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Tuesday, November 21, 2017

OnePlus 5T review: polished to a T - The Verge

"OnePlus is one of those beguiling companies that seem to promise impossibly wonderful things. Flagship products at budget prices. The assiduous elegance of an iPhone at the attainable cost of a midrange Motorola. It’s a company that constantly flirts with the “too good to be true” label, sometimes delivering on its lofty claims and at other times failing to live up to its own hype.

I like the new OnePlus 5T for many of the same reasons that I like OnePlus itself. This device is full of all the right ideas — hardware design, software responsiveness, and overall usability — and if I were tasked with the job of assembling a phone, my specification would read a lot like the OnePlus 5T does on paper. In practice, this phone isn’t the total fulfillment of every objective that OnePlus set for itself, nor every promise the company has made. But it’s damn close. It takes the imperfect OnePlus 5 from five months ago and fixes much of what ailed it. This is the most refined OnePlus phone yet...."

OnePlus 5T review: polished to a T - The Verge

FCC's Pai moves to eliminate net neutrality regulations - CNET - This is a direct attack on the open internet and a gift to large telecommunication companies like Xfinity, Verizon and Time Warner



"The Federal Communications Commission is planning a full repeal of Obama-era net neutrality rules, handing the broadband and wireless industries a big victory in the war against government oversight of the internet.

On Tuesday, FCC Chairman Ajit Pai issued his proposal for dismantling the 2015 net neutrality regulations, which ensure all traffic on the internet is treated equally, and prevent broadband and wireless providers from blocking or slowing online content. Pai has also eliminated the legal foundation that gives the FCC oversight over internet services providers.

The federal government will stop 'micromanaging the internet' under the proposal, Pai said in a statement. Instead, broadband providers will be required to be 'transparent' about how they manage their networks to allow consumers and businesses to buy the service they need."

(Via.) FCC's Pai moves to eliminate net neutrality regulations - CNET:

OnePlus 5T Review: Get this one!

Pixel 2 XL - New Update Screen Comparison

Saturday, November 18, 2017

Microsoft Surface Book 2 Review

The Surface Beast: Microsoft's Surface Book 2 is a MacBook Pro Killer

"Over the last year I have been slowly migrating from Apple to Windows, and to be honest breaking out of the walled gardens that I lived within (some known, some unknown) has not been easy, but it has been freeing. I have to hand it to Apple, they made a system, an environment, that has been comfortable and creatively useful for many years. However, slowly the sparkle that was once held in such high regards by artists, has begun to dull.

For me, there was one piece of hardware that remained from my Apple past, one that traveled with me to all my photo shoots and pre-production meetings, coffee shops and airport bars, studios and locations alike… my MacBook Pro.

When I began transitioning to Windows, I had made concessions. I thought at the time, that one of the few pieces of Apple hardware that would stay in my repertoire was the MBP. I had even decided to upgrade it to the newest one before the announcement, for I knew it would be cutting edge in the ways that other Apple products of the past had been. Then, to the horror of myself and many around, we watched as Apple gave us the new MacBook Pro, complete with… wait for it… the Touch Bar (ready to suit all of my emoji needs).

That very day I bought a Microsoft Surface Book (the very one that I am typing this blog on) and never looked back. To be honest, I had intended to write a review of it for quite some time, however, that blog had been put on the backburner. What was striking about the original Surface Book was something I had a very hard time quantifying. While there were many things I fell in love with on it, such as the keyboard, and the detachable screen, the thing that won me over more than anything was how much it just worked...

The Surface Beast: Microsoft's Surface Book 2 is a MacBook Pro Killer

Thursday, November 09, 2017

Democracy Needs a Reboot for the Age of Artificial Intelligence | The Nation

Robot to Human

"One of my favorite things about the tech industry is how quickly innovations from the big companies and premium products trickle down into more affordable devices. The rampant stealing of ideas isn't so awesome when it happens between small companies — or, as in the case of Facebook treating Snapchat like its incubation lab, when a big company copies a smaller one. But I don’t have a problem with the general flow of good ideas from giants like Apple and Google to more budget-friendly suppliers of hardware and software. Apple and Google, though, have an obvious problem with that, and they’ve worked hard to develop new techniques and approaches that can’t be readily imitated.

