Technews Update

Showing posts with label Education. Show all posts
Showing posts with label Education. Show all posts

Wednesday, 7 December 2016

How To Insert Adsense Ads INSIDE Blogger Posts ( Blogger/Blogspot)

How To Insert Adsense Ads INSIDE Blogger Posts ( Blogger/Blogspot)



One of the best sections to display your Google Adsense ads is INSIDE your blog post. So far, the Adsense block in my blog posts is one of the most performing on my blog.  In this post, I am sharing with you, how to add Adsense ad INSIDE your blog post.

Before you implement this trick, kindly BACK UP YOUR TEMPLATE first and I hope you already have an approved Adsense account. If you do not have one, Read: How To Register For Adsense Free of Charge.
Below is a snapshot from my account, showing my earnings so far within the 15 days in December 2010. Take a close look at the analysis in the picture and you will see that the "Postads" channel is making sense.  I created the "Postads" channel for the 300x280 Adsense ad inside my post. If you don't know about channels, you still have a lot to learn about Adsense then. I have 3 great ebooks that can help you asap, just for N1000. You can pay me via Liberty reserve or Paypal too. Contact me if interested.




So, lets get started.

STEP 1: Login to your Google Adsense account, and create a new ad.  Choose the 336x280 large Rectangle ad type. Then, copy the code into a Notepad.  Try and create a channel for the ad, if you know how to do it.

STEP 2: Before you can insert the adsense in your blog, you will need to "Parse" the code. Hence, we will need an html parser to do that. So, go to http://www.blogcrowds.com/resources/parse_html.php
At the page, you will see a box, paste your Adsense code into the box and click the "Parse" button. Copy the parsed code. You will need this parsed code in Step 3.

STEP 3:  Login to you Blogger dashboard and navigate to Design > Edit HTML and tick the small "Expand Widget Templates" box. Using "CTRL+F", search for the code <data:post.body/>  and paste the parsed code above, directly above  <data:post.body/>  and save the template.

That's all. View any of your blog post and you should now be seeing adsense ads showing in your post.

Remember, you can only see maximum of 3 Ad units on a page at a time. Hence, if you already displaying 3 ad units on your page, the fourth one will not display after adding this new one.

Advanced Customization

If you are as smart as me, then you can implement this advanced trick...lol. This trick will align the ad to the right of your blog post and also ensure that the ad only displays on post pages and not on the homepage.

Copy the code below into a notepad and replace the blue part with YOUR parsed adsense code in step 2 and then paste it in your blog as explained in step 3 above. If you do not replace it with your adsense code, that means you will be making money for me because the code in blue, is mine..


<b:if cond='data:blog.pageType == &quot;item&quot;'>
 <div style='float:right;padding:5px;'>
&lt;script async src=&quot;//pagead2.googlesyndication.com/pagead/js/adsbygoogle.js&quot;&gt;&lt;/script&gt;
&lt;!-- My ad 1 --&gt;
&lt;ins class=&quot;adsbygoogle&quot;
     style=&quot;display:block&quot;
     data-ad-client=&quot;ca-pub-6003519134122677&quot;
     data-ad-slot=&quot;6295783343&quot;
     data-ad-format=&quot;auto&quot;&gt;&lt;/ins&gt;
&lt;script&gt;
(adsbygoogle = window.adsbygoogle || []).push({});
&lt;/script&gt;

  </div>
</b:if>
That's all.

NOTE: You can change the float setting in the code above to center or left if you do not like been floated to the right.

I hope it works for you.

If it works for you, kindly use the comment form to share the link to your blog, so we can check it out. If you have problems to ask or want to make contributions, kindly use the comment form.

Wednesday, 6 July 2016

How to Send PDF, APK, ZIP or any other File in Whatsapp

How to Send PDF, APK, ZIP or any other File in Whatsapp

share pdf file in whatsapp
I have had many posts about Whatsapp in this blog till now. Whatsapp is the most popular messaging application in android as we already know. So i prefer writing more about Whatsapp because people are very interested about such topics. Even though whatsapp is the most popular messaging app, it has got some limitations. It’s quite natural because everything in this world is not perfect.

