fbpx

It’s a known fact that Google, along with other major tech players like Amazon, Apple, and Facebook, is increasingly trying to grab a slice of the $3 trillion dollar healthcare industry. Now, the search giant is flexing its cloud muscle to team up with healthcare providers to make further inroads.

To that effect, Google has announced a partnership with Ascension, the second-largest health system in the US, in a deal that gives it access to personal health datasets that can be used to develop AI-based tools for medical providers.

The collaboration — dubbed “Project Nightingale” — comes a week after the company’s acquisition of fitness wearable maker Fitbit for $2.1 billion. It also corroborates earlier reports that it’s working on a Google Flights-like search tool to make it easier for doctors to find medical records.

A data-sharing partnership

Interestingly, the partnership was mentioned in Google’s July earnings call, but it came under scrutiny only on Monday after the Wall Street Journal reported that Google would gain detailed personal health information of millions of Americans across 21 states.

The report also said the data involved in the project includes patient names, dates of birth, lab results, doctor diagnoses, and hospitalization records, along with their complete medical histories.

The partnership “covers the personal health records of around 50 million patients of Ascension,” the Journal wrote.

Google confirmed the deal, adding the arrangement adheres to HIPAA regulations regarding patient data and that it will meet the necessary privacy and security requirements.

As the Journal noted, HIPAA laws make it possible for hospitals to share data with its business partners without the consent of patients, provided said information is used only to help the entity meet its clinical functions.

Healthcare as a service

“Ascension’s data cannot be used for any other purpose than for providing these services we’re offering under the agreement, and patient data cannot and will not be combined with any Google consumer data,” Google said.

Ascension, for its part, said it aims to explore AI applications to help improve clinical quality and patient safety. It’s worth pointing out that the company is not paying Google for these services.

For the Mountain View company, the data-sharing project comes with another objective: design a searchable, cloud-based platform to query patient data, which it could then market to other healthcare providers.

The legality aside, it’s not fully clear why the sharing terms would include names and birthdates of patients. But this would also mean adequate safeguards are in place to anonymize the information before it could be used to develop machine learning models for personalized healthcare.

Health privacy concerns

This is far from the first time Google’s cloud division has gone after healthcare providers. It has similar relationships with a number of hospital networks, including Dr. Agarwal’s Eye Hospital, the Chilean Health Ministry, Mayo Clinic, and the American Cancer Society.

Still, the development is bound to raise concerns about health privacy, what with the Journal stating that 150 Google employees may have access to a significant portion of the medical data from Ascension.

That’s not all. The tech giant has been scrutinized for improperly sharing patient data in the name of AI research, and has drawn flak for merging Deepmind Health with Google despite the company’s earlier promises to keep its health initiatives separate.

Given this checkered history, it shouldn’t be much of a surprise if Google — and other big tech companies — grapple with the privacy and security implications associated with handling health information when they are already in possession of enormous amounts of data about their users.

Update on Nov. 13, 9:00 AM IST: Google’s data deal with Ascension is now being investigated by the Office for Civil Rights in the Department of Health and Human Services, the Wall Street Journal reported. The OCR said it “will seek to learn more information about this mass collection of individuals’ medical records to ensure that HIPAA protections were fully implemented.”

[Source: This article was published in thenextweb.com By RAVIE LAKSHMANAN - Uploaded by the Association Member: Jennifer Levin]

Categorized in Internet Privacy

Google Gravity:

Almost all of us use Google in our day to day life. Without Google we can imagine our life as easy as now.

But many times, we get bored with Google Home Page. So, if you want creative and funny Google Homepage, this article is for you.

If we compare Google with other Search Engines, we will notice that Google have number of interesting tricks which other Search Engines doesn’t have.

We will talk about the top 6 Google Magic Tricks which you can use in your spare time and amaze your friends with it as well.

Here are the Top 6 Funny Tricks of Google Gravity by which you can play with Google Home Page and make it more interesting:

1. Google Gravity


With this trick, you can move each and every element of your Google Homepage, with the help of mouse.

It is really amazing experience to play with Google Homepage.

