People search websites are used by people all around the world who want to check the details of any relative person. The prime reason to search for people using any search engine is to get prolonged data about their personal life, their jobs, identity, and background history.

These people finder services simply ask you for your target's name, phone number, or email address to find his information regarding any matter. These applications provide the data as they are linked with different national and international databases. These databases show the public records, criminal history, and national registration of individuals.

This review will list 10 best people search websites that provide authentic and factual data of the target person without him knowing.

  • Instant Checkmate - Well-featured Service providing Distinctive People's Information

  • CocoFinder - Huge Database providing in-depth Person's Data

  • TruthFinder - Multiple People Search Options with Accuracy

  • Intelius - Affordable and Accurate People Connector

Part 1: Instant Checkmate

Instant Checkmate is a people-finder website that uses any name, phone number, email address, or home address of any person to provide his data. However, the application takes a lot of time while displaying the results and shows many warnings. The data displayed through people's search has a long list. View this Instant Checkmate review post to get more about it. 

It shows the birthday of the target, including the day, date, and year with accuracy. If the target has any crime registered on his name, the search engine would also show it. The Instant Checkmate can also be used to find lost friends and family members that only require you to enter the name of the target. The locations of the target and his living area are also visible to the user.


The past and current living places with accurate addresses are also shown by the application. If the target has any court record, arrest history, or crimes registered on him, the application would also show it.

You can enter any email address and find out the details of the sender. If he is a scammer or has any association with a fake organization, the user would get instant details about his business. Hence, the application can save people from getting bullied or scammed.

Connect with People through Instant Checkmate!

Part 2: CocoFinder

CocoFinder provides the details of target by people search, reverse phone lookup, and white pages. The reverse phone lookup of the target requires a target's phone number and exhibits the required information. It can provide financial dues, loans, court proceedings, credit/debit card details, and job information of the target.


The application shows the social media applications such as Facebook, Instagram, Twitter, and LinkedIn accounts of the target. It displays the alternative phone numbers and email addresses of the target as well. If he has any business associated with his phone number, CocoFinder would also show the business details by its reverse phone lookup service.

The white pages resemble the phonebook of old times where phone numbers of people, along with their names and address, were written. The white pages require you to type the name, and it will automatically show the number of that person.

The application shows the identity of the target just like providing a complete background check, such as his complete name, phone numbers, relatives, families, and employment history. Moreover, every information available on target's social media accounts are also accessible through CocoFinder. If he has written his schools, college, university, then the user will also get to know about them.

With the help of CocoFinder, you can easily see the whole biography of the target by just typing his name or phone number in the search bar.

Run the People Search Service of CocoFinder Now

Part 3: TruthFinder

TruthFinder is an application used by investigators or organizations to reveal the truth about any person. This truth can be associated with their identity or business matters. The application requires you to enter the phone number of the target with accuracy. Then, the application would show the business information of the target, such as the nature and the date of the beginning of a business.

The software is interlinked with public search engines, and hence, it never fails to display information of the target from a 15 years old data record. If the target has any criminal history, the application will show the crime he committed and the punishment given to him.


It has an easy-to-use interface that shows the menu in sequential form so anybody can go through the software and learn the functioning. When you enter the name of the target person, it will show the full report of that person regarding his name, address, social accounts, business, and educational details. For more details, you can check this review post. 

The background check is also available on TruthFinder that reveals the background history of the target involving his criminal record, felonies, registration on the dark web, and court proceedings. The data displayed has a sequential manner and complete and accurate details.

Part 4: Intelius

With Intelius, you can check the details of the target, such as his background, friends, relatives, age, date of birth, and complete name of the target. Intelius displays the complete report of the person, including his identity information.

One can also search the details of the property he wants to buy by entering the complete address of the property in Intelius's search bar. The home address lookup exhibits the details of tenants living there, such as their names, phone numbers, sex-offending history, and employment details. Hence, the user can find out information about past and current tenants by entering their address.


This is also a way to find people's information. You can enter their home address if you don't have access to their name or phone number. The property details of the target property include home value, sales history, selling value, latitudes, and neighborhood history. Read the Intelius review post to know more about it. 

