Tag Archive | "Google"

How Google is powering the world’s AI

After helping to define the modern internet era with Search and Android, Google is already at the forefront of the next wave in computing research and development: AI. Many consider artificial intelligence and neural network computers to be the next step in computing, enabling new use cases and faster computation to solve currently unsolvable problems. The search giant, which now calls itself an “AI first” company, has been leading adoption of these new technologies in a number of ways.

Neural networking algorithms and machine learning are already at the heart of many of Google’s services. They filter out spam in Gmail, optimize targeted advertising, and analyze your voice when you talk to Google Assistant or your Home speaker. Inside smartphones, ideas like Google Lens and Samsung’s Bixby are showing the power of “AI” vision processing. Even companies like Spotify and Netflix are using Google’s Cloud servers to tailor content to their users.

Google’s Cloud Platform is at the center of its efforts (and those of third parties) to utilize this increasingly popular area of computing. However, this new field requires new kinds of hardware to run efficiently, and Google has invested heavily in its own processing hardware, which it calls a cloud tensor processing unit (Cloud TPU). This custom hardware is packed into Google’s servers and already powers the current and expanding AI ecosystem. But how does it work?

TPUs vs CPUs – searching for better efficiency

Google unveiled its second-generation TPU at Google I/O earlier this year, offering increased performance and better scaling for larger clusters. The TPU is an application specific integrated circuit. It’s custom silicon designed very specifically for a particular use case, rather than a general processing unit like a CPU. The unit is designed to handle common machine learning and neural networking calculations for training and inference; specifically matrix multiply, dot product, and quantization transforms, which are usually just 8 bits in accuracy.

While these kinds of calculations can be done on a CPU and sometimes even more efficiently on a GPU, these architectures are limited in terms of performance and energy efficiency when scaling across operation types. For example, IEEE 754 8-bit integer multiplication optimized designs can be up to 5.5X more energy and 6X more area efficient than 16-bit floating-point optimized designs. They’re also 18.5X more efficient in terms of energy and 27X smaller in terms of area than 32-bit FP multiply. IEEE 754 being the technical standard for floating point computations used in all modern CPUs.

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Furthermore, many neural networking use cases require low latency and almost instantaneous processing times from a user perspective. This favors dedicated hardware for certain tasks, as opposed to trying to fit typically higher latency graphics architectures to new use cases. Memory latency accessing external RAM can be hugely costly too.

In large data centers, power and silicon hungry processors quickly rack up costs. Google’s TPU is designed in equal parts for efficiency as well as performance.

In large data centers, the power and area inefficiencies when performing neural networking functions on a CPU or GPU could result in huge costs. Not just in terms of silicon and equipment, but also the energy bill over long periods of time. Google knew that if machine learning was ever to take off in a meaningful way, it needed hardware that could offer not only high performance, but also substantially better energy efficiency than leading CPUs and GPUs could offer.

To solve this problem, Google set about designing its TPU to offer a tenfold cost-performance improvement over an off-the-shelf GPU. The final design was a co-processor that could be attached to the common PCIe bus, allowing it to work alongside a regular CPU, which would pass it instructions and handle traffic, among other things, as well as help speed up deployment times by making the design an add-on. As a result, the design was up and running in data centers just 15 months after conception.

TPU deep dive

Earlier in the year, Google released a comprehensive comparison of its TPU’s performance and efficiencies compared with Haswell CPUs and Nvidia Tesla K80 GPUs, giving us a closer look at the processor’s design.

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At the heart of Google’s TPU is a Matrix Multiply Unit. The unit contains 65,538 8-bit multiplier accumulators (MACs)— hardware units designed specifically to calculate the product of two numbers and add that to an accumulator. When done with floating point numbers, this is called a fused multiply-add (FMA). You may recall that this is an instruction that ARM has made efforts to optimize with its latest Cortex-A75 and A55 CPUs, as well as Mali-G72 GPU.