To use this trick, you have to perform the following steps:

Step #1: Visit “www.google.com”.
Step #2: Inside Google Search box type “Google Gravity”.
Step #3: Click on “I’m Feeling Lucky”, instead of “Google Search”.
Step #4: Now that you are on the “Google Gravity” page, move your mouse and all the elements of the Google Homepage will start falling down. You can move every element of the Google Homepage with your mouse. 

2. Google Anti Gravity


Google Anti Gravity is the most funny trick in which every element of the Google Homepage start floating.

You can move every element of the Homepage like – button, search box with the help of mouse click. This is really amazing trick.

To use this trick, you have to perform the following steps:

Step #1: Visit “www.google.com”.
Step #2: Inside Google Search box type “Google Anti Gravity”.
Step #3: Click on “I’m Feeling Lucky”, instead of “Google Search”.
Step #4: Now that you are on the “Google Anti Gravity” page, you will notice that all the element are floating like – they are on the space. You can move every element of the Google Homepage with your mouse.

3. Google Zero Gravity


Google Zero Gravity is the trick which is similar to Google Gravity but unlike it, the element of the Google Homepage will be displayed in opposite manner, like – they are displayed in mirror.

To use this trick, you have to perform the following steps:

Step #1: Visit “www.google.com”.
Step #2: Inside Google Search box type “Google Zero Gravity”.
Step #3: Click on “I’m Feeling Lucky”, instead of “Google Search”.
Step #4: Now that you are on the “Google Zero Gravity” page, you will notice that all the element are in mirror position like – they are displayed on mirror and every element will start falling as well. You can move every element of the Google Homepage with your mouse.

4. Google Underwater


The Google Underwater trick will amaze you for sure.

In this trick, the Google Homepage will be floating on the sea water and you can generate the wave on to the water with the help of your mouse.

To make this trick work, you just have to do the following steps:

Step #1: Visit “www.google.com”.
Step #2: Inside Google Search box type “Google Underwater”.
Step #3: Click on “I’m Feeling Lucky”, instead of “Google Search”.
Step #4: Now that you are on the “Google Underwater” page, you will notice that all the element of Google Homepage are floating on the water. You can use your mouse to move every element of the Google Homepage.

5. Google Sphere


With this trick, you can play with Google Homepage in a really great and amazing way.

With the help of your mouse you can make each and every element of Google Homepage to revolve around Google Logo and make a sphere with it.

It is really fun to use this trick and you should definitely use it.

To perform this trick, you have to do the following steps:

Step #1: Visit “www.google.com”.
Step #2: Inside Google Search box type “Google Sphere”.
Step #3: Click on “I’m Feeling Lucky”, instead of “Google Search”.
Step #4: Now that you are on the “Google Sphere” page. When you will move your mouse, you will notice that every element of the Google Homepage will start revolving around Google Logo.

6. Google do a barrel roll


This is the trick which is not for Google Homepage but for Google index section, where we get the results for our query.

This is really amazing trick in which you can make a Google to do a barrel roll. So, you must try it.

All you have to do is just perform the following steps:

Step #1: Visit “www.google.com”.
Step #2: Inside Google Search box type “Google Anti Gravity”.
Step #3: Click on “I’m Feeling Lucky”, instead of “Google Search”.
Step #4: After this, you will see that Google is doing a barrel roll and it is really amazing to see that.

 

Hope, you like these funny trick on Google with Google Gravity, Google Anti Gravity and Google Zero Gravity.

[Source: This article was published in thecoderpedia.com By CoderPedia - Uploaded by the Association Member: Jennifer Levin]

Categorized in Search Engine

Google to offer users the option to auto-delete location history and web search data that it harvests

Google is to give users the choice of being able to automatically delete their search and location history after three months.

It announced the auto-delete tools for location history data, as well as web browsing and app activity, which will be rolled out in the coming weeks.

Last November Google was accused of misleading about location tracking after consumer groups from seven European nations asked their privacy regulators to take action against the search engine giant.

google logo mountainview 011

Location tracking

Consumer groups from the Netherlands, Poland, Czech Republic, Greece, Norway, Slovenia and Sweden, all filed GDPR complaints against Google’s location tracking.

They alleged that Google is tracking the movements of millions of users in breach of the European Union’s privacy laws.

Google, of course, is already facing a lawsuit in the United States for allegedly tracking phone users regardless of privacy settings.