Some Limitations of Whatsapp Messenger

  • We cannot send large files through Whatsapp, it holds only 16MB of file.
  • We cannot send pdf files through whatsapp and it’s the most important document format.
  • We cannot send APK files through whatsapp
  • The quality of the image files we send through whatsapp is reduced by the server.
So these are some of the limitations of whatsapp and if the above the features are included in whatsapp, it will be a great boon. I have heard that many people asking on how to send pdf file in whatsapp? and Is there any feature available in whatsapp to send documents?
Today i’m here with a new post, that is how you can send pdf, apk, zip or any other files with any extension in whatsapp. This method can also be used to send large files upto 1 GB through whatsapp or any other instant messaging application you’ve got in your smart phone.
As i have told earlier whatsapp did not have any inbuilt feature to send this kind of files and we are going to depend an awesome android application that will definitely help us to send any files up to 1GB through Whatsapp.
WhatsTools Share
WhatsTools is the application we are going to use for this purpose.The main advantage of this app is that, the recipient is not required to install WhatsTools to receive the file. Anyone on Whatsapp can receive and download the file with ease.
Actually this app works with the help of cloud storage like Google Drive. The file which we want to share on whatsapp are actually uploaded to our Google Drive Storage so that no one else can have access to it. This file, which we uploaded to our Google Drive are being shared to Whatsapp with the help of WhatsTools Service. This adds more security to the service since it is incorporated with Google Cloud.
WhatsTools has got 4.6 rating in Play Store and you can guess the popularity of the app.

How to Send PDF, APK, ZIP or any other Files in Whatsapp

I’ll show you the working procedure to operate WhatsTools. Follow the steps and also the screenshots to get a better understanding of the process.
  • After installation, open the application then it will prompt you to enable background services for the app.
WHATSTOOLS-INTRO
  • Click OK to continue and enable WhatsTools Service.
Screenshot_2015-12-12-14-03-14
  • You will be redirected to the application. now click on the + Icon  in the WhatsTools app and choose your favorite file to share.
Screenshot_2015-12-12-14-03-50
  • After choosing the file it’ll be uploaded soon.
Screenshot_2015-12-12-14-03-42
  • Click on ‘Share’ after the file has been uploaded. Then you’ll be prompted to choose the method to share the file.
  • Choose Whatsapp Messenger from the list
Screenshot_2015-12-12-14-04-08
  • Select your favourite Whatsapp contact or group to share the file.
  • Yes, you have done it right. Now people can download the files you have just sent.
  • Now continue sharing as much as files you need without losing its clarity and perfection.

Features of WhatsTools: Share File Via IM

►Highlights◄
☆ Via WhatsApp: Click on Attach button in chat window to show Whats Tools share menu. Click on the received message to open Download file popup.(We need your permission to show our menu on the click of attach button using an accessibility service)
☆ Any File Type: Share any type of file Archives, Docs, EBooks, Music, Images, Gif Videos of up to 1 GB via any Instant messaging app installed in your phone.
☆ Up To 1GB: Many of the IM’s have restriction on size of file sending (16MB) whereas WhatsTools allows you to send files of up to 1 GB to any of your instant messaging app’s contact.
☆ Pausing/Resuming: Uploading and downloading can be paused as well as resumed. In case of a network failure, you will be able to resume the upload/download without losing the current progress.
☆ Preview video before downloading: Thumbnails of video at different durations can be previewed before downloading the actual video which will help you decide whether to download the video.
☆ Cross-Platform: Send file to IPhone, Windows Phone & Blackberry. If the receiver is on another platform, the link will be opened in the browser and the user can download file from the webpage.
☆ Share to Anywhere: File sharing is not limited to SMS or IM’s. You can copy the download link and share it anywhere through SMS, Email or Social Media Platforms. Anyone with the link can download the file from any platform using a browser.
☆ Peace of mind: All data is guarded behind HTTPS/SSL encryption. We connect to your Google Drive™ with your permission to transfer your files. You can view & manage these files from your Google™ drive as well.
☆ Inbuilt Media Support: WhatsTools support playing of GIF and Music files within the app itself. The app has inbuilt Video player as well for common video formats.
►Initial Setup◄
1. Enable Accessibility Service.
2. Connect to your Google™ Drive.
3. That’s it. Start sharing files.

Wednesday, 18 May 2016

The Pirate Bay loses its Main Domain Name in Court Battle

The Pirate Bay loses its Main Domain Name in Court Battle

The Pirate Bay loses its Main Domain Name in Court Battle
The Pirate Bay has fought many legal battles since its launch in 2003 to keep the website operational for the last 13 years.