Unlike a CPU or GPU, which accesses multiple registers per operation when sending data to and from their arithmetic logic units (ALUs), this MAC implements a systolic design that reads a register once and reuses that value throughout a prolonged calculation. This is possible in the TPU because of its simplified design that sees the ALUs perform multiplication and addition in fixed patterns across adjoining ALUs, without needing any memory access. This limits the design in terms of possible functions, but greatly increases its performance and power efficiency at these fused-multiply tasks.

In terms of numbers, Google’s TPU can process 65,536 multiply-and-adds for 8-bit integers every cycle. Given that the TPU runs at 700MHz, it can compute 65,536 × 700,000,000 = 46 × 1012 multiply-and-add operations or 92 TeraOps (trillions of operations) per second in the matrix unit. Google says that its second generation TPU can deliver up to 180 teraflops of floating point performance. That’s significantly more parallel throughput than your typical scalar RISC processor, which usually only passes a single operation with each instruction over a clock cycle or more.

The 16-bit products of the Matrix Multiply Unit are collected in the 4 MiB of 32-bit Accumulators below the matrix unit. There’s also a unified buffer of 24MB of SRAM, which work as registers. Instructions to control the processor are sent from a CPU to the TPU via the PCIe bus. These are complex CISC type instructions in order to run complex tasks which each instruction, such as numerous multiply-add calculations. These instructions are passed down a 4-stage pipeline. There are only twelve instructions for the TPU in total, the five most important of which are simply to read and write results and weights in memory, and to begin a matrix multiply/convolution of the data and weights.

At the heart of Google’s TPU is a Matrix Multiple Unit, capable of 92 trillion operations per second, but otherwise the microarchitecture is a surprisingly streamlined design. It’s built to only handle a small number of operations, but can perform them very quickly and efficiently.

Overall, Google’s TPU much more closely resembles the old idea of a floating-point co-processor than a GPU. It’s a surprisingly streamlined piece of hardware, consisting of only one major processing element and a small simplified control scheme. There are no caches, branch predictors, multi-processing interconnects, or other microarchitectural features that you’ll find in a common CPU. This again helps to save significantly on silicon area and power consumption.

In terms of performance, Google states that its TPU design typically delivers an 83x better performance-to-watt ratio compared with a CPU, and 29x better than when running on a GPU. Not only is the chip design more energy efficient, but it delivers better performance too. Across six common reference neural networking workloads, the TPU offers substantial performance benefits in all but one of the tests, often by a magnitude of 20x or faster compared to a GPU and up to 71x faster than a CPU. Of course, these results will vary depending on the type of CPU and GPU tested, but Google conducted its own tests against the high-end Intel Haswell E5-2699 v3 and Nvidia K80 for its in-depth look at the hardware.

Working with Intel for edge compute

Google’s hardware efforts have given it a major head start in the cloud space, but not all AI applications are well suited to transferring data such great distances. Some applications, such as self driving cars, require almost instantaneous compute, and so can’t rely on higher latency data transfers over the internet, even if the compute power in the cloud is very fast. Instead, these type of applications need to be done on device, and the same applies for a number of smartphone applications, such as image processing on RAW camera data for a picture.

Google’s Pixel Visual Core is primarily designed for HDR image enhancement, but the company has touted its potential for other future machine learning and neural networking applications.

With the Pixel 2, Google quietly launched its first attempt at bringing neural networking capabilities to dedicated hardware suitable for a lower power mobile form factor – the Pixel Visual Core. Interestingly, Google teamed up with Intel for the chip, suggesting that it wasn’t entirely an in-house design. We don’t know exactly what the partnership entails; it could just be architectural or more to do with manufacturing connections.