That lawsuit was filed after an investigation by the Associated Press found that a number of Google services running on Android and Apple devices determine the user’s location and store it, even when Google’s “Location History” setting is switched off.

It should be remembered that Google had already allowed users to manually delete the data it harvests when they use its products such as YouTube, Maps and Search.

But now it trying to give users more control by offering auto-delete tools.

“And when you turn on settings like Location History or Web & App Activity, the data can make Google products more useful for you – like recommending a restaurant that you might enjoy, or helping you pick up where you left off on a previous search,” wrote David Monsees, product manager of search in a blog posting.

Auto-delete

“We work to keep your data private and secure, and we’ve heard your feedback that we need to provide simpler ways for you to manage or delete it,” Monsees added.

“You can already use your Google Account to access simply on/off controls for Location History and Web & App Activity, and if you choose – to delete all or part of that data manually,” he wrote. “In addition to these options, we’re announcing auto-delete controls that make it even easier to manage your data.”

Essentially, the user will give a time limit to choose for how long you want your data to be saved. This could be 3 months or 18 months.

Any data older than that will be automatically deleted from your account on an ongoing basis.

“These controls are coming first to Location History and Web & App Activity and will roll out in the coming weeks,” Monsees wrote. “You should always be able to manage your data in a way that works best for you–and we’re committed to giving you the best controls to make that happen.”

It should be noted that there will be no auto-delete of YouTube watch history or voice commands issued via Home and Assistant.

[Source: This article was published in silicon.co.uk By Tom Jowitt - Uploaded by the Association Member: James Gill]

Categorized in Search Engine

Ever had to search for something on Google, but you’re not exactly sure what it is, so you just use some language that vaguely implies it? Google’s about to make that a whole lot easier.

Google announced today it’s rolling out a new machine learning-based language understanding technique called Bidirectional Encoder Representations from Transformers, or BERT. BERT helps decipher your search queries based on the context of the language used, rather than individual words. According to Google, “when it comes to ranking results, BERT will help Search better understand one in 10 searches in the U.S. in English.”

Most of us know that Google usually responds to words, rather than to phrases — and Google’s aware of it, too. In the announcement, Pandu Nayak, Google’s VP of search, called this kind of searching “keyword-ese,” or “typing strings of words that they think we’ll understand, but aren’t actually how they’d naturally ask a question.” It’s amusing to see these kinds of searches — heck, Wired has made a whole cottage industry out of celebrities reacting to these keyword-ese queries in their “Autocomplete” video series” — but Nayak’s correct that this is not how most of us would naturally ask a question.

As you might expect, this subtle change might make some pretty big waves for potential searchers. Nayak said this “[represents] the biggest leap forward in the past five years, and one of the biggest leaps forward in the history of Search.” Google offered several examples of this in action, such as “Do estheticians stand a lot at work,” which apparently returned far more accurate search results.

I’m not sure if this is something most of us will notice — heck, I probably wouldn’t have noticed if I hadn’t read Google’s announcement, but it’ll sure make our lives a bit easier. The only reason I can see it not having a huge impact at first is that we’re now so used to keyword-ese, which is in some cases more economical to type. For example, I can search “What movie did William Powell and Jean Harlow star in together?” and get the correct result (Libeled Lady; not sure if that’s BERT’s doing or not), but I can also search “William Powell Jean Harlow movie” and get the exact same result.

BERT will only be applied to English-based searches in the US, but Google is apparently hoping to roll this out to more countries soon.

[Source: This article was published in thenextweb.com By RACHEL KASER - Uploaded by the Association Member: Dorothy Allen]

Categorized in Search Engine

The new language model can think in both directions, fingers crossed

Google has updated its search algorithms to tap into an AI language model that is better at understanding netizens' queries than previous systems.

Pandu Nayak, a Google fellow and vice president of search, announced this month that the Chocolate Factory has rolled out BERT, short for Bidirectional Encoder Representations from Transformers, for its most fundamental product: Google Search.

To pull all of this off, researchers at Google AI built a neural network known as a transformer. The architecture is suited to deal with sequences in data, making them ideal for dealing with language. To understand a sentence, you must look at all the words in it in a specific order. Unlike previous transformer models that only consider words in one direction – left to right – BERT is able to look back to consider the overall context of a sentence.

