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Google’s latest hardware innovation: Price

Posted by | Amazon, Apple, apple inc, Assistant, computing, electronics, Gadgets, Google, Google Hardware Event 2018, iOS, iPad, iPhone, Kindle, Microsoft, oled, PIXEL, RAM, Samsung, smartphone, smartphones, Sony, tablet computers, technology, video conferencing | No Comments

With its latest consumer hardware products, Google’s prices are undercutting Apple, Samsung and Amazon. The search giant just unveiled its latest flagship smartphone, tablet and smart home device, all available at prices well below their direct competitors. Where Apple and Samsung are pushing prices of its latest products even higher, Google is seemingly happy to keep prices low, and this is creating a distinct advantage for the company’s products.

Google, like Amazon and nearly Apple, is a services company that happens to sell hardware. It needs to acquire users through multiple verticals, including hardware. Somewhere, deep in the Googleplex, a team of number-crunchers decided it made more sense to make its hardware prices dramatically lower than competitors. If Google is taking a loss on the hardware, it is likely making it back through services.

Amazon does this with Kindle devices. Microsoft and Sony do it with game consoles. This is a proven strategy to increase market share where the revenue generated on the back end recovers the revenue lost on selling hardware with slim or negative margins.

Look at the Pixel 3. The base 64GB model is available for $799, while the base 64GB iPhone XS is $999. Want a bigger screen? The 64GB Pixel 3 XL is $899, and the 64GB iPhone XS Max is $1,099. Regarding the specs, both phones offer OLED displays and amazing cameras. There are likely pros and cons regarding the speed of the SoC, amount of RAM and wireless capabilities. Will consumers care that the screen and camera are so similar? Probably not.

Google also announced the Home Hub today. Like the Echo Show, it’s designed to be the central part of a smart home. It puts Google Assistant on a fixed screen where users can ask it questions and control a smart home. It’s $149. That’s $80 less than the Echo Show, though the Google version lacks video conferencing and a dedicated smart home hub — the Google Home Hub requires extra hardware for some smart home objects. Still, even with fewer features, the Home Hub is compelling because of its drastically lower price. For just a few dollars more than an Echo Show, a buyer could get a Home Hub and two Home Minis.

The Google Pixel Slate is Google’s answer to the iPad Pro. From everything we’ve seen, it appears to lack a lot of the processing power found in Apple’s top tablet. It doesn’t seem as refined or capable of specific tasks. But for view media, creating content and playing games, it feels just fine. It even has a Pixelbook Pen and a great keyboard that shows Google is positioning this against the iPad Pro. And the 12.3-inch Pixel Slate is available for $599, where the 12.9-inch iPad Pro is $799.

The upfront price is just part of the equation. When considering the resale value of these devices, a different conclusion can be reached. Apple products consistently resale for more money than Google products. On Gazelle.com, a company that buys used smartphones, a used iPhone X is worth $425, whereas a used Pixel 2 is $195. A used iPhone 8, a phone that sold for a price closer to the Pixel 2, is worth $240.

In the end, Google likely doesn’t expect to make money off the hardware it sells. It needs users to buy into its services. The best way to do that is to make the ecosystem competitive though perhaps not investing the capital to make it the best. It needs to be just good enough, and that’s how I would describe these devices. Good enough to be competitive on a spec-to-spec basis while available for much less.

more Google Event 2018 coverage

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Computer vision researchers build an AI benchmark app for Android phones

Posted by | AI, Android, Apps, artificial intelligence, Benchmark, Computer Vision, Developer, Europe, Google, hardware, huawei, MediaTek, Mobile, neural network, neural networks, Qualcomm, RAM, Samsung, Samsung Electronics, smartphones | No Comments

A group of computer vision researchers from ETH Zurich want to do their bit to enhance AI development on smartphones. To wit: They’ve created a benchmark system for assessing the performance of several major neural network architectures used for common AI tasks.

They’re hoping it will be useful to other AI researchers but also to chipmakers (by helping them get competitive insights); Android developers (to see how fast their AI models will run on different devices); and, well, to phone nerds — such as by showing whether or not a particular device contains the necessary drivers for AI accelerators. (And, therefore, whether or not they should believe a company’s marketing messages.)

The app, called AI Benchmark, is available for download on Google Play and can run on any device with Android 4.1 or higher — generating a score the researchers describe as a “final verdict” of the device’s AI performance.