If you have any email address that sends you emails regarding job opportunities or claims that you have won any prize or lottery. You want to check the credibility of that mail. The email address lookup lets the user enter a certain email and shows the credibility of the sender and his complete identity.

The application has a handy dashboard that displays the revealed information with accuracy.

Do Accurate Person Search from Intelius Website. 

Part 5: AnyWho

AnyWho provides services by requiring the target's name, phone numbers, and business. The application has a yellow pages service. This service requires the business name or category and location of the situated business. After the user enters the name of the business, the application starts searching for the business details in the database and search engines.

You can find video profiles and online reservations, basic details and maps, and coupons. The people search service requires the user to enter the first name, last name, and state where the relative person lives in.


The application helps to find the location of people. Through this service, you can get to know where the target lives and his social media accounts. Social media accounts can help to know a lot about the target, such as his photos, videos, friends, and job places throughout his life. If he has any felonies, bankruptcies, lawsuits registered, they would also be visible.

Part 6: Pipl

Pipl is especially used by customers to check the credibility of any business organization. They let you add the details of any business and find the background of the business and people that work in the company. It is basically used to prevent e-commerce fraud and theft. One can check the business and the reliability before any agreement or deal.


Furthermore, it has a loan verification policy. By this policy, one can enter the details of the person who wants the loan. The application would check his identity, his job details, and financial status. After this, the software would confirm if the relative person is worthy of a loan or not.

It is mainly used-up to confirm credibility and check the resources. The application also tends to reveal the complete identity, phone number, email address, and social media handles of the target person. One can gather, connect people and relatives by using this application. It provides social, professional, and personal information.

Part 7: ZabaSearch

ZabaSearch has white pages that require the user to enter the name and state of the target person. The application would show his background information and employment details. Moreover, one can also check the information of the target person by adding his phone number in the search bar.

The advanced search helps you to know the name, address, and social media handles of a specific person. It also accesses the age and alternative phone numbers of people. One can emphasize finding the factual data of his employees, spouses, or anyone by entering his name or phone number.


If you upgrade the search by adding the background check in the ZabaSearch, you will get the background history such as marriages, divorce records, harassment cases, and court proceedings. The background check service identifies the complete background of the target and publishes the report within a few minutes.

To get started, you only need to enter the name or phone number of the target and hit the 'Search' button.

Part 8: BlackBookOnline

BlackBookOnline offers an asset locator that requires people to enter any name, and it would access the assets registered on his name. The bank locator service allows you to enter any credit card number or any other account number and displays the bank name.

The death record service helps people to know who died and has a public record. This application lets people confirm the death of their old friend or relative. The criminal record of BlackBookOnline requires the user to enter any name in order to exhibit the crime details of that person.

It is also an essential application in finding the marriage record, divorces, off-springs, spouses, and siblings of the target person. If the relative person has any registration on dating websites, the software would also show it.

The motorcycle service helps people to enter the number of any motorcycle, and the application would access and show the owner of the vehicle. This helps to control theft and misplacement of vehicles.

Part 9: That'sThem

That'sThem offers reverse phone lookup, IP search, address search, and VIN search to the user interface. The address lookup service asks the user to enter the complete address of any property, and it would display the owner of that property. The application also shows the household contact information, selling value, worth, and area of the home.

The VIN search is a service that provides information about any vehicle, such as a car, motorcycle, or van. It only requires you to enter the number written on the nameplate of the vehicle. The application would start searching its manufacturing year, company name, and the owner of the vehicle.

The IP search finds the geographical details about any IP address. The user has to enter the IP address, and the search will begin. It provides the most accurate and factual IP data available.

The reverse email search requires the email of the target to carry the search. The results of the search would show the name, number, address, and social media profiles of the email sender.

Part 10: Zlookup

Zlookup is a reverse phone lookup application mainly built to access people through their phone numbers. It requires people to enter the phone number of the target person and carries the search within a few seconds. The application is linked with huge databases that spy on the oldest information with accuracy.

Zlookup is especially interlinked with every country in the world. You need to select a particular country where you want to run the reverse phone lookup. The application has the authority to show identity through the phone number. The identity includes the name and age of the person, his education, workplaces, and social accounts.

