iHeartRadio crafts a radio station just for you

When it comes to streaming music, it’s all about personalization these days — so it was only a matter of time until iHeartRadio went down that road. With the service’s new “My Favorites Radio” station, which is launching today, you’ll have a single station built up from all of the tunes you’ve favorite over the years. Much like Spotify’s Discover playlist and Apple Music’s Beats-powered personalization, the new iHeartRadio feature should make it easier to just sit back and enjoy music you already like, as well as explore new musical territory. You’ll be able to fine-tune what the station plays by removing individual tracks, and you can also share it with your friends pretty easily.

For my own personalized station, iHeartRadio successfully combined my love of Janelle Moane, Radiohead, and Arcade Fire, with the occasional bit of Kanye thrown in. What’s particularly interesting about the new feature is that iHeartRadio built it completely in house. Instead of relying on EchoNest, a service that it previously relied on (which was purchased by Spotify last year), the company put together a team of data scientists to make sense of the mountains of listening data its collected over the years.

“We’ve been doing this now for four years, and we have an extraordinary amount of actionable data,” said Owen Grover, iHeartRadio’s senior vice president and general manager. “We felt that the combo of listener’s data and the programming expertise from our leading programmer was really the special sauce for us.”

At this point, My Favorites Radio doesn’t feel much different than other music personalization features, but it’ll be interesting to see where iHeartRadio takes it from here. It’s bringing personalization to an audience that’s likely a bit more mainstream than Spotify and Apple Music’s — iHeartRadio now has over 200 million monthly listeners and 75 million registered users — so it has the potential to change the way plenty of people jam throughout the day.

[Photo credit: Jason Kempin/Getty Images]

Source: iHeartRadio

AI could be the solution to catching tax cheats

The fear of AI usually revolves around the fear of an uprising and humans being attacked by our new robot overlords. Researchers at MIT and non-profit technology source Mitre have a new terrifying future for AI. Well, not that scary to most people, but something that could put a fright in the accountants of tax-cheating corporations. The researchers propose a using artificial intelligence to investigate complex tax shelters that keep companies and the rich from paying their fair share of taxes. It’s like Skynet but with a really awesome calculator and algorithms.

The IRS currently analyzes data from filed returns and looks for patterns from firms that are already under suspicion. It usually takes years to unravel the Gordian knot of accounting that surround dubious partnerships and good old fashioned tax evasion. The researcher’s propose a system that targets partnerships and looks not just at individual returns (which on their own seem legit) but the whole network surrounding those returns that add up to fraud.

Because the system is always looking for signals of nefarious company practices, it wouldn’t need to be focus on an individual source. It could just waits until a series of tax regulations are being used concurrently that usually means someone is exploiting the system for their own gain. And, the system could evolve to detect new ways tax evaders are cheating the government.

In their paper the researchers state: “Our approach is to model the co-evolutionary arms race between transaction sequences in ownership networks with their corresponding audit observables.” Which is a fancy way of saying, it can help the IRS win. Of course it has to convince the same entity that makes you fill out a mountain of forms if you buy a house. So it might be a while before AI starts making sure we’re all paying our fair share.

Source: New York Times

LastPass gets acquired by remote desktop service LogMeIn

The popular password manager LastPass will soon have a new home at LogMeIn, which runs a remote desktop management service, the companies announced today. But don’t fret if you’re an existing LastPass user: LogMeIn says it’ll keep the service and brand alive, while also adding in technology from Meldium, another password service it recently acquired. The news comes amid a busy year for LastPass. Back in June, the company announced that it was hacked, and a few months ago it added free mobile password support. For the most part, the acquisition seems to be about making LogMeIn a more desirable choice for businesses who want to give employees a simple way to secure their many passwords, across a variety of online services.

Via: The Next Web

Source: LogMeIn

The US government won’t force backdoor access, but still wants it

Here’s some good news: the government has decided not to push for a law that would force tech companies to include backdoors in their software. The move means that your encrypted communications from services like WhatsApp and iMessage, will remain unreadable to law enforcement officials. That said, it’s not the win for privacy and freedom that you might hope it to be, since officials are still going to be ringing up CEOs to quell their resistance. The Washington Post quotes one spokesperson saying that the National Security Council is “actively engaged” with these firms to “ensure they understand” the risks that come from encrypted dick pics. This is probably the right time to remind everyone that, when asked, the FBI’s director James Comedy couldn’t name a single investigation that was hindered by encrypted data.

@JimmyChalk @evacide Worst case scenario is silent capitulation from the companies. The Administration is now publicly counting on it.

— Nate Cardozo (@ncardozo) October 9, 2015

The EFF is similarly cynical about the news, describing it as a “partial victory” for privacy campaigners across the land. The organization feels that the government will now spend much more time and effort to pressure companies like Apple and Google to include secret backdoors — from behind closed doors. That’s why it’s throwing its weight behind the Save Crypto movement, which is looking to raise 100,000 signatures on the White House’s online petitions site. The movement is backed by plenty of high-profile names in the tech industry, including the CEA, Mozilla and Twitter. And, if that isn’t enough to sway the administration’s mind, perhaps they should consult with a former director of the NSA — who said only a couple of months ago that adding backdoors would make America more vunlerable to a cyberattack.

