09 June 2018

US startups off to a strong M&A run in 2018


With Microsoft’s $7.5 billion acquisition of GitHub this week, we can now decisively declare a trend: 2018 is shaping up as a darn good year for U.S. venture-backed M&A.

So far this year, acquirers have spent just over $20 billion in disclosed-price purchases of U.S. VC-funded companies, according to Crunchbase data. That’s about 80 percent of the 2017 full-year total, which is pretty impressive, considering we’re barely five months into 2018.

If one included unreported purchase prices, the totals would be quite a bit higher. Fewer than 20 percent of acquisitions in our data set came with reported prices.1 Undisclosed prices are mostly for smaller deals, but not always. We put together a list of a dozen undisclosed price M&A transactions this year involving companies snapped up by large-cap acquirers after raising more than $20 million in venture funding.

The big deals

The deals that everyone talks about, however, are the ones with the big and disclosed price tags. And we’ve seen quite a few of those lately.

As we approach the half-year mark, nothing comes close to topping the GitHub deal, which ranks as one of the biggest acquisitions of a private, U.S. venture-backed company ever. The last deal to top it was Facebook’s $19 billion purchase of WhatsApp in 2014, according to Crunchbase.

Of course, GitHub is a unique story with an astounding growth trajectory. Its platform for code development, most popular among programmers, has drawn 28 million users. For context, that’s more than the entire population of Australia.

Still, let’s not forget about the other big deals announced in 2018. We list the top six below:

Flatiron Health, a provider of software used by cancer care providers and researchers, ranks as the second-biggest VC-backed acquisition of 2018. Its purchaser, Roche, was an existing stakeholder who apparently liked what it saw enough to buy up all remaining shares.

Next up is job and employer review site Glassdoor, a company familiar to many of those who’ve looked for a new post or handled hiring in the past decade. The 11-year-old company found a fan in Tokyo-based Recruit Holdings, a provider of recruitment and human resources services that also owns leading job site Indeed.com.

Meanwhile, Impact Biomedicines, a cancer therapy developer that sold to Celgene for $1.1 billion, could end up delivering an even larger exit. The acquisition deal includes potential milestone payments approaching nearly $6 billion.

Deal counts look flat

Not all metrics are trending up, however. While acquirers are doing bigger deals, they don’t appear to be buying a larger number of startups.

Crunchbase shows 216 startups in our data set that sold this year. That’s roughly on par with the pace of dealmaking in the year-ago period, which had 222 M&A exits using similar parameters. (For all of 2017, there were 508 startup acquisitions that met our parameters.2)

Below, we look at M&A counts for the past five calendar years:

Looking at prior years for comparison, the takeaway seems to be that M&A deal counts for 2018 look just fine, but we’re not seeing a big spike.

What’s changed?

The more notable shift from 2017 seems to be buyers’ bigger appetite for unicorn-scale deals. Last year, we saw just one acquisition of a software company for more than a billion dollars — Cisco’s $3.7 billion purchase of AppDynamics — and that was only after the performance management software provider filed to go public. The only other billion-plus deal was PetSmart’s $3.4 billion acquisition of pet food delivery service Chewy, which previously raised early venture funding and later private equity backing.

There are plenty of reasons why acquirers could be spending more freely this year. Some that come to mind: Stock indexes are chugging along, and U.S. legislators have slashed corporate tax rates. U.S. companies with large cash hordes held overseas, like Apple and Microsoft, also received new financial incentives to repatriate that money.

That’s not to say companies are doing acquisitions for these reasons. There’s no obligation to spend repatriated cash in any particular way. Many prefer share buybacks or sitting on piles of money. Nonetheless, the combination of these two things — more money and less uncertainty around tax reform — are certainly not a bad thing for M&A.

High public valuations, particularly for tech, also help. Microsoft shares, for instance, have risen by more than 44 percent in the past year. That means that it took about a third fewer shares to buy GitHub this month than it would have a year ago. (Of course, GitHub’s valuation probably rose as well, but we’ll ignore that for now.)

Paying retail

Overall, this is not looking like an M&A market for bargain hunters.

Large-cap acquirers seem willing to pay retail price for startups they like, given the competitive environment. After all, the IPO window is wide open. Plus, fast-growing unicorns have the option of staying private and raising money from SoftBank or a panoply of other highly capitalized investors.

Meanwhile, acquirers themselves are competing for desirable startups. Microsoft’s winning bid for GitHub reportedly followed overtures by Google, Atlassian and a host of other would-be buyers.

But even in the most buoyant climate, one rule of acquiring remains true: It’s hard to turn down $7.5 billion.

  1. The data set included companies that have raised $1 million or more in venture or seed funding, with their most recent round closing within the past five years.
  2. For the prior year comparisons, including the chart, the data set consisted of companies acquired in a specified year that raised $1 million or more in venture or seed funding, with their most recent round closing no more than five years before the middle of that year.

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Evoluent Vertical Mouse: Do Your Wrist a Favor and Buy This Mouse

No More Photoshop: 5 No-Signup Image Editors on the Web


free-online-image-editors

It is a pain to fire up Photoshop, Pixelmator, or GIMP for a simple task like resizing some photos or blurring sensitive information in an image. Well, you don’t need to. Use these websites to do your job in a jiffy.