Intel has been buying up AI hardware companies, nabbing Nervana Systems in 2016, Movidius (which made chips for DJI drones) last September, and Mobileye in March 2017. We also know that Intel has its own neural networking processor in the works, codenamed Lake Crest, which falls under its Nervana line. This product was the result of Intel’s purchase of the company of the same name. We don’t know a lot about processor, but it’s designed for servers, uses a low-precision number format called Flexpoint, and boasts a blazing fast memory access speed of 8 Terabits per second. It’s going to compete with Google’s TPU, rather than it’s mobile products.

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Even so, there appear to be some design similarities between Intel and Google hardware based on images floating around online. Specifically, the multi-core configuration, use of PCIe and accompanying controller, a management CPU, and close integration to fast memory.


At a glance, the Pixel’s hardware looks quite different to Google’s cloud design, which isn’t surprising given the different power budgets. Although we don’t know as much about the Visual Core architecture as we do about Google’s Cloud TPUs, we can spot some similar capabilities. Each of the Image Processing Units (IPUs) inside the design offers 512 arithmetic logic units, for a total of 4,096.

Again, this means a highly parallelized design capable of crunching lots of numbers at once, and even this trimmed down design can perform 3 trillion operations per second. Clearly the chip features a far smaller number of math units than Google’s TPU, and there are no doubt other differences as this is primarily designed for imaging enhancements, rather than the variety of neural networks Google is running in the cloud. However, it’s a similar, highly parallel design with a specific set of operations in mind.

Whether Google sticks with this design and continues to work with Intel for future edge compute capabilities, or returns to relying on hardware developed by other companies remains to be seen. However, I would be surprised if we don’t see Google’s experience in neural networking hardware continue to evolve silicon products both in the server and small form factor spaces.

Wrap Up

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Google may be best known for its software, but when it comes to powering this new generation of AI computing, Google is equally embedded in the hardware development and deployment side.

The company’s custom TPU silicon provides the necessary energy efficiency savings needed to deploy machine learning on a large cloud scale. It also offers up notably higher performance for these specific tasks than more generalized CPU and GPU hardware. We’re seeing a similar trend in the mobile space, with SoC manufacturing increasingly turning to dedicated DSP hardware to efficiently run these mathematically intensive algorithms. Google could become a major hardware player in this market too.

We’re still waiting to see what Google has in store for its first generation smartphone AI hardware, the Pixel Visual Core. The chip will soon be switched on for faster HDR processing and will no doubt play a role in some further AI tests and products that the company rolls out to its Pixel 2 smartphones. At the moment, Google is leading the way forward with its Cloud TPU AI hardware and software support with TensorFlow. It’s worth remembering that Intel, Microsoft, Facebook, Amazon, and others are all vying for a piece of this quickly emerging market too.

With machine learning and neural networks powering an increasing number of applications both in the cloud and on edge devices like smartphones, Google’s early hardware efforts have positioned the company to be a leader in this next generation field of computing.

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Pixel 2 XL + Google Home Mini International Giveaway!

Welcome to the Sunday Giveaway, the place where we giveaway a new Android phone each and every Sunday!

A big congratulations to last week’s winner of the OnePlus 5T International Giveaway: Mrigank P. (Australia).

This week we are giving away a brand new Pixel 2 XL alongside three runner-up prizes of a Google Home Mini, in partnership with DGiT.

Google’s 2017 flagship phones are finally here, and they’re great. Both the Google Pixel 2 and Pixel 2 XL feature top-of-the-line specs, IP67 ratings for dust and water resistance (finally), as well as the best smartphone cameras on the market, according to DxOMark. They’ll also be the first devices to include Google Lens, and will also come with three full years of OS updates. More specifically, the Pixel 2 XL sports a 6.0-inch pOLED 18:9 display and a bigger 3,520 mAh battery, but other than that, these two phones are pretty much identical.

The Google Home Mini brings all the power of the larger Google Home in a much smaller size. It’s available in three colors – black, white, and the stunning coral – and it does everything the more expensive Google Home does thanks to the Google Assistant. This means you’ll be able to control your smart home, listen to news, play music through Google Play Music or Spotify, follow recipes, and more!