“BERT models can, therefore, consider the full context of a word by looking at the words that come before and after it—particularly useful for understanding the intent behind search queries,” Nayak said.

For example, below's what the previous Google Search and new BERT-powered search looks like when you query: “2019 brazil traveler to usa need a visa.”

2019 brazil

Left: The result returned for the old Google Search that incorrectly understands the query as a US traveler heading to Brazil. Right: The result returned for the new Google Search using BERT, which correctly identifies the search is for a Brazilian traveler going to the US. Image credit: Google.

BERT has a better grasp of the significance behind the word "to" in the new search. The old model returns results that show information for US citizens traveling to Brazil, instead of the other way around. It looks like BERT is a bit patchy, however, as a Google Search today still appears to give results as if it's American travelers looking to go to Brazil:

current google search

Current search result for the query: 2019 brazil traveler to USA need a visa. It still thinks the sentence means a US traveler going to Brazil

The Register asked Google about this, and a spokesperson told us... the screenshots were just a demo. Your mileage may vary.

"In terms of not seeing those exact examples, the side-by-sides we showed were from our evaluation process, and might not 100 percent mirror what you see live in Search," the PR team told us. "These were side-by-side examples from our evaluation process where we identified particular types of language understanding challenges where BERT was able to figure out the query better - they were largely illustrative.

"Search is dynamic, content on the web changes. So it's not necessarily going to have a predictable set of results for any query at any point in time. The web is constantly changing and we make a lot of updates to our algorithms throughout the year as well."

Nayak claimed BERT would improve 10 percent of all its searches. The biggest changes will be for longer queries, apparently, where sentences are peppered with prepositions like “for” or “to.”

“BERT will help Search better understand one in 10 searches in the US in English, and we’ll bring this to more languages and locales over time,” he said.

Google will run BERT on its custom Cloud TPU chips; it declined to disclose how many would be needed to power the model. The most powerful Cloud TPU option currently is the Cloud TPU v3 Pods, which contain 64 ASICs, each carrying performance of 420 teraflops and 128GB of high-bandwidth memory.

At the moment, BERT will work best for queries made in English. Google said it also works in two dozen countries for other languages, too, such as Korean, Hindi, and Portuguese for “featured snippets” of text. ®

[Source: This article was published in theregister.co.uk By Katyanna Quach - Uploaded by the Association Member: Anthony Frank]

Categorized in Search Engine

Google confirmed an update affecting local search results has now fully rolled out, a process that began in early November.

Screenshot 1

In what’s been called the November 2019 Local Search Update, Google is now applying neural matching to local search results. To explain neural matching, Google points to a tweet published earlier this year that describes it as a super-synonym system.

That means neural matching allows Google to better understand the meaning behind queries and match them to the most relevant local businesses – even if the keywords in the query are not specifically included in the business name and description.

“The use of neural matching means that Google can do a better job going beyond the exact words in business name or description to understand conceptually how it might be related to the words searchers use and their intents.”

In other words, some business listings might now be surfaced for queries they wouldn’t have shown up for prior to this update. Hopefully, that proves to be a good thing.

Google notes that, although the update has finished rolling out, local search results as they are displayed now are not set in stone by any means. Like regular web searches, results can change over time.

Google has not stated to what extent local search results will be impacted by this update, though it was confirmed this is a global launch across all countries and languages.

[Source: This article was published in searchenginejournal.com By Matt Southern - Uploaded by the Association Member: Jasper Solander]

Categorized in Search Engine

John Mueller from Google gave one of the clearest and easiest to understand explanations on how Google uses machine learning in web search. He basically said Google uses it for "specific problems" where automation and machine learning can help improve the outcome. The example he gave was with canonicalization and the example clears things up.

This is from the Google webmaster hangout starting at 37:47 mark. The example is this "So, for example, we use machine learning for canonicalization. So what that kind of means is we have all of those factors that we talked about before. And we give them individual weights. That's kind of the traditional way to do it. And we say well rel canonical has this much weight and redirect has this much weight and internal linking has this much weight. And the traditional approach would be to say well we will just make up those weights, at those numbers and see if it works out. And if we see that things don't work out we will tweak those numbers a little bit. And with machine learning what we can essentially do is say well this is the outcome that we want to have achieved and machine learning algorithms should figure out these weights on their own."