If he has any fraud case registered in his name or has gone through any punishment, the application displays its details. This helps people to know about the history of suspicious people by entering their phone numbers. By the Zlookup, one can know who called them and who keeps on calling them with different numbers.


The article concludes a list of 10 best websites to find people that are used to provide factual information on the target. The search is carried when the user enters any data such as name, phone number, or email address. These applications find out data with accuracy. The information includes the criminal background, information about vehicles, death records, and IP address.

This is an important and vital way to find people through their names or phone number. This secures people from getting scammed by fake people. If you are being disgusted by calls and messages, the people finder sites allow you to enter the phone number and get to know the name and address of the caller.

[Source: This article was published in techtimes.com By Staff Reporter - Uploaded by the Association Member: Alex Gray]
Categorized in Search Engine

With Google threatening to pull out of Australia, the founder of a search engine that plants trees when people search believes his platform can help fill this potential void as an ethical alternative.

Ecosia is a search engine based in Germany that uses ad revenue from searches to fund reforestation projects around the world.

The social business was founded by Christian Kroll in 2009 and has so far helped plant more than 119 million trees.

Kroll told Pro Bono News he first became interested in social business models when he was travelling through Nepal and tried starting a search engine that would finance development projects. 

While this was unsuccessful, he said he learnt a lot and it helped renew his focus on using tech for good. 

“After Nepal I travelled through South America, where I saw the devastation caused by massive deforestation and learnt the critical role of trees in reducing carbon, combating hunger and poverty, and restoring biodiversity,” Kroll said.

“When I returned to Berlin in 2009, I started Ecosia with my sister and a couple of friends. We knew from the start that we wanted to put our profits into ecological conservation projects and tree-planting was a natural choice.” 

Today, Ecosia – which uses Bing’s search technology – has around 15 million active users.

In Australia, it makes up just 0.22 per cent of the search engine market.

Google meanwhile holds more than 94 per cent of the market share.

But with the company threatening to pull out of the Australian market due to proposed media bargaining code laws, Kroll believes Ecosia could help fill the search engine void.

“Ecosia already has a strong base in Australia – we’re seeing over 7 million searches made on Ecosia by Australians each month, and users is up 30 per cent year-on-year,” he said.

“[But] there’s still plenty of room to grow. If a large number of [internet] users switched over, it would make a huge difference to the number of trees we’d be able to plant.

“It’s now in the hands of ordinary Australians who can help plant change through their everyday internet searches.”    

Ecosia was the first German company to become a B Corporation and has consistently been rated among the top-performing B Corps in the world.

Kroll said meeting the highest standards of verified social impact performance was incredibly important given Ecosia’s mission to centre people before profit.

He said transparency was central to this, noting that Ecosia has been publishing its financial reports since 2014 to keep it accountable to users.

“Social impact is a thread that runs through everything we do,” he said.

“Whether it’s releasing a new product, considering green investments, or sharing content on our platforms, we aim to cultivate a more environmentally, economically, and socially sustainable world.” 

Ecosia funded the planting of 26,000 trees in the Byron Bay region last year with local partner ReForest Now and has just signed a contract to double this figure.

Kroll said Ecosia was more than 350 per cent renewable in 2020, producing enough renewable energy through the seven solar power plants it has built to power its searches and help to push dirty energy out of the grid.

He also said the company has strong privacy protections.

“We’re privacy-friendly, searches are never stored permanently, no personal profiles are created based on search history, and all searches are securely encrypted and anonymised within days,” he said. 

“Ecosia also never uses external tracking tools and never sells data to advertisers.

“Hopefully that’s enough to convince all Australians to use Ecosia and help us to regenerate the planet.”

[Source: This article was published in probonoaustralia.com.au By Luke Michael - Uploaded by the Association Member: David J. Redcliff]
Categorized in Search Engine

This may form part of the social media guidelines currently underway by the IT Ministry and could be out soon.

Social media platforms such as Facebook, WhatsApp, Instagram, Twitter, and TikTok may have to scramble for developing an account identity-verification option to check "fake news, malicious content, misinformation, racial slurs, gender abuse that may have an impact on the individual and society as a whole." This may form part of the social media guidelines currently underway by the IT Ministry and could be out soon. "The work is in progress, we have sent it to the Law Ministry for vetting," said a source.