To learn more about the Google Pixel 2 XL, check out our related coverage below:

Enter the giveaway here

Pixel 2 XL + Google Home Mini International Giveaway!

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Google Assistant can finally recognize songs

One of Google Assistant‘s more glaring omissions since its debut in 2016 was the inability to identify songs. Some semblance of that functionality arrived with the Pixel 2 and Pixel 2 XL, but it looks like the feature is finally rolling out to Android smartphones.

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If you want Google Assistant to identify a song, you can ask “What song is this?” or something along those lines to have Google‘s virtual assistant start listening. Once the song is identified, Google Assistant presents you with a small info card that contains some lyrics, the artist, the album, when it was released, and what genre the song belongs to.

The info card also contains embedded links to listen to the song through YouTube and Google Play Music, as well as an embedded link to search the song on Google.

Alternatively, Google Assistant has “What’s this song?” as a suggestion in the carousel of choices. You will need to have voice set as the preferred input in settings for that option to pop up. Interestingly, when I tried this on my Pixel XL, it did not pop up at first and took an extra second or two for the option to pop up.

I am not sure how widely available the new feature is, but as with all things Google when it comes to software, it might take a few days until the rollout finishes. It should also be noted that I am using the English version of Google Assistant and am located in the US, so that could affect whether the ability to identify songs works for you or not.

Android Authority

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Google almost included a pair of Pixel Bud-like earbuds in the Pixel 2’s box

When you buy a top-tier smartphone, you expect to see a few things in the box: the phone (duh), a charging cable, a SIM card removal tool, a headphone jack adapter if the device doesn’t have a headphone port, as well as a pair of earbuds. That last accessory isn’t a must, but it’s definitely a nice gesture.

When you buy a Galaxy S8, you also get a great pair of AKG earbuds. HTC even included a wonderful pair of noise-canceling USonic earbuds with the U11. But for some reason, despite their $ 650+ price tags, Google didn’t include a pair of earbuds in the Pixel 2 and Pixel 2 XL box. Why? Nobody really knows, but new evidence suggests Google considered it at one point.

A customer by the name of Lucas Everett recently purchased a Pixel 2 from Verizon. Inside the box he found a cutout for a pair of earbuds, but there weren’t actually earbuds in the box.

That’s not the only strange thing—the earbuds were also mentioned in the “Inside the box” booklet as you can see in the images above.

In the first image, you can see the wired earbuds connect via USB Type-C and have inline controls. Flipping over to the second page, you’ll notice these earbuds have the same adjustable loop as the new Google Pixel Buds.

See also: Google Pixel 2 and Pixel 2 XL review: the way Android is meant to be

Lucas’ box was also missing the USB Type-C to 3.5 mm headphone jack adapter that’s included with all Pixel 2 retail units. A Verizon employee said none of the other boxes in the store had that insert. And as you can see in our Pixel 2 XL unboxing, ours didn’t either.

It’s pretty frustrating knowing that Google considered throwing in a pair of earbuds but decided against it. If they threw in a some Pixel Bud-like earbuds, would that sway your opinion one way or the other? Let us know your thoughts in the comments.

Android Authority

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You can now grab the Daydream View VR headset from the Google Store

Back when Google announced the Pixel 2 and Pixel 2 XL, it also took the wraps off some other goodies as well. The recently released Google Home Mini was one, but another was the updated Daydream View VR headset. We weren’t given a release date at the time of the announcement, but it looks like the headset has just gone live. 

You can now head over to the Google Store (link below) and pick up the headset in either Fog, Charcoal, or Coral. If you want yours sooner rather than later, the Charcoal and Coral headsets are expected to ship by October 22, while the Fog headset is back ordered by two to three weeks. 

