Articles about Machine Learning

If you are like me, there is a good chance that you are confused as well about the most recent terminology to use in the field of data science … pardon, artificial intelligence … no, I mean data science. No, I mean artificial intelligence. Please, somebody tell me what I should call it and what the difference is!

Isn’t artificial intelligence just a new cool name to label the old traditional data science? Don't both concepts cover the same algorithms? And isn’t it all machine learning anyway? This is what I used to think until I took a pause to write this post. During this breather, I went back in time and tried to remember all the names that used to be used to label this field of what essentially is data analytics. Let’s see …

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Netflix has millions of users around the world, but how many of these are actually paying customers? Many of us either know (or are) people who share their Netflix account with friends and family, or leech off the one person they know that's willing to pay for a subscription.

But Netflix free rides could be coming to an end. At CES, UK-based firm Synamedia revealed artificial intelligence software that could be used by Netflix and other companies to detect and block the sharing of account credentials.

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There are a lot of benefits to be gained from artificial intelligence, but its use also raises concerns over the impact it is likely to have on jobs, privacy and more.

Enterprise AI specialist noodle.ai has produced an infographic looking at the positive and negative impacts of the technology.

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When you're taking a flight, you can check the arrivals and departures section of your airport website to see if you're going to take off on time, or just rely on an airline announcement. Or you could just ask Google Assistant.

Google has announced that it will start to predict flight delays, using a combination of historic flight information and machine learning. The company says that it is able to deliver predictions with 85 percent confidence.

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Increasing numbers of organizations are interested in the opportunities offered by machine learning, but their efforts are often hindered by a lack of data science talent.

California-based SnapLogic is launching a new self-service solution to help break down the barriers to implementing machine learning.

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Almost any article you read about how automation will affect our future can be classified into one of two narratives. The first one is that it will definitely lead to a better future, as it always had since the industrial revolution. Of course, some people will lose their jobs, but as history shows, new jobs will be created. And not just new jobs, but better jobs. The other narrative is that this time is different. The robots are becoming more and more intelligent and capable. And the number of jobs and industries they’ll destroy will far exceed the number of jobs they create. Of course, it’s impossible to tell which of the two narratives will become a reality. What we can tell is that these narratives share similar inception: more and more parts of our jobs and lives are being automated.

Take for example the process of driving. For many years now, we have been taking small parts of the driving process and automating them. For a better driving experience, we built cruise control. For route planning, we developed the GPS. Now, we are able to tackle more complex problems like lane merging and emergency braking. In the next couple of years, we will most certainly have fully autonomous cars driving on the roads. Just last week Waymo, Alphabet’s self-driving subsidiary, officially received the very first California permit to test their vehicles in the state without a human behind the wheel.

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One of the problems that businesses can have protecting sensitive data is the task of actually locating it in the first place.

Data protection specialist TITUS is launching a new Intelligent Protection solution that offers businesses a model based on their specific data protection needs while using machine learning to provide additional consistency and accuracy to data protection initiatives.

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IT operations is an area that often involves analyzing and reacting to a series of events and that makes it a strong candidate for automation.

Operations platform specialist OpsRamp has recognized this with the launch of OpsQ, an intelligent event management, alert correlation, and remediation solution for hybrid enterprises.

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Data science and machine learning professionals within larger organizations are feeling significantly more satisfied with their progress than those in smaller organizations, according to a new study.

The report from machine learning specialist Algorithmia shows that those in organizations with 2,500+ employees are 80 percent more likely to be 'satisfied' or 'very satisfied' with their progress as compared to professionals in companies of 500 employees or less.

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Access to up to date information is essential for businesses, but as data proliferates it's too often the case that people spend time searching for the information they need to do their jobs.

Employee experience portal Sapho is integrating machine learning into its product so that metrics that are typically hard to access, due to complex applications or time-consuming dashboards, will now be delivered directly to employees without needing them to conduct an information search.

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Traditional signature-based security solutions find it hard to keep up with the fast pace of malware development, so security companies are turning to other solutions.

FireEye is launching a new version of its Endpoint Security product with the addition of a machine learning engine called MalwareGuard.

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Microsoft has just released Microsoft released Windows 10 Redstone 5 Build 17723 and Redstone 6 (19H1) Build 18204 and one of the new features is a new system that avoids restarts at awkward times following the installation of an update.

This sounds great, and Microsoft says that people have complained about this very scenario. But is an artificial intelligence or machine learning powered system really what's needed? How about just leaving users in charge to choose when their computer restarts. There you go, Microsoft; I fixed that for you.

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Seeking to strengthen its artificial intelligence arsenal, Microsoft has announced an agreement to acquire San Francisco-based AI startup Bonsai.

Bonsai already had Microsoft links, having been set up back in 2014 by two former Microsoft engineers, Mark Hammond and Keen Browne. The company specializes in "deep reinforcement learning" which can be used to teach autonomous systems within simulations, and the company sees this tying in with Azure.

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As recently noted by AdDuplex, the Windows 10 1803 rollout is progressing much more smoothly than all previous feature updates. AdDuplex’s figures suggest over 50 percent of Windows 10 users have already been offered the update, while Microsoft’s own numbers say 250 million machines have it. With close to 700 million Windows 10 systems, that’s just over 35 percent.

It’s certainly been a huge improvement over the famously slow and problematic Creators Update last year, and part of the reason this rollout has been so successful is down to Microsoft’s use of AI and Machine Learning.

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AI is, of course, one of the latest big buzzwords in the tech industry, but here’s something new: Norman, the world’s first "psychopathic" artificial intelligence, as concocted by researchers at MIT.

So, you might wonder, how do you make a psychopath in the world of machine learning? Simple -- you pack the AI in question off for a vacation on Reddit. Or the "darkest corners" of Reddit, as the MIT researchers put it.

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