[Image Credit: Getty]

Source: EFF, Washington Post, Save Crypto

Lyft partners with Hertz to offer its drivers affordable rental rates

If you’ve been trying to become a driver for Lyft, but your car doesn’t have four door or is too old, the company has a solution. It’s partnered with Hertz car rentals for what it’s calling “affordable” daily, weekly, and monthly rates. In addition to giving new drivers a chance to earn some extra cash, the partnership is also meant to help current drivers whose cars may be in the shop or is otherwise unavailable. The partnership has already launched in Las Vegas and should be rolling out to other cities by the end of the year. At driver event this morning, the ride-sharing platform also announced a partnership with Shell for gas rewards. Drivers get a unique PIN code that offers discounts fuel depending on how often you fill up. The more gas you use, the cheaper your fuel. Power drivers could earn free gasoline with the system. It’s launching in San Francisco, Chicago and Boston and will be available at all Shell stations nationwide by the end of the ear.

Just to keep the driver love going, the company also announced a product for immediate cash out of funds. Express Pay will transfer funds immediately from a driver’s account into their bank account if they have a minimum balance of $50. The new insta-cash feature will launch at the beginning of November.

Source: Lyft

SwiftKey’s latest keyboard is powered by a neural network

A new SwiftKey keyboard hopes to serve you better typing suggestions by utilizing a miniaturized neural network. SwiftKey Neural does away with the company’s tried-and-tested prediction engine in favor of a method that mimics the way the brain processes information. It’s a model that’s typically deployed on a grand scale for things like spam and phishing prevention in Gmail or image recognition, but very recent advancements have seen neural networks creep into phones through Google Translate, which uses one for offline text recognition. According to SwiftKey, this is the first time it’s been used on a phone keyboard.

To grasp how the new system works, we need to understand the old one. SwiftKey currently uses a probability-based language algorithm based on the n-gram model for predictions. There are some additional layers of learning on top of it, which is part of what makes SwiftKey so popular, but the basic implementation reads the last two words in a sentence, looks through a large database, and spits out what it deduces is the most likely word to follow. The two-word limit is a constraint of the n-gram model, and seriously hampers predictions. (Reading back three or four words would be very hard to implement with n-gram, as it would require a far larger database which would in turn be harder for the app to search).

The neural model approaches predictions from a different angle. SwiftKey trained the network with millions of sample sentences, and now each word is represented by a piece of code. This allows the app to better understand sentences in a number of ways. Words that can be used in the same way share similar code. As you’d expect, “Meet” is marked as similar to synonymous words like “met” and “connect.” Less obvious is the link with “speak” or “chat,” which mean something completely different but linguistically will slide into many of the same places. The same goes for days of the week, months, or any other word or concept really — one word can share similar code with thousands of others.

Because the model looks at entire sentences, it’s able to sequence together words as code to find more accurate suggestions. Going back to the “meet” example, let’s take a look at the sentence fragment “Meet you at the.” Using n-gram, SwiftKey typically looked at “at the,” and served you three suggestions: “moment,” “end” and “same.” Using the neural model, it looks as the sentence as a whole and services you “airport,” “hotel” and “office.”

SwiftKey Neural is Android-only and still in alpha, for now. It’s part of the company’s Greenhouse program, which it uses as a launchpad for new ideas that may find their way into the regular app. It’s well worth checking out, but there are, as you’d expect, a few caveats to being on the cutting-edge of keyboard technology.

One of the things that draws users to SwiftKey is its ability to learn your typing style. The regular app can (if you allow it to) scan your emails and social networks for clues, and then monitor your usage of the keyboard itself to improve suggestions. It does this by editing or adding to the language database that the n-gram model uses. Because Neural taps into a different type of database, this personalization isn’t available in the alpha. That doesn’t mean it won’t ever be there — neural networks are a type of machine learning, after all — but for now, it’s not on the to-do list.

“The sooner you can get an idea out of the lab and into the public, the quicker you get feedback and the more useful it becomes,” Joe Braidwood, Chief Marketing Officer at SwiftKey, told Engadget, explaining the reasoning for releasing Neural as a separate app. There’s also the question of resources. Neural is a relatively small 25MB download, but it requires more power than the current SwiftKey, using your phone’s GPU to run the math. Braidwood says it runs with “no perceivable lag” on even modestly-specced smartphones, but there’s likely more optimization to be done before this is ready to replace the regular app.

Caveats aside, SwiftKey’s achievement here is impressive. As mentioned, neural networks are more typically found in giant server farms than on your smartphone, but with two apps released in just a few months, small-scale, focused applications of the tech seem to now be feasible. “We’re pretty sure that the future of mobile typing is going to use neural networks,” Braidwood explained. “Language is such a human thing that if you can build things that think more like humans than computers you’re inevitably going to make a more useful keyboard.”

Source: Google Play