I’m a big fan of doing common web tasks without signing up. Apart from the convenience, it’s also a big step in protecting your privacy online, especially when you realize how much information websites store about you.

When it comes to everyday operations for an image, you’d be better off using one of these web apps to quickly and efficiently finish what you need to do.

Image Blur (Web): Blur Sensitive Information in Photos

When you share a screenshot or an image, it can often have sensitive information that you don’t want others to know. You might want to protect someone’s identity by blurring their face or even stop bots from reading your email address.

Image Blur is the simplest tool I’ve seen for this task. It only lets you upload images from your hard drive, so you can’t use links to photos. Once the image is uploaded, draw a rectangle anywhere and click “Blur it” to apply the effect. You can have multiple rectangles in the same image to blur different spots. After finishing, you can download the image to your hard drive again. Nothing is stored in the cloud, and the servers are purged periodically, so as to protect privacy.

Image Blur is tremendously convenient to use, but if you’re looking for a little more control, try LunaPic. You’ll need to register to use it, but the web app lets you both pixelate and blur images online.

Screely (Web): Add a Beautiful Background to Images or Screenshots

Don’t share a drab old image on the internet, or a badly cropped screenshot that ruins the rounded edges of the window you took it in. There’s a better way. It’s called Screely.

Crop your drab image to the desired size first, and then upload it to Screely. The site will automatically add a background to it, along with a drop shadow, making it look like those professional screenshots and images you see online. You can change the color of the background too.

For screenshots, Screely lets you add a fake window title bar if you want. It only has the Mac title bar theme though.

Screely is a simple tool that does its job well. What was usually five to seven steps in Photoshop is now much faster.

AddText (Web, Android, iOS): Quickly Add Text to Any Image

Whether you’re creating a “One Does Not Simply” meme or actually adding a caption to an image, AddText is the easiest and quickest way to finish the job. Plus, it’s quite customizable.

Once you upload the image, you can add as many text boxes as you want. Each box can have a different font style, color, size, and position. Go wild, it’s all up to you. There are some quirky and fun font styles available here, so go through the selections, you might find something cool to make your text look interesting.

AddText also has mobile apps for Android and iOS, which are just as easy as the web app. Since the web version doesn’t work well on mobile screens, the apps are a better solution. But it defeats the purpose of a quick, no-signup app, so you might as well get one of the best smartphone photo-editing apps.

Social Image Resizer Tool (Web): Crop and Resize for Social Platforms

The blog Internet Marketing Ninjas developed a cool web app for anyone who wants to change their social media picture. As you probably know, you usually need a cheat sheet for social media sizes, since Facebook, Twitter, and others keep changing the dimensions of profile pictures, headers, and so on.

Social Image Resizer Tool (SIRT) gets rid of the cheat sheet. Upload an image and you can start cropping it perfectly. Choose what you are making first, like a Facebook header or YouTube profile picture, and SIRT will automatically give you rectangle or circle selection accordingly. Resize and drag it to the desired part of your image. You can see the original image size, the selection size, and the final size at all times.

Once you’re done, choose JPEG, PNG, GIF, or ICO as the final file format and download it to your hard drive.

BIRME (Web): Resize and Rename Many Images in One Click

Bulk Image Resizing Made Easy, or BIRME, is the simplest online tool I’ve come across to resize and rename images in a batch. Plus, it’s surprisingly customizable too.

First, upload all the images you want to resize. Choose the desired height or width (and you can have the height or width auto-adjust too, depending on portrait or landscape pictures). Apart from resizing, BIRME will also crop images to your desired aspect ratio, so choose wisely. You can also add a border to all the photos. Images will be saved in JPEG format at 80% quality by default, so you might want to pump that up. And you can rename them too, of course.

BIRME smartly gives users the option to download all photos as a ZIP file, or individually if that’s what you want. As long as you have a fast internet connection to upload and then download those pictures, BIRME is better than resizing images in bulk on a computer.

Not Just Photos, Videos Too

Such simple, no-signup editors aren’t the sole domain of photo editors. If it’s a video you want to crop or resize, there’s a solution for that too. Try one of these free online video editors that make you anonymous, it takes almost no time to do what you need to.

Read the full article: No More Photoshop: 5 No-Signup Image Editors on the Web


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08 June 2018

Google at NAACL




This week, New Orleans, LA hosted the North American Association of Computational Linguistics (NAACL) conference, a venue for the latest research on computational approaches to understanding natural language. Google once again had a strong presence, presenting our research on a diverse set of topics, including dialog, summarization, machine translation, and linguistic analysis. In addition to contributing publications, Googlers were also involved as committee members, workshop organizers, panelists and presented one of the conference keynotes. We also provided telepresence robots, which enabled researchers who couldn’t attend in person to present their work remotely at the Widening Natural Language Processing Workshop (WiNLP).
Googler Margaret Mitchell and a researcher using our telepresence robots to remotely present their work at the WiNLP workshop.
This year NAACL also introduced a new Test of Time Award recognizing influential papers published between 2002 and 2012. We are happy and honored to recognize that all three papers receiving the award (listed below with a shot summary) were co-authored by researchers who are now at Google (in blue):

BLEU: a Method for Automatic Evaluation of Machine Translation (2002)
Kishore Papineni, Salim Roukos, Todd Ward, Wei-Jing Zhu
Before the introduction of the BLEU metric, comparing Machine Translation (MT) models required expensive human evaluation. While human evaluation is still the gold standard, the strong correlation of BLEU with human judgment has permitted much faster experiment cycles. BLEU has been a reliable measure of progress, persisting through multiple paradigm shifts in MT.

Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms (2002)
Michael Collins
The structured perceptron is a generalization of the classical perceptron to structured prediction problems, where the number of possible "labels" for each input is a very large set, and each label has rich internal structure. Canonical examples are speech recognition, machine translation, and syntactic parsing. The structured perceptron was one of the first algorithms proposed for structured prediction, and has been shown to be effective in spite of its simplicity.

Thumbs up?: Sentiment Classification using Machine Learning Techniques (2002)
Bo Pang, Lillian Lee, Shivakumar Vaithyanathan
This paper is amongst the first works in sentiment analysis and helped define the subfield of sentiment and opinion analysis and review mining. The paper introduced a new way to look at document classification, developed the first solutions to it using supervised machine learning methods, and discussed insights and challenges. This paper also had significant data impact -- the movie review dataset has supported much of the early work in this area and is still one of the commonly used benchmark evaluation datasets.

If you attended NAACL 2018, we hope that you stopped by the booth to check out some demos, meet our researchers and discuss projects and opportunities at Google that go into solving interesting problems for billions of people. You can learn more about Google research presented at NAACL 2018 below (Googlers highlighted in blue), and visit the Google AI Language Team page.

Keynote
Google Assistant or My Assistant? Towards Personalized Situated Conversational Agents
Dilek Hakkani-Tür

Publications
Bootstrapping a Neural Conversational Agent with Dialogue Self-Play, Crowdsourcing and On-Line Reinforcement Learning
Pararth Shah, Dilek Hakkani-Tür, Bing Liu, Gokhan Tür

SHAPED: Shared-Private Encoder-Decoder for Text Style Adaptation
Ye Zhang, Nan Ding, Radu Soricut

Olive Oil is Made of Olives, Baby Oil is Made for Babies: Interpreting Noun Compounds Using Paraphrases in a Neural Model
Vered Schwartz, Chris Waterson

Are All Languages Equally Hard to Language-Model?
Ryan Cotterell, Sebastian J. Mielke, Jason Eisner, Brian Roark

Self-Attention with Relative Position Representations
Peter Shaw, Jakob Uszkoreit, Ashish Vaswani

Dialogue Learning with Human Teaching and Feedback in End-to-End Trainable Task-Oriented Dialogue Systems
Bing Liu, Gokhan Tür, Dilek Hakkani-Tür, Parath Shah, Larry Heck

Workshops
Subword & Character Level Models in NLP
Organizers: Manaal Faruqui, Hinrich Schütze, Isabel Trancoso, Yulia Tsvetkov, Yadollah Yaghoobzadeh

Storytelling Workshop
Organizers: Margaret Mitchell, Ishan Misra, Ting-Hao 'Kenneth' Huang, Frank Ferraro

Ethics in NLP
Organizers: Michael Strube, Dirk Hovy, Margaret Mitchell, Mark Alfano

NAACL HLT Panels
Careers in Industry
Participants: Philip Resnik (moderator), Jason Baldridge, Laura Chiticariu, Marie Mateer, Dan Roth

Ethics in NLP
Participants: Dirk Hovy (moderator), Margaret Mitchell, Vinodkumar Prabhakaran, Mark Yatskar, Barbara Plank


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Beyond Trello Basics: 8 Handy Tips and Tricks for a Faster Workflow


trello-tricks

Once you have figured out the basics of using Trello, it’s time to level up! Your favorite digital Kanban tool hides quite a few useful tricks up its sleeve, and in this article we’re going to explore a few of them and how you can make use of them.

1. Turn Any Webpage Into a Trello Card

send-to-trello-bookmarklet

Find yourself creating many cards while browsing the web for inspiration or research?

You don’t have to interrupt your workflow by switching to a Trello board every time you want to create a card. With this Trello bookmarklet, you can turn webpages into cards on the fly.

Once you drag the Send to Trello bookmarklet to your Bookmarks, you’re all set. The next time you’re on a webpage that you would like to convert to a card, click on this bookmark in your browser’s bookmarks bar.

You’ll then get a popup in which you can select the board and list where the new card should go. If you change your mind midway and don’t want to create the card after all, hit the Never Mind button in the popup.

2. Use Markdown in Trello

markdown-formatting-trello

Markdown is everywhere, and with good reason. It makes writing for the web faster and intuitive. You can now use Markdown in your Trello workflow.

Basic formatting like emphasis, italics, and links follows standard Markdown syntax. Trello does have a few formatting restrictions in place. For example, certain syntax works only with card descriptions and comments, while some of it works in checklist items as well. It’s a pity you can’t use Markdown in card titles.

Read the official help page to learn how to format your text the Trello way. Want a quicker solution? Click on the Formatting Help link when you’re viewing the back of a card. Trello will then display its basic Markdown formatting rules in a popup on the right.

3. Clone Public Boards

copy-public-board-trello

Cloning boards with the Copy Board option in the Show Menu sidebar is one of those essential Trello productivity tips we recommend to all users. But don’t stop at your own boards!