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The headsets all come with free shipping and will run you $ 99. That’s $ 20 more than the first generation model, but Google made some improvements on the headset so it obviously feels like it can charge a little more. Those improvements include an added head strap, a new heat sink to keep things cool, and controller storage. It also comes with a wider field of view to accommodate the trend of bezel-less phones and a game bundle that is valued at more than $ 40.

If you’re looking to get a free Daydream View VR headset, keep in mind that LG and Google have teamed up to give them away when you purchase an LG V30. The purchases must be made before November 6, 2017, and you have until November 20, 2017, to complete the registration form here

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Google adds video calling through your Phone, Contacts, and Android Messages apps

As someone who uses an iPhone on a daily basis – no need for the torches and pitchforks – one of the things I appreciate is the ability to make video calls without leaving the Phone or Messages app. That is why I am happy to see Google integrate the same feature into the Phone, Contacts, and Android Messages apps.

Google accomplished this by incorporating its own Duo video calling service and the ViLTE standard, the latter of which is an extension of the existing VoLTE that focuses on increased video call quality over an LTE network. By default, video calls will be routed through ViLTE, but Duo is the fall-back if your carrier does not support the standard.

There are a few things to keep in mind, the first being that you and the person you’re calling must have Duo installed and activated if ViLTE isn’t used. Next up, you must also have the latest versions of the Phone, Contacts, Android Messages, and Duo apps installed.

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Google also mentioned that it will add the ability to upgrade a voice call to a video call later this year, a small, but appreciable, feature should you or the other person feel the need to have a video chat mid-conversation.

Duo integration

Finally, integrated video calling is rolling out to first-generation Pixel, Nexus, and Android One devices, with the Pixel 2 phones also including the feature out of the box. Google said it is working with carriers and device manufacturers to have integrated video calling across a wider variety of devices.

With the feature, it is clear that Google really wants to push video calling further, but the company might also benefit from sorting out its wide assortment of messaging, calling, and video services as well.

Android Authority

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Google Pixel 2 XL vs Samsung Galaxy Note 8: The flagship battle

This review is brought to you by MNML Case, an ultra-thin case that showcases the beauty of your new phone and fits like a glove! Get 15% OFF your Google Pixel 2 XL case until the end of October with the promo code: PIX215

Google just unwrapped its latest flagship and it’s only natural to wonder how it compares to the other big phones of the year. At $ 849 for the Pixel 2 XL, it’s definitely on the pricey side of the smartphone market and for less than $ 100 more, you can nab yourself Samsung’s latest flagship, the Galaxy Note 8.

Both devices have a lot to offer and appeal largely to different types of customers, but how do they stack up? Which device is the best and most worthy of your money? Let’s find out!

The Pixel 2 XL follows the trend of other ultra-premium flagships in 2017, sporting a taller aspect ratio display with smaller bezels. It’s bezels aren’t nearly as small as those on the Note 8, though. The Pixel 2 XL features a 6-inch pOLED QHD display with a 2880×1440 pixel resolution. It has front facing speakers at the top and bottom, and slight bezels on either side of the screen.

The Galaxy Note 8 brings a 6.3-inch QHD Super AMOLED display. It’s got a slightly lower pixel density, but the curved screen means it has a similarly-sized overall footprint. The Galaxy Note 8 only has a single speaker at the bottom, but also has a 3.5mm headphone jack, which Google left out of the Pixel 2 XL. Google includes a 3.5mm headphone jack to USB-C adapter in the box, so people with older headphones won’t have to spring for a new pair. The big question here is whether you’d rather have native support for a headphone jack, or dual front facing stereo speakers.

Both devices also support Always-On Display technology. The Galaxy Note 8 Always-On Display features shortcuts to apps, icons for your latest notifications, music controls and the ability to pin a screen off memo from the S-Pen. Meanwhile, the Pixel 2 Always-On Display is a little more understated with a fairly standard experience accompanied by the Now playing feature, which allows you to see what song is playing at any given time at a glance.