AI tasks being assessed by their benchmark system include image classification, face recognition, image deblurring, image super-resolution, photo enhancement or segmentation.

They are even testing some algorithms used in autonomous driving systems, though there’s not really any practical purpose for doing that at this point. Not yet anyway. (Looking down the road, the researchers say it’s not clear what hardware platform will be used for autonomous driving — and they suggest it’s “quite possible” mobile processors will, in future, become fast enough to be used for this task. So they’re at least prepped for that possibility.)

The app also includes visualizations of the algorithms’ output to help users assess the results and get a feel for the current state-of-the-art in various AI fields.

The researchers hope their score will become a universally accepted metric — similar to DxOMark that is used for evaluating camera performance — and all algorithms included in the benchmark are open source. The current ranking of different smartphones and mobile processors is available on the project’s webpage.

The benchmark system and app was around three months in development, says AI researcher and developer Andrey Ignatov.

He explains that the score being displayed reflects two main aspects: The SoC’s speed and available RAM.

“Let’s consider two devices: one with a score of 6000 and one with a score of 200. If some AI algorithm will run on the first device for 5 seconds, then this means that on the second device this will take about 30 times longer, i.e. almost 2.5 minutes. And if we are thinking about applications like face recognition this is not just about the speed, but about the applicability of the approach: Nobody will wait 10 seconds till their phone will be trying to recognize them.

“The same is about memory: The larger is the network/input image — the more RAM is needed to process it. If the phone has a small amount of RAM that is e.g. only enough to enhance 0.3MP photo, then this enhancement will be clearly useless, but if it can do the same job for Full HD images — this opens up much wider possibilities. So, basically the higher score — the more complex algorithms can be used / larger images can be processed / it will take less time to do this.”

Discussing the idea for the benchmark, Ignatov says the lab is “tightly bound” to both research and industry — so “at some point we became curious about what are the limitations of running the recent AI algorithms on smartphones”.

“Since there was no information about this (currently, all AI algorithms are running remotely on the servers, not on your device, except for some built-in apps integrated in phone’s firmware), we decided to develop our own tool that will clearly show the performance and capabilities of each device,” he adds. 

“We can say that we are quite satisfied with the obtained results — despite all current problems, the industry is clearly moving towards using AI on smartphones, and we also hope that our efforts will help to accelerate this movement and give some useful information for other members participating in this development.”

After building the benchmarking system and collating scores on a bunch of Android devices, Ignatov sums up the current situation of AI on smartphones as “both interesting and absurd”.

For example, the team found that devices running Qualcomm chips weren’t the clear winners they’d imagined — i.e. based on the company’s promotional materials about Snapdragon’s 845 AI capabilities and 8x performance acceleration.

“It turned out that this acceleration is available only for ‘quantized’ networks that currently cannot be deployed on the phones, thus for ‘normal’ networks you won’t get any acceleration at all,” he says. “The saddest thing is that actually they can theoretically provide acceleration for the latter networks too, but they just haven’t implemented the appropriated drivers yet, and the only possible way to get this acceleration now is to use Snapdragon’s proprietary SDK available for their own processors only. As a result — if you are developing an app that is using AI, you won’t get any acceleration on Snapdragon’s SoCs, unless you are developing it for their processors only.”

Whereas the researchers found that Huawei’s Kirin’s 970 CPU — which is technically even slower than Snapdragon 636 — offered a surprisingly strong performance.

“Their integrated NPU gives almost 10x acceleration for Neural Networks, and thus even the most powerful phone CPUs and GPUs can’t compete with it,” says Ignatov. “Additionally, Huawei P20/P20 Pro are the only smartphones on the market running Android 8.1 that are currently providing AI acceleration, all other phones will get this support only in Android 9 or later.”

It’s not all great news for Huawei phone owners, though, as Ignatov says the NPU doesn’t provide acceleration for ‘quantized’ networks (though he notes the company has promised to add this support by the end of this year); and also it uses its own RAM — which is “quite limited” in size, and therefore you “can’t process large images with it”…

“We would say that if they solve these two issues — most likely nobody will be able to compete with them within the following year(s),” he suggests, though he also emphasizes that this assessment only refers to the one SoC, noting that Huawei’s processors don’t have the NPU module.

For Samsung processors, the researchers flag up that all the company’s devices are still running Android 8.0 but AI acceleration is only available starting from Android 8.1 and above. Natch.

