analytics adoption:
Form competency centers. At a high level, a competency center is a collection of domain experts who are given a goal to improve agility, foster innovation, establish best practices, provide training (and mentoring), and be a communications engine...
In addition to the digital tools entering the workplace now, several technologies and trends on the horizon have the potential to further transform the way we work and interact with others.
Artificial intelligence. Artificial intelligence (AI) is already in use throughout the web and increasingly within the enterprise, handling everything from initial call screening for sales prospects to scheduling.
Chatbots are evolving into more complex virtual assistants, interacting with humans to replace phone calls, emails, and texts. Online virtual assistants, such as Amy or Andrew at x.ai, schedule meetings based on calendars and preferences, propose a range of times by email, negotiate with (human) administrative assistants as needed, and send invitations. This type of help has a high return on investment: x.ai estimates that it takes humans an average of 17 minutes to schedule one meeting, while virtual assistants cost less than $100 per month.
Eventually, this will evolve into virtual as..
Many people would agree that scheduling meetings is tedious. Perhaps you have experienced an email chain like this:
Jenn, a potential client: Hey! What day/time works for a quick call next week?
You: (toggling between calendar app and email) I’m wide open Monday.
Jenn: (several hours later) Sorry. Traveling that day. How about Wednesday at 10 AM?
You: (checking your calendar app again) That should work. Your office?
Jenn: My office is great. Maybe we should see if Emad can join?
This back-and-forth can carry on, and it can get even more challenging when people use different calendaring systems or meet across different time zones. Not only are these exchanges time-consuming, they also obliterate our ability to focus on more demanding tasks.
An informal survey confirmed our suspicion that others felt similarly. We asked about 100 information workers, in a wide range of industries and roles, to identify tiresome tasks they regularly do that are not part of their primary work duties. Th..
In the 1980s and 1990s, Blockbuster modernized the movie rental business. It offered far more movies than its smaller rivals, used computers to better manage that inventory, and designed its stores to be bright and family friendly. By 1993, just eight years after its founding, Blockbuster was the global leader in movie rentals, with more than 3,400 stores worldwide.
Then Netflix happened. Blockbuster went bankrupt in 2010.
Economist Luigi Zingales mentions the Blockbuster story in a recent paper as an example of how the economy ought to work. A company has an innovative idea, which for a while provides competitive advantage. Later on, a new innovator comes along and pushes it aside.
But Zingales fears that this isn’t happening as often as it should. Instead, he argues, the U.S. economy may be succumbing to what he calls “the Medici cycle,” named for the powerful family of medieval Florence. Their motto — or at least the motto often attributed to them — was “Money to get power. Power..