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As with any flagship smartphone in 2017, the Pixel 2 XL comes with a flagship specs list. This includes being powered by a Qualcomm Snapdragon 835 processor with an Adreno 530 GPU, 4 GB of RAM and either 64 GB or 128 GB of storage. The Galaxy Note 8 has the same processing package but increases the RAM to 6 GB and offers 256 GB of storage instead of 128 GB. Both devices also have IP67 dust and water resistance, but the Galaxy Note 8 also comes with other useful extra likes wireless charging and a microSD card slot for expandable storage.

On the back is where you’ll find one of the biggest differences between the two. The Galaxy Note 8 is Samsung’s first attempt at the dual camera. It incorporates two 12MP sensors with an f/1.7 aperture on the wide-angle lens, and an f/2.4 aperture on the telephoto lens. There’s also OIS in both lenses, which is a first for smartphone cameras. You can use the dual cameras to add bokeh to your shots.

The Pixel 2 XL’s front-facing speakers mean its bezels aren’t nearly as thin as the Galaxy Note 8.

The Pixel 2 XL takes a different approach and with it, Google is signaling to the world that a single camera can do the same job as two. The rear camera is a 12.2MP sensor with f/1.8 aperture and OIS, but the stand out feature is Portrait Mode. While every other smartphone OEM needs two cameras to achieve this, Google is able to achieve this by using one lens, dual pixel cameras, and its powerful machine learning algorithms.

The original Pixel XL had what was arguably the best camera of 2016, and with a record-high DxO Mark score of 98, Google’s new flagships could have the best smartphone cameras ever. Of course, the real proof will come once we put these smartphones head to head so stay tuned for that before the end of the month.

As you might have expected, the Pixel 2 XL runs Android Oreo out of the box, while the Note 8 launched with Nougat and will be updated to Android Marshmallow in the near future. Google’s version of Oreo brings a mostly stock experience, with a redesigned Pixel launcher, notification dots, native picture-in-picture and a whole lot more.

The Pixel 2 XL uses machine learning and dual pixels to achieve bokeh effects with only one lens.

The Pixel 2 is the first Android smartphone with Google Lens, which uses machine learning to give you information about anything you point the camera at. It’s similar to Samsung’s Bixby Vision, but being linked to the world’s largest search engine will probably increase usability. The Pixel 2 XL also comes with the new Active Edge feature that lets you squeeze the edge of the phone, like the HTC U11’s Squeeze feature, as an easy way to launch Google Assistant.

The Galaxy Note 8 comes with Samsung’s software experience on top of Android 7.1.1 Nougat. The standout feature of this phone is the S Pen which can be used to jot down notes, create drawings, translate sentences, and more. The S-Pen brings a few tweaks over last year like being able to save screen off memos that are up to 100 pages long, send gif-like live messages, and more.


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Which smartphone would you choose between the Google Pixel 2 XL and the Samsung Galaxy Note 8? Share your thoughts in the comments section below.

Missed all the announcements from the Google event? We’ve got you covered!

Android Authority

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Ported Google Camera with HDR+ gets RAW support and squashes major bugs

The modified version of the Google Camera app caused a few ripples in the Android community because it allowed those who don’t own Pixel or Nexus devices to try out Google‘s excellent HDR+ chops, among other features. Thankfully for fans, independent developer B-S-G did not stop his work on the modified app and released a new version that adds RAW support, squashes some major bugs, and throws in a few features along the way.

With the update, the ported Google Camera HDR+ app can enable RAW capture while saving the JPEG file. RAW support might not be significant for most folks, but it allows others to use their computers for additional processing and fine-tuning as they see fit. It also allows you to use HDR+ and bypass the processing that happens after snapping a picture.

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The updated port also allows you to configure the processing modes for HDR+. Keep in mind that you will need to completely close the application and open it for the changes to go into effect. There are also certain combinations that will not work well with each other, so just play around with the settings and see what works.

Finally, overall speed and stability have supposedly been significantly improved with Google Camera HDR+.