However, this time The Pirate Bay is suffering a major blow after the Swedish Court ruled Thursday that it will take away the domain names 'ThePirateBay.se' and 'PirateBay.se' of the world's most popular torrent website and will hand over them to the state.

As its name suggests, The Pirate Bay is one of the most popular file-sharing torrent site predominantly used for downloading pirated or copyrighted media and programs free of charge.

Despite the criminal convictions, the torrent site remains functioning although it has moved to different Web domains several times.

However, this time, The Pirate Bay loses its main .SE domain, the world's 225th most popular website according to the Alexa ranking, according to Swedish newspaper DN.
"In common with the District Court ruling the Court of Appeal finds that there is a basis for confiscation since the domain names assisted crimes under the Copyright Act," a statement on the site of the Svea Court of Appeal reads. "This means that the right to the domain names falls to the state."
Back in 2013, the anti-piracy prosecutor Fredrik Ingblad took a different approach to shutting downthe file-sharing website.

Instead of suing the operators of the site or going after The Pirate Bay directly, the prosecutor decided to take two of its more popular domains from it and filed a complaint against Punkt SE (IIS), the company that manages .SE domain names.

The lawsuit filed against Punkt SE claimed that The Pirate Bay was an illegal torrent site and that all tools, including the domain names thepiratebay.se and piratebay.se, used in connection with the illegal site should be suspended.

Last year, the Stockholm District Court ruled in favor of the prosecution, saying that both ThePirateBay.se and PirateBay.se would be taken from the owners of The Pirate Bay.

Punkt SE then appealed and won the case and also awarded the body compensation of US$40,000 for legal costs.

As a result, the prosecution appealed, and now the decision came in the prosecution's favor, which means The Pirate Bay’s popular domains names are set to be forfeited to the Swedish state.

Both ThePirateBay.se and PirateBay.se are held in the name of The Pirate Bay co-founder Fredrik Neij, so the next step of the legal battle will now be against him.

Although there is still the possibility of another appeal, it is hard to say at this time whether both .SE domains of The Pirate Bay will still be active in the coming months.

Tuesday, 17 May 2016

How computer programming languages for kids have evolved and where they're going

How computer programming languages for kids have evolved and where they're going

With the President’s recent #CSforall initiative and an increasing focus on STEM, all signs point to the need to establish standards and best practices for teaching computer science to young children. The consensus in the industry is that the best way to introduce computer science and computational thinking to young children is through visual programming languages. Get rid of painstaking syntax to give kids flexibility and control of software at a young age.

Iterating on Logo

Over the last 50 years, designers have been making iterations on Seymour Papert’s Logo, resulting in an explosion of slightly different interfaces that teach the same core framework for thinking about programming. The current standard is block based programming, thanks to the popularity of MIT’s Scratch. In CSTA’s K-12 CS Standards, “constructing and testing solutions using block-based visual programming languages” is required for showing competency in programming for K-5.

Going Younger

Another trend in computer science education is trying to reach younger and younger audiences. Research shows that children as young as 5 can grasp computational thinking concepts, so why not go there? To teach children how to code before they know how to read, you need to get rid of text. Recent interfaces like Scratch Jr and Code.org’s Course 1 take block-based programming languages and replace the words with icons.

Introducing Robotics

There is something magical about seeing your code come to life. In the early 2000s, LEGO and MIT collaborated on a project that brought block-based programming into the real world. Students could write a program on a computer and then download it to a robot that they built. Early versions of the RIS (robotics invention system) looked almost exactly like Scratch.
The 2013 version of Lego Mindstorms has added complexity but largely works the same way as its predecessor. It adds input parameters to blocks that allow students to specify distances, time, outputs, and more.
Martin Exner created this handy infographic of programming interfaces inspired by Logo and more recently Scratch. Many of these derivatives of Logo have been designed around a specific use case - creating games, making 3D storytelling environments, drawing pictures, programming robots, and even controlling virtual fish tanks. While broad in their appeal to different types of kids, many children have difficulty going beyond learning how to build sequences of statements.