This was the first part of the answer around how Google debugs its search algorithm.

Here is the full transcript of this part.

The question:

Machine learning has been a part of Google search algorithm and I can imagine it's getting smarter every day. Do you as an employee with access to the secret files know the exact reason why pages rank better than others or is the algorithm now making decisions and evolving in a way that makes it impossible for humans to understand?

John's full answer:

We get this question every now and then and we're not allowed to could provide an answer because the machines are telling us not to talk about this topic. So it's I really can't answer. No just kidding.

It's something where we use machine learning in lots of ways to help us understand things better. But machine learning isn't just this one black box that does everything for you. Like you feed the internet in on one side the other side comes out search results. It's a tool for us. It's essentially a way of testing things out a lot faster and trying things out figuring out what the right solution there is.

So, for example, we use machine learning for canonicalization. So what that kind of means is we have all of those factors that we talked about before. And we give them individual weights. That's kind of the traditional way to do it. And we say well rel canonical has this much weight and redirect has this much weight and internal linking has this much weight. And the traditional approach would be to say well we will just make up those weights, at those numbers and see if it works out. And if we see that things don't work out we will tweak those numbers a little bit. And with machine learning what we can essentially do is say well this is the outcome that we want to have achieved and machine learning algorithms should figure out these weights on their own.

So it's not so much that machine learning does everything with canonicalization on its own but rather it has this well-defined problem. It's working out like what are these numbers that we should have there as weights and kind of repeatedly trying to relearn that system and understanding like on the web this is how people do it and this is where things go wrong and that's why we should choose these numbers.

So when it comes to debugging that. We still have those numbers, we still have those weights there. It's just that they're determined by machine learning algorithms. And if we see that things go wrong then we need to find a way like how could we tell the machine learning algorithm actually in this case we should have taken into account, I don't know phone numbers on a page more rather than just the pure content, to kind of separate like local versions for example. And that's something that we can do when we kind of train these algorithms.

So with all of this machine learning things, it's not that there's one black box and it just does everything and nobody knows why it does things. But rather we try to apply it to specific problems where it makes sense to automate things a little bit in a way that saves us time and that helps to pull out patterns that maybe we wouldn't have recognized manually if we looked at it.

Here is the video embed:

{youtube}5QxYWMEZT3A{/youtube}

Here is how Glenn Gabe summed it up on Twitter:

Glenn Gabe@glenngabe
Glenn Gabe@glenngabe

More from @johnmu: Machine learning helps us pull out patterns we might have missed. And for debugging, Google can see those weights which are determined by ML algos. If there is something that needs to be improved, Google can work to train the algorithms: https://www.youtube.com/watch?v=5QxYWMEZT3A&t=38m53s 

[Source: This article was published in seroundtable.com By Barry Schwartz - Uploaded by the Association Member: Robert Hensonw]

Categorized in Search Engine

Google has seemingly put the final nail in the coffin for Adobe Flash, the once-popular video and animation player that's become less relevant as newer web standards like HTML5 have taken over.

The company announced on Monday that its search engine will stop supporting Flash later this year, and that it will ignore Flash content in websites that contain it. The search engine will also stop indexing SWF files, the file format for media played through the Flash Player. Google noted that most users and websites won't see any impact from this change. 

The move has been a long time coming for Flash. Adobe announced in 2017 that it was planning to end-of-life Flash by ceasing to update and distribute it at the end of 2020, and Flash is already disabled in Chrome by default. When it made the announcement, Adobe said it was working with partners like Apple, Microsoft, Facebook, Google, and Mozilla to smoothly phase out Flash.

Flash was once a critical technology that enabled content creators to easily implement media, animations, and games  in their websites during the earlier days of the web. If you frequently played online games in your web browser in the early 2000s, you'll probably remember that Flash plugin was a necessity. 

But as new web standards like HTML5 and WebGL have risen in popularity, there became less of a need for Flash. Plus, as time went on, Flash became more prone to security concerns — including one vulnerability highlighted by security blog Naked Security which surfaced last year that would have made it possible for hackers to execute malicious code via a Flash file.

