Two new Pixel phones and a competitor to Amazon's Echo Dot are among the products expected to be unveiled today at an event held by Google. The Pixel 2 and Pixel 2 XL phones will be iterations of the first Pixel phones released a year ago, according to leaks, while the Google Home Mini smart speaker is expected to be similar to Amazon's shrunk-down Echo Dot smart speaker, squeezing the voice-control features into a smaller package but requiring a separate speaker for high-quality music playback. It appears the phones are part of the company doubling down its efforts to compete directly with Apple in smartphone hardware. Additionally, they will continue to provide Google the opportunity to demonstrate the extent of its software prowess when freed from the requirement to work closely with other Android device manufacturers. These are the Google Pixel 2 and Pixel 2 XL https://t.co/cXCs560jNH

Makes me feel sad for the rest. Actually, that's a movie ("The Spy that Loved Me") that Netflix recommends for me since I'm a James Bond junkie and Netflix knows that. In fact, Netflix knows a lot about me as it knows a lot about all of its viewers, which is one reason why Netflix is a Wall Street darling and has rewarded its stockholders very well over the past couple of years (see Figure 1). But Netflix isn't doing anything that other organizations cannot do. To replicate Netflix's business success starts with thinking differently about the role of data and analytics in powering the organization's business.

David Fletcher was born in England in 1952. On leaving school he studied production engineering for five years then jumped on an aircraft bound for New Zealand where he's lived ever since. He was employed as an illustrator and cartoonist by New Zealand's largest daily newspaper, the New Zealand Herald, for three years, but for the last thirty years he's been pretending to work from home as a comic strip artist. He draws two daily strips called The Politician and Crumb the Blackbird, also several weekly strips. His cartoons are syndicated to Europe, Britain, US, Africa, Australia and New Zealand.

We know what Star Wars fans will be wishing for this Christmas -- aside from Sphero's R2-D2 and BB-9E toys. Ubtech, the company behind the dancing Lynx robot, is releasing a Stormtrooper bot. Although it can't teach you yoga, you can use voice commands to instruct it to ward off intruders (hopefully not with an actual blaster). Its facial recognition tech also allows it to store up to three faces in its memory bank. That way, it can shout at any uninvited guests that keep barging into your room. And, its accompanying mobile app packs an augmented reality game that lets you fight off the Resistance and launch First Order attacks.

I'm working with some friends on an idea for email classification and we're wondering what would be the best way to approach the problem. Essentially we're looking to create an application/Outlook extension that would classify emails into various categories like "Important/Not Important" or "Project email, Contract talks, Trash", we're not totally sure on categories at the moment, if it could be user defined it would be more useful I guess. How could one approach such a problem, is text-mining the right approach or should be we looking into AI/Machine Learning techniques or a combination of the two? I read a bit about Bayesian Probabilities and how using previous results sets you get a matrix table of probabilities and that's used to determine where new data would be categories. Is this the best approach or are there alternatives we should be looking at?

What are the state-of-the-art object detection and/or recognition architectures/papers? I found "Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks" very interesting, and I want to use the same idea on a very specific image domain. Once the objects are reliably detected, i plan to apply some sort of "information bottleneck" auto-encoder-style architecture for the task of image compression/decompression. Maybe even add adversarial training to get "sharper" reconstructions. Do you know some recent literature on this topic?

We're hurtling toward the holiday shopping season, which means companies are putting the finishing touches on their gadgets and getting them ready for the impending crush of consumerism. This week, we met a bundle of new Alexa-based products from Amazon, and Spotify sent everyone on your friends list into a full-on nostalgia bender. Here's what you might have missed last week. Amazon gave the Echo smart speaker lineup a near-total refresh last week. Taking the place of the old $179 Echo are two new devices: an adorably small $99 Echo speaker, and a $150 Echo Plus--which has bigger speakers and more advanced smart home controls.

With its cannon and claw accessories, last year's Mambo drone from Parrot was more a toy than a photography tool. The latest version of the mini drone looks to be at least more fun, if not more useful, than its predecessor. The Mambo FPV comes with a camera attachment and a headset, so you can stream what the tiny flyer is seeing right into your eyes. Last year's Mambo came with a cannon that shoots six pellets up to six feet and a "Grabber" claw that picks up very small objects weighing up to four ounces. The new version isn't physically different -- it just comes with different accessories (the older ones are also compatible). Parrot increased the wireless range between the Bluetooth controller and the drone so you can now fly it up to 100 meters (330 feet) away, up from 60 meters before.

Artificial Intelligence (AI) is being used more and more in devices including virtual assistants such as Siri and Alexa.

Sibyl harnesses artificial intelligence that is capable of learning when to schedule individual patients in order to increase utilization.