Thinking Beyond Logo

In the real world, computer programs usually consider a wide variety of inputs at the same time with dynamic if/else logic. Let’s take a simple scenario of Computing Wake Up. If it’s Saturday or Sunday, then we will go outside. If it’s Monday, we need to pack gym clothes. If it’s Thursday, we will take out the trash. Every weekday, we also need to go to school. Here’s how you would approach this problem through Scratch.
There is a new programming language for kids that takes a different approach from the standard block-based interfaces. In 2015, Wonder Workshop designed a new language called Wonder, a flow-based programming interface. Wonder allows students to focus on the connections between pre-described functional units (or states), building a state machine. The robot is in a single given state at any time; it's performing some task, and an input causes it to switch to doing something different.
This diagram shows how you would solve Computing Wake Up using a flow-based approach.
By escaping from the linear programming paradigm, this language provides a different approach to computational thinking that allows them to model responses to real-world stimuli in an easy-to-grasp way. Students can more easily take a problem, break it into smaller parts, and use those parts to solve the bigger problem. Students only need to to focus on one state at a time when solving the problem. This process, called decomposition, is a fundamental area of computer science that Wonder is specifically designed for.
There are many examples of robotics and state machines in our everyday lives, and they are only becoming more and more common. Vending machines give you food when the proper combination of coins is deposited. Self-driving cars know where to move based on obstacles around them. State machines can also be extended to model a large number of problems including language parsing, artificial intelligence, communication protocols, character development in games, and even neurological systems.
As applications of robotics become even more far-reaching, teachers are being trained on block-based programming as the standard for teaching computer science to young children. As it enters more and more classrooms, we should ask ourselves if this is the right direction to go in or if there is an appetite for other perspectives to early computer programming education.source: blockly, wonder

Friday, 13 May 2016

WhatsApp launches Desktop Software for Windows and Mac Users

WhatsApp launches Desktop Software for Windows and Mac Users

whatsapp-desktop-client
The most popular messaging app WhatsApp now has a fully functional desktop app – both for Macas well as Windows platform.

Facebook-owned WhatsApp messaging software has been a mobile-only messaging platform forever, but from Tuesday, the company is offering you its desktop application for both Windows and OS X.

Few months back, WhatsApp launched a Web client that can be run through your browser to use WhatsApp on your desktop, but now users running Windows 8 or Mac OS 10.9 and above can use the new desktop app that mirrors WhatsApp messages from a user's mobile device.

According to the company's blog post, the WhatsApp desktop app is similar to WhatsApp Web with synchronized conversations and messages

Since WhatsApp desktop app is native for both Windows and OS X platform, it can support desktop notifications and keyboard shortcuts.

WhatsApp has been rising at an extraordinary pace recently. The service has over 1 Billion monthly active users.

At the beginning of the year, the company removed its yearly $1 subscription fee. Just last month, the company rolled out end-to-end encryption for all its users' communication by default.

Here's how to Download WhatsApp Desktop Software:

WhatsApp launches Desktop Software for Windows and Mac Users
  1. Users running Windows 8 (or newer) or OS X 10.9 (or newer) can download WhatsApp desktop app available for direct downloading.
  2. Once Downloaded, open the WhatsApp desktop app.
  3. Scan the QR code with your mobile phone to Sync your device.
Now enjoy WhatsApping your friends and family straight from your desktop.

Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source

Announcing SyntaxNet: The World’s Most Accurate Parser Goes Open Source


At Google, we spend a lot of time thinking about how computer systems can read and understandhuman language in order to process it in intelligent ways. Today, we are excited to share the fruits of our research with the broader community by releasing SyntaxNet, an open-source neural network framework implemented in TensorFlow that provides a foundation for Natural Language Understanding (NLU) systems. Our release includes all the code needed to train new SyntaxNet models on your own data, as well as Parsey McParseface, an English parser that we have trained for you and that you can use to analyze English text.

Parsey McParseface is built on powerful machine learning algorithms that learn to analyze the linguistic structure of language, and that can explain the functional role of each word in a given sentence. Because Parsey McParseface is the most accurate such model in the world, we hope that it will be useful to developers and researchers interested in automatic extraction of information, translation, and other core applications of NLU. 

How does SyntaxNet work?

