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Uber’s AI division is in the news again, but this time it’s a good thing. The company recently announced in a blog post that they have released the latest of their deep learning initiatives to the world.
As the post explains, “Extending our commitment to making deep learning more accessible, we are releasing Ludwig, an open source, deep learning toolbox built on top of TensorFlow that allows users to train and test deep learning models without writing code.”
Photo credit Flickr/Descryptive.com
Turns out, blockchain technology isn’t quite as foolproof as all the hype would have you believe. A new article from MIT Technology Review explains that as blockchain systems become increasingly complicated, the likelihood that they can – and most assuredly will – be hacked goes through the roof.
Does the above video hit just a little too close to home? (You haven’t watched it yet? Sigh. Ok, I’ll wait.)
As I was saying, if watching the clip of what has to be one of the most dysfunctional workplaces imaginable feels like déjà vu for you, first of all I would like to say, “I’m sorry.” And second of all, I would like to share with you that you are absolutely not alone. According to this piece from TED’s The Way We Work series, 60 percent of people worldwide are unhappy at work. Sixty percent. That’s more people than actually live in the United States of America. That’s higher than the percentage of Americans who voted in the last presidential election. That is an obscene amount of people.
A new study published recently in Nature Medicine and covered in Quartz suggests that AI systems may be able to someday take the diagnostic reins from physicians, at least when it comes to the diagnosis of common childhood diseases. The study’s deep-learning system was so successful, in fact, that it outperformed some doctors in correctly identifying a range of conditions. The study, however, (though promising) is not without its limitations.
As anyone familiar with how these models work will tell you, these systems are ultimately only as good as the data upon which they’re trained; and in this instance, the data came entirely from one medical center in China. Sure, it was able to successfully find diagnostic patterns when subsequently put to the test among this very specific community, but can we really assume it would be just as successful in, say, Manhattan (NY, not Kansas), having had no training on this vastly different population? There are certainly models out there – like this one I recently wrote about – that perform quite well in zero-shot environments, but the amount and variety of the data required to make this happen is staggering.
If you’re a self-professed (or otherwise acknowledged) robotics geek (like me), you don’t want to miss this Kickstarter project from Sphero – you know, the company that brought you the take-home version of Star Wars’ BB-8.
Launched just this morning and already up to more than 500 backers for a grand total of almost $135,000 pledged, the Kickstarter project hopes to make the company’s newest robot, RVR, a reality. (I’ve actually had to update those numbers twice, strike that, three times while attempting to post this article.)
If you’re one of the 35 percent of US adults who use Instagram, you may have awoken Wednesday morning to a bit of a shock: Follower counts across the platform had dropped overnight, with some of the more prolific users losing millions. While many at first speculated that this dramatic reduction was due to yet another round of bot purges, Instagram soon confirmed that a bug was the real culprit.
While this story may at first seem trivial – is it really such a huge deal that Selena Gomez’s depleted follower numbers led to Ariana Grande being crowned the new Instagram pop queen? – it does bring a much more important issue back to the forefront, one posed just last September by cybersecurity expert Raj Goel:
As anyone who has used Google Maps’ walking navigation feature in a major city can attest, the app doesn’t always get it right. Relying on GPS technology to guide users from one precise location to another can be a rather tenuous endeavor in an urban environment, where visibility from the ground can be low and GPS signals are often interrupted by tall structures.
“We’re experimenting with a way to solve this problem using a technique we call global localization, which combines Visual Positioning Service (VPS), Street View, and machine learning to more accurately identify position and orientation. Using the smartphone camera as a sensor, this technology enables a more powerful and intuitive way to help people quickly determine which way to go,” the company said Monday on the Google AI Blog.
Photo credit Flickr/rocketace
Software developers are certainly a unique breed. They’re the most inquisitive people you’ll probably ever meet, can learn new technologies seemingly by osmosis, and are fairly likely to have a well-developed theory about the feasibility of warp drive.
Let’s be honest, most tech stories that come out these days are more likely to result in a Xanax subscription than a glowing reaffirmation of mankind’s magnanimity. Devastating security breaches are about as old hat now as dishonest politicians, and too much screen time is, of course, turning our children into illiterate zombies. The apocalypse, it seems, is here.
But something interesting popped up in my news feed this morning that actually gave me a glimmer of hope: Google just launched two new apps that will help the deaf and hard of hearing communicate better in a world that is, at least until now, not really made for them.