Articles about Machine Learning

Google has announced a significant update to its iOS and Android apps, introducing a new algorithm-driven feed that pushes personalized content at users. The company says that the update makes "it easier than ever to discover, explore and stay connected to what matters to you -- even when you don't have a query in mind."

The feature, known simply as "the feed", has been around since December, but this is an important update that sees Google further leaning on the algorithms it has come to love. The feed draws on machine learning to create a personalized stream of content made up not only of news, but also videos, music and other content Google thinks may be of interest.

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While industry thought leaders are predicting a surge in the use of artificial intelligence (AI) and machine learning this year, much of that usage is still siloed in the hands of large technology enterprises such as Apple, Google, and Facebook. In fact, your smartphone has a lot more AI in it than your local call center operator terminal. In a recent Forrester survey among technology and business professionals, 58 percent responded that their organizations are researching AI technology; however, only 12 percent are now using AI systems at work.

Why the gap between interest and implementation? For many organizations, the bottleneck lies in machine learning platforms that are designed to maximize ease of use and value for data scientists and not day-to-day business users. As a result, predictions, recommendations, and any actionable insights end up siloed in the data and analytics departments or executive reports, denying business users the insights they need to do their jobs more effectively and efficiently. But that has begun to change.

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Emoji offer a great way to spice up your chats, and the Android version of Gboard has been updated to make it easier to find the perfect ones. The update means you can now use the emoji search box to draw the sort of emoji you're looking for, and Google's keyboard will track down what it thinks you mean.

Google uses machine learning to interpret even the most primitive of squiggles, so now there's no need to think about how you would describe a particular emoji in order to perform a text-based search for it -- just draw what you want! But there's more.

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It's not really the time of year for spring cleaning, but Google is turbo-charging the Archive option in Google Photos with the added power of artificial intelligence. Archiving is only a recent addition to Google Photos, making it possible to clear out the clutter from your timeline, and now it has been boosted by AI.

The idea acknowledges the fact that while we might take a photo of something -- such as snapping a poster to save writing down dates and times of an upcoming event -- this isn’t something we necessarily need to see after it has served its purpose.

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More than half, 54 percent, of almost 200 insurance executives recently confirmed that their company was using machine learning for predictive analytical modeling.

They confirmed it to analytics solutions firm Earnix, which used the information to release a report entitled Machine Learning -- Growing, Promising, Challenging.

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Google has updated Gmail with a number of new security features aimed at businesses that require better protection against malware and phishing scams.

The company announced today that it is bringing early phishing detection to its email service by using machine learning along with click-time warnings for malicious links found in emails as well as unintended external reply warnings.

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Users of Google Allo can now use selfies -- and a little AI jiggery-pokery -- to generate a custom set of emoji. Or, as Google puts it, users can now benefit from "Neural Network-Generated Illustrations in Allo."

Working in a similar way to the existing Bitmoji idea, Google's nameless feature will transform a simple selfie into a customizable illustration -- emoji with greater character, more personality. In fact, the system doesn't just create a single emoji, it creates a full sticker pack.

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Anyone involved in writing books or TV and film scripts knows that whilst the entertainment and publishing sectors are constantly on the look out for the next blockbuster, nobody is quite sure what one actually looks like.

A new AI platform called AUTHORS is looking to use machine learning technology to recognize critical insights in original, creative work, to identify its mass audience appeal.

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ARM, the Cambridge-based microprocessor company has just announced a new processor architecture that it promises will give a significant boost to artificial intelligence and machine learning technology.

The new technology, announced this Tuesday, is called DynamIQ and ARM describes it as "probably the biggest micro-architectural shift since ARM announced 64-bit ARMv8-A in 2011." This "monumental shift in multicore microarchitecture" is not the processor itself -- new Cortex-A processors will be built by ARM’s partners, both of which will be announced later this year.

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We’ve been losing the war on cybercrime for some time. Research firm Forrester reports over a billion accounts stolen in 2016 alone, and these data breaches are going up, not down. We are having to wade through more incident data, and people cannot keep up. Could machine learning help solve the problem?

For years, researchers hoped that artificial intelligence would produce human-like machines. Now, they focus on a subset of AI that can solve more realistic and useful challenges. Machine learning cannot do everything a human can, but it doesn’t have to. Instead, we can train it to be good at narrowly-defined tasks -- even better at them than humans, in some cases.

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Any website that allows contributions from visitors -- whether it is a platform such as Twitter or a site that has a comments section -- has to contend with the problem of abuse, swearing and harassment. Manually keeping on top of this sort of content can be a hellish task, but Google and fellow Alphabet subsidiary Jigsaw have launched a new technology called Perspective to help automate things.

The technology uses machine learning to identify what are being called "toxic comments" (defined as "a rude, disrespectful, or unreasonable comment that is likely to make you leave a discussion") so they can be dealt with appropriately.

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Twitter has given its search results a tweak just in time for the New Year. The change sees a move away from displaying tweets in reverse chronological order to showing them in order of relevance instead.

The company recognizes that the site is "live and real-time, so naturally Twitter search must surface recent, yet still relevant, results", so time of posting is still factored in to determine the display order -- it is just no longer the only factor used. With a dash of machine learning thrown in, Twitter thinks it has things sorted.

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In the sci-fi film Ex Machina, reclusive inventor Nathan Bateman foresees a bleak future, telling the movie's protagonist, Caleb, that "One day the AIs are going to look back on us the same way we look at fossil skeletons on the plains of Africa".

When we don’t understand something, we tend to fear it; which is one reason popular movies like Ex Machina and HBO’s nail-biting new series Westworld like to imagine futures in which artificial intelligence plots to destroy humanity.

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With the world so focused on privacy, Evernote should really not have been surprised when there was something of a backlash at an update to its privacy policy that said company employees would be able to access users' unencrypted notes.

Forced to clarify the situation, CEO Chris O'Neill issued an apology for any "confusion" and "angst" the announcement caused, but this was seemingly not enough. Faced with mounting pressure and criticism, the company admits it "messed up" and has now announced that employees will only be able to access notes if users opt-in to allow this. Furthermore, Evernote "will not implement the previously announced Privacy Policy changes that were scheduled to go into effect January 23, 2017".

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There has been great concern over the last day or so following an update to Evernote's Privacy Policy. The update said that Evernote employees might be able to access unencrypted notes as part of a human review of machine learning technologies. Users were unsurprisingly rather concerned, and there was much talk online of a mass exodus to OneNote and other alternatives.

In the face of a user backlash, Evernote CEO Chris O'Neill has issued an apology for any "angst we may have caused" and stressed that "privacy has always been at the heart" of the company. He concedes that the changes to the Privacy Policy were "communicated poorly"... but then managed to half-shift the blame for upset back onto users by saying the change "resulted in some understandable confusion".

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