SyntaxNet is a framework for what’s known in academic circles as a syntactic parser, which is a key first component in many NLU systems. Given a sentence as input, it tags each word with a part-of-speech (POS) tag that describes the word's syntactic function, and it determines the syntactic relationships between words in the sentence, represented in the dependency parse tree. These syntactic relationships are directly related to the underlying meaning of the sentence in question. To take a very simple example, consider the following dependency tree for Alice saw Bob:


This structure encodes that Alice and Bob are nouns and saw is a verb. The main verb saw is the root of the sentence and Alice is the subject (nsubj) of saw, while Bob is its direct object (dobj). As expected, Parsey McParseface analyzes this sentence correctly, but also understands the following more complex example:


This structure again encodes the fact that Alice and Bob are the subject and object respectively ofsaw, in addition that Alice is modified by a relative clause with the verb reading, that saw is modified by the temporal modifier yesterday, and so on. The grammatical relationships encoded in dependency structures allow us to easily recover the answers to various questions, for examplewhom did Alice see?who saw Bob?what had Alice been reading about? or when did Alice see Bob?

Why is Parsing So Hard For Computers to Get Right?

One of the main problems that makes parsing so challenging is that human languages show remarkable levels of ambiguity. It is not uncommon for moderate length sentences - say 20 or 30 words in length - to have hundreds, thousands, or even tens of thousands of possible syntactic structures. A natural language parser must somehow search through all of these alternatives, and find the most plausible structure given the context. As a very simple example, the sentence Alice drove down the street in her car has at least two possible dependency parses:


The first corresponds to the (correct) interpretation where Alice is driving in her car; the second corresponds to the (absurd, but possible) interpretation where the street is located in her car. The ambiguity arises because the preposition in can either modify drove or street; this example is an instance of what is called prepositional phrase attachment ambiguity

Humans do a remarkable job of dealing with ambiguity, almost to the point where the problem is unnoticeable; the challenge is for computers to do the same. Multiple ambiguities such as these in longer sentences conspire to give a combinatorial explosion in the number of possible structures for a sentence. Usually the vast majority of these structures are wildly implausible, but are nevertheless possible and must be somehow discarded by a parser. 

SyntaxNet applies neural networks to the ambiguity problem. An input sentence is processed from left to right, with dependencies between words being incrementally added as each word in the sentence is considered. At each point in processing many decisions may be possible—due to ambiguity—and a neural network gives scores for competing decisions based on their plausibility. For this reason, it is very important to use beam search in the model. Instead of simply taking the first-best decision at each point, multiple partial hypotheses are kept at each step, with hypotheses only being discarded when there are several other higher-ranked hypotheses under consideration. An example of a left-to-right sequence of decisions that produces a simple parse is shown below for the sentence I booked a ticket to Google.
Furthermore, as described in our paper, it is critical to tightly integrate learning and search in order to achieve the highest prediction accuracy. Parsey McParseface and other SyntaxNet models are some of the most complex networks that we have trained with the TensorFlow framework at Google. Given some data from the Google supported Universal Treebanks project, you can train a parsing model on your own machine.

So How Accurate is Parsey McParseface?

On a standard benchmark consisting of randomly drawn English newswire sentences (the 20 year old Penn Treebank), Parsey McParseface recovers individual dependencies between words with over 94% accuracy, beating our own previous state-of-the-art results, which were already better than any previous approach. While there are no explicit studies in the literature about human performance, we know from our in-house annotation projects that linguists trained for this task agree in 96-97% of the cases. This suggests that we are approaching human performance—but only on well-formed text. Sentences drawn from the web are a lot harder to analyze, as we learned from the Google WebTreebank (released in 2011). Parsey McParseface achieves just over 90% of parse accuracy on this dataset. 

While the accuracy is not perfect, it’s certainly high enough to be useful in many applications. The major source of errors at this point are examples such as the prepositional phrase attachment ambiguity described above, which require real world knowledge (e.g. that a street is not likely to be located in a car) and deep contextual reasoning. Machine learning (and in particular, neural networks) have made significant progress in resolving these ambiguities. But our work is still cut out for us: we would like to develop methods that can learn world knowledge and enable equal understanding of natural language across all languages and contexts.

To get started, see the SyntaxNet code and download the Parsey McParseface parser model. Happy parsing from the main developers, Chris Alberti, David Weiss, Daniel Andor, Michael Collins & Slav Petrov.

Monday, 9 May 2016

Autonomous Robot Surgeon Bests Humans in World First

Autonomous Robot Surgeon Bests Humans in World First


Gif: Sheikh Zayed Institute for Pediatric Surgical Innovation
The smart surgical bot planned and performed the operation, although supervising humans occasionally reached in to help.