With a bit of effort, you’ll find plenty of useful public boards to copy and repurpose. Trello itself has a roundup of handy public boards to inspire you.

Any public board you copy to your account is automatically classified as Private. Also, while copying the board you get the option to rename the copy and discard the cards if you would rather have only the lists in place.

4. Enable Trello Power-Ups

power-ups-trello

The power of Trello’s Power-Ups allows you to integrate custom fields plus data from various apps into your Trello boards.

For example, you can set reminders with the Card Repeater Power-Up, or build your own forms with the JotForm Power-Up.

This feature alone might be enough to tempt you to upgrade your Trello account to Business Class. (Each board in the free tier has a limit of one Power-Up.)

To enable a Power-Up for a board, first click on the Show Menu button in the top right section. In the fly-out sidebar that appears, click on the Power-Ups option to reveal Trello’s library of versatile add-ons. Hit the Enable button for any of them to integrate the Power-Up into the active board.

5. Automate Trello Card Creation

card-repeater-power-up-trello

Take the pain out of creating recurring cards by hand with a tool or two. One way to do that is with the Card Repeater Power-Up that we mentioned in the above section.

Once you enable the Power-Up, you’ll see a Repeat button appear under Power-Ups in the sidebar on the card back. Click on that button to schedule card creation. You get to pick the list, position, day of the week, time, and the frequency for recurring cards. After you tweak the available options, hit the Save button.

You can also fall back on the trusty IFTTT for some Trello automation. This IFTTT recipe creates cards out of emails in Gmail.

The Butler and Zapier Power-Ups can also automate the card creation process for you.

6. Cut, Copy, and Paste Trello Cards

While you’re used to the universal cut-copy-paste shortcut trio of Ctrl + X, Ctrl + C, Ctrl + V, you probably don’t expect it to work on cards. But it does! The best part is that it works across boards.

Hover over any card and cut or copy it. Next, hover over the Add a card button in any list on any board and hit the keyboard shortcut to paste.

Of course, you’ll have to replace the Ctrl key in the shortcuts with the Cmd key if you’re a macOS user.

7. Change Due Dates With Drag-and-Drop

calendar-view-trello

Want to reassign due dates for several cards? Sure, you can do it one at a time as usual. But you don’t have to!

If you enable the Calendar Power-Up, you can reschedule cards by dragging and dropping them onto the right date in the calendar view. This view shows up when you click on the Calendar button to the left of the Show Menu button.

Keep in mind that the Calendar button shows up only after you enable the Power-Up.

8. Insert New Lists Between Existing Lists

insert-list-trello

Clicking on the Add a List button after the last list on a board is how you create lists. If you want the new list to appear in a different position, you have to drag and drop it to the right location.

Want a quicker way to do that?

There is one. To insert a new list between two existing lists, double-click on the empty space between them. You’ll then see an option to create a new list right there.

If you double-click in the space below any list, you can create a new one to show up right after that list.

Add More Power to Trello With Third-Party Tools

Wish Trello could do this or that? It probably can, once you power it up with smart third-party tools. Start by getting a few browser extensions for Trello. They allow you to add card numbers, advanced sort options, list hiding, and so on. Next, move on to a few essential Trello integrations that will make your job easier.

Trello is as versatile as your ideas are. Once you become familiar with its various nooks and crannies, Trello can keep every bit of your day-to-day life on track. Now, are you ready to explore a few unique ways to use Trello?

Read the full article: Beyond Trello Basics: 8 Handy Tips and Tricks for a Faster Workflow


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The Beginner’s Guide to Apple AirPlay Mirroring on Mac and iOS


airplay-guide

Many people buy an Apple TV solely to send video or audio wirelessly from their Mac and iOS devices to the big screen in their living room via AirPlay. It’s a handy feature, with a huge number of applications, and it generally works quite well.

Both macOS and iOS handle AirPlay in their own ways. Whether you want to share family photos, give a presentation, or extend your Mac desktop beyond the confines of your laptop, it’s a powerful tool and one you should learn how to use.

Today we’re going to look at AirPlay and how you can get the most out of it.

What Is Apple AirPlay?

AirPlay is Apple’s proprietary wireless streaming protocol. It allows you to send video or audio from your Mac or iOS device to an AirPlay receiver, like an Apple TV. Apple first introduced AirPlay as AirTunes for iTunes in 2004.

Back then you could only stream wireless audio, but in 2010 the feature made its way onto iOS with support for video streaming too. The following year, the company introduced AirPlay mirroring, and in May 2018 Apple introduced its successor, AirPlay 2.

AirTunes Promo

What Is AirPlay Mirroring?

AirPlay mirroring is the ability to mirror your current display on an AirPlay receiver. The feature exists on both iOS devices like the iPhone and iPad, as well as Mac computers and laptops.

While mirroring sends both video and audio, some content is restricted due to potential copyright violation. If you try to mirror your Mac’s display while playing protected iTunes content, like Apple Music videos, you’ll see a grey box where the video should be.

What Is AirPlay 2?

AirPlay 2 was announced by Apple at WWDC 2017 and was due to launch with iOS 11 in the fall of that year. In May 2018, AirPlay 2 finally released, enabling multi-room audio for the first time. You can now stream music to multiple devices around your house, which was previously only possible using iTunes on a Mac or PC.