They also found CPU performance could “vary quite significantly” — up to 50% on the same Samsung device — because of throttling and power optimization logic. Which would then have a knock on impact on AI performance.

For Mediatek, the researchers found the chipmaker is providing acceleration for both ‘quantized’ and ‘normal’ networks — which means it can reach the performance of “top CPUs”.

But, on the flip side, Ignatov calls out the company’s slogan — that it’s “Leading the Edge-AI Technology Revolution” — dubbing it “nothing more than their dream”, and adding: “Even the aforementioned Samsung’s latest Exynos CPU can slightly outperform it without using any acceleration at all, not to mention Huawei with its Kirin’s 970 NPU.”

“In summary: Snapdragon — can theoretically provide good results, but are lacking the drivers; Huawei — quite outstanding results now and most probably in the nearest future; Samsung — no acceleration support now (most likely this will change soon since they are now developing their own AI Chip), but powerful CPUs; Mediatek — good results for mid-range devices, but definitely no breakthrough.”

It’s also worth noting that some of the results were obtained on prototype samples, rather than shipped smartphones, so haven’t yet been included in the benchmark table on the team’s website.

“We will wait till the devices with final firmware will come to the market since some changes might still be introduced,” he adds.

For more on the pros and cons of AI-powered smartphone features check out our article from earlier this year.

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Xiaomi goes after global markets with two new Android One phones

Posted by | Android, Android One, Asia, China, computing, Europe, France, hutchison, india, Italy, Mexico, Mobile, RAM, smartphone, smartphones, spain, TC, technology, Xiaomi | No Comments

Xiaomi gave Google’s well-intentioned but somewhat-stalled Android One project a major boost last year when it unveiled its first device under the program, Mi A1. That’s now joined by not one but two sequel devices, after the Chinese phone maker unveiled the Mi A2 and Mi A2 Lite at an event in Spain today.

Xiaomi in Spain? Yes, that’s right. International growth is a major part of the Xiaomi story now that it is a listed business, and Spain is one of a handful of countries in Europe where Xiaomi is aiming to make its mark. These two new A2 handsets are an early push and they’ll be available in over 40 countries, including Spain, France, Italy and 11 other European markets.

Both phones run on Android One — so none of Xiaomi’s iOS-inspired MIUI Android fork — and charge via type-C USB. The 5.99-inch A2 is the more premium option, sporting a Snapdragon 660 processor and 4GB or 6GB RAM with 32GB, 64GB or 128GB in storage. There’s a 20-megapixel front camera and dual 20-megapixel and 16-megapixel cameras on the rear. On-device storage ranges between 32GB, 64GB and 128GB.

The Mi A2 Lite is the more budget option that’s powered by a lesser Snapdragon 625 processor with 3GB or 4GB RAM, and 32GB or 64GB storage options. It comes with a smaller 5.84-inch display, there’s a 12- and 5-megapixel camera array on the reverse and a front-facing five-megapixel camera.

The A2 is priced from €249 to €279 ($291-$327) based on specs. The A2 Lite will sell for €179 or €229 ($210 or $268), against based on RAM and storage selection.

The 40 market availability mirrors the A1 launch last year, but on this occasion, Xiaomi has been busy preparing the ground in a number of countries, particularly in Europe. It has been in Spain for the past year, but it also launched local operations in France and Italy in May and tied up with CK Hutchison to sell phones in other parts of the continent via its 3 telecom business. While it isn’t operational in the U.S., Xiaomi has expanded into Mexico and it has set up partnerships with local retailers in dozens of other countries.

Xiaomi has been successful with its move into India, where it one of the top smartphone sellers, but it has not yet replicated that elsewhere outside of China so far.

China is, as you’d expect, the primary revenue market but Xiaomi is increasingly less dependent on its homeland. For 2017 sales, China represented 72 percent, but it had been 94 percent and 87 percent, respectively, in 2015 and 2016.

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Now They’ve Gone And Stuck Android Onto A Graphing Calculator

Posted by | Android, Gadgets, RAM, TC, texas instruments, wi-fi | No Comments

nexus2cee_CIAONytUEAAMPnl_thumb Today in our ongoing series of people putting one thing into another thing, we present Android running on a Texas Instruments TI-Nspire CX, a robust graphing calculator popular with the pre-calc set. The calculator has about 100MB of storage and 64MB of RAM but has enough power to run Android 1.6 aka Donut. Obviously you’re not going to make very many calls using your graphing calculator… Read More

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