Machine Learning: Lessons From 5 Forward-Thinking Companies

Machine Learning: Lessons From 5 Forward-Thinking Companies

Machine Learning: Lessons From 5 Forward-Thinking Companies

From self-driving cars to online retailers that remember – and respond to – your every keystroke, machine learning is deeply embedded in today’s consumer landscape.

In fact, smart technologies, tools and appliances are popping up everywhere, making artificial intelligence (AI) – once a futuristic concept – a dynamic and evolving reality in our daily lives.

While the fraud fighting potential of AI applications, such as machine learning, has been splashed across industry headlines, the technology can do so much more.

Here are five fascinating ways machine learning is transforming our lives.

#1 – Facebook Gets a Facelift

According to, Facebook literally wrote the book on machine learning: “The next time you load Facebook . . . consider the computing muscle it takes to load the personal updates, news stories and family photos you see on your screen. Now multiply that by one billion users. Now do it every single day.”

What Facebook accomplishes day-in and day-out – thanks to machine learning – is nothing short of magical. And it is getting even better.

Since so much of Facebook’s appeal comes from the personal photos posted, the company recently implemented new and improved facial recognition software.

With this enhancement, the system has become so intelligent, and so precise, it can recognize faces that haven’t even been tagged or captioned yet, based on volumes of data in its systems.

“Just two years ago, computers were terrible at identifying pictures,”’s Geoff Colvin reports. “And I recall speaking with mainstream experts who believed it would be many years before computers would be as good as humans, if they could ever be that good.”

#2Carnival Cruise Line: Why Smarter Vacations Are More Fun

ZDNet reports Carnival Cruise Line is getting on board with machine learning as well. At CES 2017, the cruise line announced the introduction of a new machine-learning-driven service called OCEAN (One Cruise Experience Access Network), designed to personalize the cruising experience for guests.

The new system will enable cruise staffers – as well as a “digital concierge” – to anticipate every whim and preference of guests as they travel from port to port, based on their previous selections in dining, shopping and entertainment options. In advance of the cruise, guests will also receive their very own OCEAN Medallion, a wearable they can use anywhere on the ship to have their needs and wishes fulfilled at a moment’s notice.

#3 – Amazon AI: It’s More Than a Bot – It’s a Friend

Amazon has always been on the forefront of machine learning, and now outside developers have even greater access to its deep technological resources. Amazon AI, announced at the company’s AWS re:Invent developer event last fall, is giving external developers three intriguing new tools for their next generation of applications.

The first, called Rekognition, leverages data to identify objects and scenes with uncanny detail. For example, it can know the pet in view is not only a dog, but it’s also a golden retriever.

The second tool, Amazon Polly, is a highly sophisticated text-to-speech service that, according to, speaks in 24 languages and 47 voices, both male and female. Polly is so well versed in the languages she speaks, she knows, for example, the correct pronunciation of words like “live” in different contexts (as in “I live in Chicago” versus “Live from New York”).

Amazon’s third new developer tool – which also happens to power its famous Alexa bot – is Amazon Lex. This tool takes the Alexa concept one step further by enabling engaging, multi-step conversations. As Amazon told developers in its announcement, Lex-based bots can “provide information, power your applications, streamline work activities or provide a control mechanism for robots, drones or toys.”

They can even book your next flight.

#4 – Uber and Data: Why Your Pizza Always Arrives Piping Hot

For Uber, delivering lunch on time to your doorstep – or conference table – involves more than an understanding of weather and traffic. The company uses machine learning algorithms to calculate a myriad of relevant data points, from the time it takes to cook noodles or make a hamburger to how long it will take to transport the meal to different parts of town at different times of day.

According to a interview with Uber’s head of machine learning, Danny Lange, when the company estimates the time it will take for a driver to pick you up, its objective is to be right every single time – down to the minute.  “We gather information from millions of trips,” he said. “What is really unique to machine learning is some of the speed by which you can analyze and improve your accuracy. Every time you finish a trip, right there we get a report.”

#5 – Taking the Guesswork Out of Remodeling at Lowes

Anyone who has ever remodeled a kitchen or bathroom understands the dilemma: That flooring or countertop you picked out in the showroom just doesn’t look the same now that it is installed in your home. Well, thanks to Lowes’ new machine learning and augmented reality (AR) design service, those days may soon be over.

Available in just a handful of Lowes locations now, the service allows would-be remodelers to don an AR headset and view a potential future kitchen in the form of a hologram. The technology uses a mixed reality experience based on Microsoft’s HoloLens AR technology.

A recent article in USA Today explains how the solution leverages data by matching favorite design elements from the shopper’s Pinterest account with similar materials, appliances and other products that Lowes actually carries. “Virtual kitchens” can be redesigned by the viewer using gestures, for the perfect outcome every time.

Microsoft Data Group Vice President Joseph Sirosh told USA Today, “We’re aiming to create a new generation of customer experiences driven by intelligent data and machine learning. Making decisions can be time consuming and stressful. Our job is to continue to learn and help companies improve the consumer experience.”

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