AirPlay 2 also plays a part in enabling full stereo playback (where available) on multiple HomePod smart speakers (our Apple HomePod review). The second version of Apple’s wireless streaming protocol is included in the iOS 11.4 update, enabling any device that can run iOS 11 to make use of the technology.

Apple HomePod

Apple TV units that update to tvOS 11.4 can also use AirPlay 2. Apple’s HomePod should update itself automatically. Follow our HomePod troubleshooting guide if it doesn’t. Older third-party devices may not be updated to include support for the refreshed protocol, so if you own any old receivers it’s worth checking with the manufacturer if they’re compatible.

How to Use AirPlay to Stream or Mirror

You can either use AirPlay to stream content to a receiver (audio or video), or to mirror your current device’s screen to a receiver (including audio). In order to use AirPlay, make sure Bluetooth and Wi-Fi are both enabled, and that Airplane Mode is disabled on your device.

The easiest way to use AirPlay is to look for the AirPlay logo, which looks like a square with a triangle in front of it (pictured below). Any time you see this symbol, click or tap it and select your destination receiver from the list that pops up. Your media will then stream wirelessly.

Apple AirPlay

How to AirPlay From iPhone/iPad to Apple TV

To stream audio or video to an AirPlay receiver from an iPhone or iPad:

  1. Swipe up from the bottom of the screen (non-iPhone X) to reveal Control Center. iPhone X users should swipe down from the top-right corner.
  2. 3D Touch the Now Playing box to the right of the screen.
  3. Tap on the wireless icon (three circles and a triangle) next to the playback controls.
  4. Wait for the AirPlay receiver to appear in the list.
  5. Tap on your chosen receiver and play some media.

AirPlay on iOS

To stop streaming via AirPlay, repeat the process and choose iPhone or iPad in step five.

To mirror your iPhone or iPad screen:

  1. Swipe up from the bottom of the screen (non-iPhone X) to reveal Control Center. iPhone X users, swipe down from the top-right corner.
  2. Tap Screen Mirroring on the left-hand side of the screen.
  3. Wait for any nearby AirPlay devices to appear.
  4. Tap the receiver on which you would like to mirror your screen.

AirPlay Mirroring

To stop mirroring, repeat the process and tap Stop Mirroring in step four.

How to AirPlay From Mac to Apple TV

To connect your Mac to an Apple TV, look for the AirPlay icon in apps like iTunes and QuickTime. You can also use System Preferences > Displays to specify an AirPlay Display, which behaves like a wireless monitor connected to your Mac. This allows you to stream from a Mac to an Apple TV.

AirPlay on Mac

The easiest way to mirror your Mac to an Apple TV is via the menu bar shortcut. Click on the AirPlay logo in the top-right corner of the screen, then click on the receiver of your choice. Once connected you can choose:

  • Mirror Built-in Display: Match the size of your Mac’s screen, mirrored on an Apple TV.
  • Mirror Apple TV: Match the size of your TV, optimizing your Mac’s screen.
  • Use as Separate Display: Disable mirroring entirely, and use your Apple TV like an external monitor.

How to AirPlay From iPhone/iPad to Mac or Windows

Apple doesn’t allow a Mac (or Windows) computer to act as an AirPlay receiver, despite many users valuing the feature. Fortunately you can add this functionality with some third-party software. You currently have two good options:

  • AirServer ($20): The gold standard for AirPlay receiver emulation, available for Mac and Windows. Also works with Google Cast and Miracast for an all-around casting solution. There’s a 14-day free trial available.
  • Reflector ($15): A slightly cheaper alternative to AirServer, with support for Google Cast and Miracast. You can try it free for seven days.

You can try both of these solutions before you buy, and it’s probably worth doing so to ensure performance is adequate. Personal experience has led me to believe these software solutions are never quite as good as a genuine Apple TV, but your mileage may vary.

Troubleshooting and Settings for AirPlay

Sometimes, AirPlay doesn’t work as expected. Often, these issues are caused by external factors, but it’s always worth restarting your equipment before trying anything drastic.

Streaming, Quality, and Other AirPlay Playback Issues

Much of the time, problems streaming video or audio wirelessly is due to Wi-Fi congestion. Too many competing Wi-Fi signals, on similar channels to your receiver, can reduce the quality of the signal that reaches the Apple TV.

Older devices that feature slower wireless speeds can also struggle. There’s not much you can do about that beyond getting as close to the receiver as possible, or using a newer iOS device.

How to Change Your Apple TV’s AirPlay Name

Rename Apple TV's AirPlay name

If you have multiple Apple TV units in one house, or your neighbor’s Apple TV is constantly showing up in the list, you can differentiate receivers by giving them unique names. To rename your Apple TV, head to Settings > General > About > Name.

How to Turn On/Off AirPlay on Your Apple TV

Turn AirPlay On or Off on Apple TV

You can turn AirPlay off entirely, or restrict who can use AirPlay under Settings > AirPlay on your Apple TV. Options include:

  • Allowing anyone to stream via AirPlay.
  • Restricting AirPlay to devices that are on the same network as your Apple TV.
  • Turning AirPlay off altogether.
  • Setting a password which other users must first enter before they can use AirPlay on that device.