In a robotic surgery breakthrough, a bot stitched up a pig’s small intestines using its own vision, tools, and intelligence to carry out the procedure. What’s more, the Smart Tissue Autonomous Robot (STAR) did a better job on the operation than human surgeons who were given the same task.
STAR’s inventors don’t claim that robots can replace humans in the operating room anytime soon. Instead they see the accomplishment as a proof of concept—both for the specific technologies used and for the general concept of “supervised autonomy” in the OR.
Pediatric surgeon Peter Kim, one of the researchers, didn’t sound threatened when he spoke to reporters in a press call yesterday. “Even though we surgeons take pride in our craft at doing procedures, to have a machine that works with us to improve outcomes and safety would be a tremendous benefit,” he said.
For this study, published today in the journal Science Translational Medicine, researchers programmed their robot to carry out a procedure called intestinalanastomosis, in which a piece of intestine that’s been cut through is stitched back together. It’s like repairing a garden hose, said Ryan Decker, the senior engineer on the team, in that the sutures must be tight and regularly spaced to prevent leaks. STAR performed this task both on ex vivo tissue in the lab and on in vivo tissue in an anesthetized pig, and experienced human surgeons were given the same tasks. When the resulting sutures were compared, STAR’s stitches were more consistent and more resistant to leaks.  
The robot did have a little help. In about 40 percent of its trials, the researchers intervened to offer guidance of some sort—as in the GIF above, where a human hand is seen holding the thread. In the other 60 percent of trials, STAR did the job completely on its own. 
The researchers don’t think these assists invalidate their claim of autonomy; instead they see the setup as representative of shared control setups that would be appropriate for real ORs. Human surgeons could supervise procedures or even trade off tasks with the robot, letting the machine do more routine or tedious parts of an operation. “You can imagine that if something critical is happening, that would be a point where the surgeon is going to be closely monitoring the robot,” Decker said. “I’m sure they wouldn’t feel comfortable just letting it run and going to take a coffee break.” 
img
Today, some surgical procedures already incorporate smart machines. Robots routinely carry out the crucial steps in some procedures including orthopedicknee replacementsLasik eye surgery, and hair transplants. What these types of surgery have in common, though, is the fixed nature of their targets, as leg bones, eyes, and heads can be held in place during the procedure. Soft tissue surgeries are much messier and more difficult to automate, because all the slippery pink parts of the body shift around and are hard to track. 
The current state-of-the-art robot for soft tissue surgery is the da Vinci systemfrom Intuitive Surgical, but it’s not automated at all. The da Vinci is a teleoperated system, in which the surgeon sits at a console and manipulates controls in dexterous maneuvers that are mimicked by tiny tools inside the patient’s body. 
STAR solved the soft tissue challenge by integrating a few different technologies. Its vision system relied on near-infrared fluorescent (NIRF) tags placed in the intestinal tissue; a specialized NIRF camera tracked those markers while a 3D camera recorded images of the entire surgical field. Combining all this data allowed STAR to keep its focus on its target. The robot made its own plan for the suturing job, and it adjusted that plan as tissues moved during the operation. 
The researchers trained STAR only on how to perform this particular intestinal suturing procedure. “We programmed the best surgeon’s techniques, based on consensus and physics, into the machine,” Kim said. 
An outside expert in the field of surgical robotics called this study a breakthrough, but also said its limitations show that autonomous robots “will not come to the OR soon.” Blake Hannaford, a pioneer of autonomous surgical robotics at the University of Washington, noted that the NIRF tags that the robot relied on were placed by humans.
Hannaford also questioned the clinical significance of the task that STAR performed. “While in a technical sense, semi-autonomous suturing is a ‘grand challenge’ problem of surgical robotics, clinically much suturing and bowel anastomosis is done by staplers which can do the whole thing in seconds,” he wrote in an email. “Clearly the task they chose does not justify the elaborate equipment they used.”    
The STAR team said this task was simply intended as proof that autonomous robots could meet the challenge of soft tissue surgery. While the robot may not be ready to take over the OR, Kim said he hopes his technology will be integrated into commercial devices in the next few years. If robotic systems are shown to improve safety and patient outcomes, he said, medicine may go the way of the auto industry. 
“Now driverless cars are coming into our lives,” Kim said. “It started with self-parking, then a technology that tells you not to go into the wrong lane. Soon you have a car that can drive by itself.” Similarly, he said, surgical robots could start by giving human surgeons a helping hand. And maybe one day they’ll take over. 

High-Severity OpenSSL Vulnerability allows Hackers to Decrypt HTTPS Traffic