Alas, the list of devices confirmed to work with the app is not very extensive, but includes the following:

Other devices, such as the Nokia 6 and Xiaomi Redmi Note 4, should work with the app, since they support the Camera2 API. The list should increase over time, but as of now, it’s a wait-and-see approach.

If you want to give the updated Google Camera HDR+ a spin, head to Android FileHost to download it.

Android Authority

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Sony’s new Google Assistant-powered speaker will take on Google Home and Amazon Echo

Yesterday, Google announced at IFA in Berlin that its Assistant will soon expand to more third-party speakers. Only a day later, one of them has already been revealed by Sony. The company took the wraps off the LF-S50G, which offers a lot of the same functionalities found on the Google Home and other similar devices.

The Assistant-powered speaker will play you music based on your commands from services like Spotify, Google Play Music, and Pandora, let you know what the weather is like, and even answer any weird questions you might have. Additionally, you can also use it to control other smart devices found in your home.

See also:
Sony Xperia XZ1 and Xperia XZ1 Compact hands-on – a flagship in two sizes

Sony Xperia XZ1 and Xperia XZ1 Compact hands-on – a flagship in two sizes

3 hours ago

The device is not completely waterproof but is splash-resistant (IPX3), has a simple yet attractive design, and even shows you what time it is. According to Sony, the speaker offers a 360-degree audio experience and has enough power to “comfortably fill the average room with sound”. It supports Bluetooth as well as NFC and sports a gesture control top that allows you to play music, skip tracks, and adjust the volume.

Sony’s smart speaker will go on sale in the US in October and will set you back $ 200. You’ll be able to get it in either black or gray. A month later, it will also be available in certain European countries — Germany, France, the UK — where it will cost you around €230 or £200.

The demand for voice-controlled speakers is on the rise, so it’s no wonder that companies like Sony are entering the market with their own products. However, the LF-S50G is facing some serious competition from devices like the Google Home and Amazon’s Alexa-powered speakers, just to name a few.

The competition will only heat up in the future, with Apple releasing the HomePod in December, while Samsung is expected to announce its own speaker with Bixby on board, although there’s no word on when exactly that might happen.

Android Authority

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Google’s Preview Program now gives Google Home owners first dibs on upcoming updates

It is not unusual for companies to provide its users several features before the rest of us. One of the ways Google does this is through its Preview Program, which was first introduced for the Chromecast last year. Now, the search giant has expanded the program to include the Google Home.

As previously alluded to, the Preview Program gives folks early access to new features, but Google stresses that the program is not a beta – the updates they receive are the same as those the rest of us receive. Rather, people who sign up for the Preview Program are first in line for these updates and, as such, are encouraged to provide Google with feedback.

See also:
How to use Google Home with Chromecast

How to use Google Home with Chromecast

4 weeks ago

If you want to sign up for the Google Home’s Preview Program, here are the steps you need to take:

  1. From your phone or tablet, open the Google Home app
  2. In the upper right corner of the home screen, tap Devices to see your available Chromecast and Google Home devices
  3. Scroll to find the device card for the device you’d like to enroll in the Preview Program
  4. In the top right corner of the device card, tap the device card menu
  5. Tap Settings > Preview Program. If you don’t see Preview Program, we aren’t accepting new members at this time. Please continue to check back as opportunities become available.
  6. Choose whether to receive email notifications by moving the slider to the right or left. Note: We recommend allowing email notifications so you’ll know when new updates are pushed to your device.
  7. If you opt-in to email notifications, you’ll be asked to sign into your Google account if you haven’t already.
  8. Review the contents of that page, and tap Join Program.
  9. Review the contents of the page, then tap OK, GOT IT.

When we checked out the Google Home, we thought it showed plenty of promise that might be fulfilled with future software updates. This Preview Program is a chance for folks to possibly see that potential realized ahead of other folks while being able to help Google fix some kinks along the way.

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