Apple TV Doesn’t Show Up on Mac or iOS

If you can’t find your Apple TV (or other receiver) on your Mac, first make sure your Wi-Fi and Bluetooth are both on. Next make sure your Apple TV is on, and connected to power and a TV via HDMI.

The Apple TV should automatically wake up when it detects a new AirPlay connection, but sometimes clicking the remote and waking it manually can resolve the issue. If you still can’t see your Apple TV on your Mac or iPhone, try restarting it.

To restart an Apple TV, head to Settings > System > Restart. The process should take around 30 seconds, and you’ll need to wake the remote by pressing a button once it’s complete. If the Apple TV has crashed, you can simply pull the cord out of the back and wait 10 seconds, then power it back up.

Restart Apple TV

If none of that works, the next step is to restart your source device. That might be your Mac, iPhone, or iPad. Next try restarting your network equipment. If you’re still having trouble, try a different Mac or iOS device to isolate the problem further.

You can also restore your Apple TV to factory settings, which is a final resort for most but worth a try if nothing else works. Head to Settings > System > Reset and follow the prompts. You’ll need to set up your Apple TV from scratch once the reset completes.

Factory Reset Apple TV

AirPlay Is the Future of Wireless Home Media

The presence of AirPlay signifies that Apple is still serious about cutting the cord. As Wi-Fi performance improves, so too will the speed, quality, and reliability of AirPlay as a protocol.

Apple is betting big on other wireless technologies, too. In the last few years we’ve seen wireless earphones like the AirPods and BeatsX, an Apple Watch with integrated cellular, and wireless charging added to both the iPhone 8 and X. Who knows what will come next?

Read the full article: The Beginner’s Guide to Apple AirPlay Mirroring on Mac and iOS


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How to Stop Auto-Playing Videos in YouTube’s Home Feed

How to Customize App Borders and Shadows on Windows 10


windows-apps-enhance

On Windows, you’ve been able to change how apps look for almost the entire history of the operating system’s life.

However, Insider Preview builds of Redstone 5 (the next Windows update to be released in Fall 2018) suggest that Windows will automatically change the color of all app borders to gray. The theory is that it will match the new shadows better.

Thankfully, you will still be able to override those default settings and change the color. You can even turn the shadows on and off at your pleasure. Let’s take a closer look.

How to Customize App Borders and Shadows

Firstly, we will explain how to change the color of the app borders, and then we’ll look at how to turn the shadow on and off. To change the colors, follow the steps below:

  1. Open the Settings app.
  2. Click on Personalize.
  3. On the menu in the left-hand panel, select Colors.
  4. You can choose one of the default colors, or you can click on Custom color and enter your own RBG or hex code.
  5. Scroll down to Show the accent color on the following surfaces.
  6. Mark the checkbox next to Title bars.

If you would like to add shadows to your app windows, follow these steps:

  1. Go to Control Panel > System and Security > System > Advanced System Settings.
  2. Open the Advanced tab.
  3. In the Performance section, click on Settings.
  4. Click on the Visual Effects tab.
  5. Mark the checkbox next to Custom.
  6. Mark or unmark the checkbox next to Show shadows under windows as preferred.
  7. Click on Apply
  8. Finish by clicking on OK.

Remember one of the best ways to customize the operating is to use your own theme. You can choose a light theme for Windows or a dark theme for Windows.

Read the full article: How to Customize App Borders and Shadows on Windows 10


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How to Make Web Pages Load Faster With a VPN (Yes, It Really Works)


vpn-protocols-explained

As you’ve probably seen from the dozens of emails in your inbox, the European Union’s General Data Protection Regulation (GDPR) law has gone into effect. This has forced companies to change how they store your data, be more transparent about what data they have, and allow you to delete it if you want.

While this law doesn’t have much effect on those outside of the EU, those outside the EU can actually use it to their advantage. Indeed, thanks to the GDPR, most users can now enjoy faster web loading speeds.

The VPN Trick That Makes Websites Load Faster

The GDPR restricts websites from using common forms of tracking on the web, including ad servers, Google’s various analytics, and social media sharing buttons. Every time you open a website that uses these elements, your browser has to load them, which takes time.

GPDR-compliant websites strip away most of these elements, making each page load much faster. Of course, websites still want to collect information on users from other countries if they can. But no matter where you live, you can enjoy these same speed increases by using a VPN!

VPN-Connect-to-UK

If you didn’t know, VPNs disguise your browsing by making it look like your traffic comes from another location. With a reputable VPN service, you can simply connect to a server from the UK or another country in the EU and access the benefits of GPDR.

Web developers have found this makes a huge difference in both speed and amount of extra junk loaded onto websites.

When using this method, note that some websites block EU users because their site isn’t GDPR-compliant yet (or will never be). Also, keep in mind the dangers of using a free VPN. We recommend a reputable service like ExpressVPN, which won’t sell your browsing data or inject ads.