[Source: This article was published in businessinsider.com By Lisa Eadicicco - Uploaded by the Association Member: David J. Redcliff] 

Categorized in Search Engine

As always, when Google releases a new update to its search algorithm, it’s an exciting (and potentially scary) time for SEO. Google’s latest update, BERT, represents the biggest alteration to its search algorithm in the last five years.

So, what does BERT do?

Google says the BERT update means its search algorithm will have an easier time comprehending conversational nuances in a user’s query.

The best example of this is statements where prepositional words such as ‘to’ and ‘for’ inform the intent of the query.

BERT stands for Bidirectional Encoder Representations from Transformers, which is a language processing technique based on neural networking principles.

Google estimates the update will impact about 10% of United States-based queries and has revealed BERT can already be seen in action on featured snippets around the world.

How does Google BERT affect on-page SEO?

SEO practitioners can breathe a collective sigh of relief, because the Google BERT update is not designed to penalise websites, rather, only improve the way the search engine understands and interprets search queries.

However, because the search algorithm is better at understanding nuances in language, it means websites with higher-quality written content are going to be more discoverable.

Websites that have a lot of detailed ‘how-to’ guides and other in-depth content designed to benefit users are going to get the most from Google BERT. This means businesses who aren’t implementing a thorough content strategy are likely to fall behind the curve.

Basically, the BERT update follows Google’s long-running trend of trying to improve the ability of its search algorithm to accurately serve conversational search queries.

The ultimate result of this trend is users being able to perform detailed search queries with the Google voice assistant as if they were speaking to a real person.

Previous algorithm updates

While BERT may be the first major change to Google search in five years, it’s not the biggest shakeup in their history.

The prior Google PANDA and Google PENGUIN updates were both significant and caused a large number of websites to become penalised due to the use of SEO strategies that were considered ‘spammy’ or unfriendly to users.

PANDA

Google PANDA was developed in response to user complaints about ‘content farms’.

Basically, Google’s algorithm was rewarding quantity over quality, meaning there was a business incentive for websites to pump out lots of cheaply acquired content for the purposes of serving ads next to or even within them.

The PANDA update most noticeably affected link building or ‘article marketing’ strategies where low-quality content was published to content farms with a link to a business’ website attached to a keyword repeated throughout the article.

It meant that there was a significant push towards more ethical content marketing strategies, such as guest posting.

PENGUIN

Google PENGUIN is commonly seen as a follow up to the work started by PANDA, targeting spammy link-building practices and ‘black-hat’ SEO techniques.

This update was focused primarily on the way the algorithm evaluates the authority of links as well as the sincerity of their implementation in website content. Spammy or manipulative links now carried less weight. 

However, this meant that if another website posted a link to yours in a spammy or manipulative way, it would negatively affect your search rankings.

This meant that webmasters and SEO-focused businesses needed to make use of the disavow tool to inform Google what inbound links they approve of and which they don’t.

[Source: This article was published in smartcompany.com.au By LUCAS BIKOWSKI - Uploaded by the Association Member: Bridget Miller]

Categorized in Search Engine

Search-engine giant says one in 10 queries (and some advertisements) will see improved results from algorithm change

MOUNTAIN VIEW, Calif.—Google rarely talks about its secretive search algorithm. This week, the tech giant took a stab at transparency, unveiling changes that it says will surface more accurate and intelligent responses to hundreds of millions of queries each day.

Top Google executives, in a media briefing Thursday, said they had harnessed advanced machine learning and mathematical modeling to produce better answers for complex search entries that often confound its current algorithm. They characterized the changes—under a...

Read More...

[Source: This article was published in wsj.com By Rob Copeland - Uploaded by the Association Member: Jasper Solander] 

 
Categorized in Search Engine
Page 1 of 88

airs logo

Association of Internet Research Specialists is the world's leading community for the Internet Research Specialist and provide a Unified Platform that delivers, Education, Training and Certification for Online Research.

Get Exclusive Research Tips in Your Inbox

Receive Great tips via email, enter your email to Subscribe.

Follow Us on Social Media

Book Your Seat for Webinar - GET 70% OFF FOR MEMBERS ONLY      Register Now