The big new thing in smartphones lately is one of those buzz phrases you’ll have heard tossed around: machine learning (ML). Like augmented and virtual reality, machine learning is often thought of as a distant promise, however in 2017 it has materialized in major ways. ML is at the heart of what makes this year’s iPhone X from Apple and Pixel 2 / XL from Google unique. It is the driver of differentiation both today and tomorrow; and the companies that fall behind in it will find themselves desperately out of contention.

A machine-learning advantage can’t be easily replicated, cloned, or reverse-engineered: to compete with the likes of Apple and Google at this game, you need to have as much computing power and user data as they do (which you probably lack) and as much time as they’ve invested (which you probably don’t have). In simple terms, ML promises to be the holy grail for giant tech companies that want to scale peaks that smaller rivals can’t reach. It capitalizes on vast resources and user bases, and it keeps getting better with time, so competitors have to keep moving just to stay within reach.

I’m not arguing that ML is a panacea any more than I would argue that all OLED displays are awesome (some are terrible): it’s just the basis on which some of the key differentiating features are now being built.

Google’s HDR+ camera
Let’s start with the most impressive expression of machine-learning consumer tech to date: the camera on Google’s Pixel and Pixel 2 phones. Its DSLR-like performance never ceases to amaze me, especially in low-light conditions. Google’s imaging software has transcended the traditional physical limitations of mobile cameras (namely: shortage of physical space for large sensors and lenses), and it’s done so through a combination of clever algorithms and machine learning. As Google likes to put it, the company has turned a light problem into a data problem, and few companies are as adept at processing data as Google.

I spoke with Marc Levoy, the Stanford academic that leads Google’s computational photography team, recently, and he stressed something important about Google’s ML-assisted camera: it keeps getting better over time. Even if Google had done nothing whatsoever to improve the Pixel camera in the time between the Pixel and Pixel 2’s launch, the simple accumulation of machine learning time will have made the camera better. Time is the added dimension that makes machine learning even more exciting. The more resources you can throw at your ML setup, says Levoy, the better its output becomes, and time and processing power (both on the device itself and in Google’s vast server farms) are crucial.


Google’s Assistant
At CES in January this year, Huawei’s mobile boss Richard Yu was asked if his company would introduce its own voice assistant in the US, to which he replied, “Alexa and Google Assistant are better, how can we compete?” That uncharacteristically pragmatic response (for a mobile company CEO) neatly encapsulates the difficulty of copying Google and Amazon’s machine-learning efforts. All the vast resources that the two US companies have invested into natural language processing and voice recognition are returning a dividend in keeping them far enough ahead of the competition that even Huawei, one of the biggest consumer tech brands outside the US, isn’t trying to compete. That’s the cumulative power of long-term investment in machine learning.

Is Google Assistant a differentiating feature? Not for hardware, as Google wants to have Assistant running on every device possible. But the Assistant serves as a conduit for funneling users into Google search and the rest of the company’s services, with practically all of them benefiting from some variety of machine learning, whether you’re thinking of Google Maps tips or YouTube video suggestions. What Assistant does for the mobile market is to enhance Google’s influence over its hardware partners: woe betide the manufacturer that tries to ship an Android phone in 2018 without either the Google Play Store or Assistant on board.

Apple’s Face ID
On the Apple side of the fence, machine learning is permeating much of the software running on the iPhone already, and the company’s Core ML tools are making it easy for developers to add to that library. But the big highlight feature of the new iPhone X, the thing everyone notices, is the notch at the top of its display and the technology contained within it. Up in that monobrow section, you’ll find a full array of infrared and light sensors, something tantamount to a Microsoft Kinect system, which facilitates the new FaceID authentication method.

I remain uncertain about how well Face ID strikes the balance between security and convenience (especially without the fallback of Touch ID’s fingerprint recognition), but I have no doubt about the technical achievement that it represents. Everyone I know that has used Face ID gives a glowing assessment of its accuracy. The system is robust enough to work in the dark and, thanks to machine learning, it will adapt to changes in your appearance. If you strip away all the usual incremental upgrades and design tweaks, the FaceI D system is the iPhone X’s defining new feature. And it’s reliant on ML to work its technological magic..."

Democracy Needs a Reboot for the Age of Artificial Intelligence | The Nation