Read the full article: How to Make Web Pages Load Faster With a VPN (Yes, It Really Works)


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07 June 2018

Realtime tSNE Visualizations with TensorFlow.js




In recent years, the t-distributed Stochastic Neighbor Embedding (tSNE) algorithm has become one of the most used and insightful techniques for exploratory data analysis of high-dimensional data. Used to interpret deep neural network outputs in tools such as the TensorFlow Embedding Projector and TensorBoard, a powerful feature of tSNE is that it reveals clusters of high-dimensional data points at different scales while requiring only minimal tuning of its parameters. Despite these advantages, the computational complexity of the tSNE algorithm limits its application to relatively small datasets. While several evolutions of tSNE have been developed to address this issue (mainly focusing on the scalability of the similarity computations between data points), they have so far not been enough to provide a truly interactive experience when visualizing the evolution of the tSNE embedding for large datasets.

In “Linear tSNE Optimization for the Web”, we present a novel approach to tSNE that heavily relies on modern graphics hardware. Given the linear complexity of the new approach, our method generates embeddings faster than comparable techniques and can even be executed on the client side in a web browser by leveraging GPU capabilities through WebGL. The combination of these two factors allows for real-time interactive visualization of large, high dimensional datasets. Furthermore, we are releasing this work as an open source library in the TensorFlow.js family in the hopes that the broader research community finds it useful.
Real-time evolution of the tSNE embedding for the complete MNIST dataset with our technique. The dataset contains images of 60,000 handwritten digits. You can find a live demo here.
The aim of tSNE is to cluster small “neighborhoods” of similar data points while also reducing the overall dimensionality of the data so it is more easily visualized. In other words, the tSNE objective function measures how well these neighborhoods of similar data are preserved in the 2 or 3-dimensional space, and arranges them into clusters accordingly.

In previous work, the minimization of the tSNE objective was performed as a N-body simulation problem, in which points are randomly placed in the embedding space and two different types of forces are applied on each point. Attractive forces bring the points closer to the points that are most similar in the high-dimensional space, while repulsive forces push them away from all the neighbors in the embedding.

While the attractive forces are acting on a small subset of points (i.e., similar neighbors), repulsive forces are in effect from all pairs of points. Due to this, tSNE requires significant computation and many iterations of the objective function, which limits the possible dataset size to just a few hundred data points. To improve over a brute force solution, the Barnes-Hut algorithm was used to approximate the repulsive forces and the gradient of the objective function. This allows scaling of the computation to tens of thousand data points, but it requires more than 15 minutes to compute the MNIST embedding in a C++ implementation.

In our paper, we propose a solution to this scaling problem by approximating the gradient of the objective function using textures that are generated in WebGL. Our technique draws a “repulsive field” at every minimization iteration using a three channel texture, with the 3 components treated as colors and drawn in the RGB channels. The repulsive field is obtained for every point to represent both the horizontal and vertical repulsive force created by the point, and a third component used for normalization. Intuitively, the normalization term ensures that the magnitude of the shifts matches the similarity measure in the high-dimensional space. In addition, the resolution of the texture is adaptively changed to keep the number of pixels drawn constant.
Rendering of the three functions used to approximate the repulsive effect created by a single point. In the above figure the repulsive forces show a point in a blue area is pushed to the left/bottom, while a point in the red area is pushed to the right/top while a point in the white region will not move.
The contribution of every point is then added on the GPU, resulting in a texture similar to those presented in the GIF below, that approximate the repulsive fields. This innovative repulsive field approach turns out to be much more GPU friendly than more commonly used calculation of point-to-point interactions. This is because repulsion for multiple points can be computed at once and in a very fast way in the GPU. In addition, we implemented the computation of the attraction between points in the GPU.
This animation shows the evolution of the tSNE embedding (upper left) and of the scalar fields used to approximate its gradient with normalization term (upper right), horizontal shift (bottom left) and vertical shift (bottom right).
We additionally revised the update of the embedding from an ad-hoc implementation to a series of standard tensor operations that are computed in TensorFlow.js, a JavaScript library to perform tensor computations in the web browser. Our approach, which is released as an open source library in the TensorFlow.js family, allows us to compute the evolution of the tSNE embedding entirely on the GPU while having better computational complexity.

With this implementation, what used to take 15 minutes to calculate (on the MNIST dataset) can now be visualized in real-time and in the web browser. Furthermore this allows real-time visualizations of much larger datasets, a feature that is particularly useful when deep neural output is analyzed. One main limitation of our work is that this technique currently only works for 2D embeddings. However, 2D visualizations are often preferred over 3D ones as they require more interaction to effectively understand cluster results.

Future Work
We believe that having a fast and interactive tSNE implementation that runs in the browser will empower developers of data analytics systems. We are particularly interested in exploring how our implementation can be used for the interpretation of deep neural networks. Additionally, our implementation shows how lateral thinking in using GPU computations (approximating the gradient using RGB texture) can be used to significantly speed up algorithmic computations. In the future we will be exploring how this kind of gradient approximation can be applied not only to speed-up other dimensionality reduction algorithms, but also to implement other N-body simulations in the web browser using TensorFlow.js.

Acknowledgements
We would like to thank Alexander Mordvintsev, Yannick Assogba, Matt Sharifi, Anna Vilanova, Elmar Eisemann, Nikhil Thorat, Daniel Smilkov, Martin Wattenberg, Fernanda Viegas, Alessio Bazzica, Boudewijn Lelieveldt, Thomas Höllt, Baldur van Lew, Julian Thijssen and Marvin Ritter.

Google Cloud announces the Beta of single tenant instances


One of the characteristics of cloud computing is that when you launch a virtual machine, it gets distributed wherever it makes the most sense for the cloud provider. That usually means sharing servers with other customers in what is known as a multi-tenant environment. But what about times when you want a physical server dedicated just to you?

To help meet those kinds of demands, Google announced the Beta of Google Compute Engine Sole-tenant nodes, which have been designed for use cases such a regulatory or compliance where you require full control of the underlying physical machine, and sharing is not desirable.

“Normally, VM instances run on physical hosts that may be shared by many customers. With sole-tenant nodes, you have the host all to yourself,” Google wrote in a blog post announcing the new offering.

Diagram: Google

Google has tried to be as flexible as possible, letting the customer choose exactly what configuration they want in terms CPU and memory. Customers can also let Google choose the dedicated server that’s best at any particular moment, or you can manually select the server if you want that level of control. In both cases, you will be assigned a dedicated machine.

If you want to play with this, there is a free tier and then various pricing tiers for a variety of computing requirements. Regardless of your choice, you will be charged on a per-second basis with a one-minute minimum charge, according to Google.

Since this feature is still in Beta, it’s worth noting that it is not covered under any SLA. Microsoft and Amazon have similar offerings.


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Women’s Safety XPRIZE $1M winner is a smart, simple panic button


Devices like smartphones ought to help people feel safer, but if you’re in real danger the last thing you want to do is pull out your phone, go to your recent contacts, and type out a message asking a friend for help. The Women’s Safety XPRIZE just awarded its $1 million prize to one of dozens of companies attempting to make a safety wearable that’s simple and affordable.

The official challenge was to create a device costing less than $40 that can “autonomously and inconspicuously trigger an emergency alert while transmitting information to a network of community responders, all within 90 seconds.”

Anu and Naveen Jain, the entrepreneurs who funded the competition, emphasized the international and very present danger of sexual assault in particular.

“Women’s safety is not just a third world problem; we face it every day in our own country and on our college campuses,” said Naveen Jain in the press release announcing the winner. “It’s not a red state problem or a blue state problem but a national problem.”

“Safety is a fundamental human right and shouldn’t be considered a luxury for women. It is the foundation in achieving gender equality,” added Anu Jain.

Out of dozens of teams that entered, five finalists were chosen in April: Artemis, Leaf Wearables, Nimb & SafeTrek, Saffron, and Soterra. All had some variation on a device that either detected or was manually activated during an attack or stressful situation, alerting friends to one’s location.

The winner was Leaf, which had the advantage of having already shipped a product along these lines, the Safer pendant. Like any other Bluetooth accessory, it keeps in touch with your smartphone wirelessly and when you press the button twice your emergency contacts are alerted to your location and need for help. It also records audio, possibly providing evidence later or a deterrent to harassers who might fear being identified.

It’s not that it’s an original idea — we’ve had various versions of this for some time, and even covered one of the other finalists last year. But they haven’t been quantitatively evaluated or given a platform like this.

“These devices were tested in many conditions by the judges to ensure that they will work in real-life cases where women face dangers today. They were tested in no-connectivity areas, on public transit, in basements of buildings, among other environments,” explained Anu Jain to TechCrunch. “Having the capability to record audio after sending the alert was one of the main differentiators for Leaf Wearables. Their chip design and software was also easy to be integrated into other accessories.”

Hopefully the million dollars and the visibility from winning the prize will help Leaf get its product out to people who need it. The runners up don’t seem likely to give up on the problem, either. And it seems like the devices will only get better and cheaper — not that this will change the world on its own.

“Prices will come down as the sensor prices drop. In many countries it will require community support to be built,” continued Jain. “These technologies can act as a deterrent but in the long term culture of violence again women must change.”


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SeatGeek brings ticket buying into Snapchat


You can now buy game and concert tickets from teams and musicians within Snapchat, thanks to an integration with SeatGeek.

While Snapchat has started testing e-commerce features in the past few months, SeatGeek says this is the first ticket-buying experience built into the Snapchat app.

The Los Angeles Football Club was the first team to sell tickets through this integration, by posting a Snapchat Story (and a Snapcode on the team website) that allowed users to swipe up to buy tickets to the May 26 game. The full purchase experience takes place without leaving the app.

“We’re always looking to reach our fans in innovative ways, and selling tickets directly to our followers on Snapchat gives us an incredible opportunity to connect with our most dedicated supporters,” said Los Angeles Football Club President and co-owner Tom Penn in the announcement.

SeatGeek Snapchat

SeatGeek co-founder Russ D’Souza said that as “the pipe gets solidified,” you’ll start seeing more Snapchat/SeatGeek ticket sales. He added that this the kind of integration he was hoping for when the company launched the SeatGeek Open platform a couple years ago, allowing teams, musicians and other rightsholders to sell tickets directly through SeatGeek. (The platform also supports ticket sales through Facebook.)

“For too long, the legacy ticketing approach has been to make it difficult for teams to sell tickets in lots of places,” D’Souza said. “Teams should want to sell their tickets in as many places as possible.”

And it sounds there are additional deals in the works: “What we’re excited about over the next few months is beating the drumbeat of openness with new partnerships … We want to drive the whole industry forward and create more tangible results that cause the industry to open up.”


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