The IT Ministry is learned to have finalized the social media guidelines to check misinformation, malicious info, and gender-biased views and have sent them to the Law Ministry for vetting it where account holder verification could be made mandatory.

The new draft personal data protection Bill has proposed social media intermediaries to enable "voluntary verification" of user accounts. The method for this, as suggested in the bill, is that these verified users should be given a demonstrable and visible mark of verification which is akin to biometric or physical identification which is publicly visible to all users.

If this is implemented, then this verification system would be different from the existing verified accounts category on platforms such as Instagram and Twitter.

The security check user account verification will be developed by the social media company.

Another major change that may come up is in the definition of the "significant data fiduciary" based on the volume of personal data they possess because there is a feeling that big or small, any incorrect or fake information through even a small social media platform has the potential to multiply the fake news irrespective of the volume of personal data it holds.

Therefore, there may be another layer included for those social media companies who don't have volumes of personal data, but they can affect the democratic nature of the country.

Under Section 26 of the 2019 Bill, certain thresholds in terms of volume of personal data processed, the sensitivity of personal data processed, risk of harm, etc are specified, upon satisfaction of which, the Data Protection Authority may notify a data fiduciary as a "significant data fiduciary" (social media companies).

This provision in the data privacy Bill is only applicable to "significant" social media platforms. The significant status of a company is determined by the Central government on the basis of the number of users and the potential impact that these companies can have on Indian democracy and the country's security and general harmony. But this may change, said sources.

A social media intermediary has been defined as a body that primarily or solely enables online interaction between two or more users and allows them to create, upload, share, disseminate, modify or access information using its services.

Earlier, there was a proposal to link social media accounts with Aadhaar to trail the real source of fake news, but the nodal agency for UIDAI shot down the proposal, saying Aadhaar is meant for the distribution of government welfare benefits not catching culprits which is a policing job.

IT Minister Ravi Shankar Prasad later said there is no proposal to link social media accounts of individuals to Aadhaar.

With the rise in fake news and hate speeches online, the need for verification of social media accounts has been felt for a while. This became even more pronounced following a series of lynching incidents over religious issues. Earlier this year, Facebook reported taking down 2.19 billion fake accounts in the first quarter of 2019, a significant hike from 1.2 bn accounts in Q4 of 2018.

[Source: This article was published in gadgets.ndtv.com  - Uploaded by the Association Member: James Gill]

Categorized in Internet Privacy

Sometime in late 2019, I became increasingly more concerned with personal privacy. I’ve never been the type of person to lean into sharing details with companies when I didn’t need to, but I became aware of the ways I was “leaking” data to companies. One of the easiest things I did to help curtail some of the data I was sharing was changing my default web search to DuckDuckGo, and after a year of using it, I wanted to share some of my thoughts on it.

Table of contents

  • Google is better, but I still use DuckDuckGo
  • DuckDuckGo is using Bing results with extra data added
  • Changing your default is easy
  • Google isn’t selling your data
  • Should Apple buy DuckDuckGo?
  • Wrap up on DuckDuckGo as my default search

Google is better, but I still use DuckDuckGo

One of the opinions I’ve heard from others about switching to DuckDuckGo is that they believe Google provides better search results. I agree with them, but that hasn’t changed my opinion. Google is the best search engine globally, and there is no changing that fact. Just because it’s the best doesn’t mean it’s good to use. Facebook is the best way to stay connected to people, but I still don’t want to use it.

If you want the best search results, then use Google. If you want excellent search results that aren’t used to target you with better ads, use DuckDuckGo. For me, I’ve decided that protecting my privacy is a worthy trade-off for slightly worse search results. I still generally find what I am looking for when searching.

DuckDuckGo is using Bing results with extra data added

DuckDuckGo isn’t crawling the web in the same way that Google crawls it. Yes, they do have some crawlers, but they use a host of data they pull together in such a way where you aren’t tracked by it. Some of the search results are pulled in from Bing, while others are populated from Apple Maps, Wikipedia, Wolfram Alpha, etc. It’s estimated that they use over 400 sources in total to populate their data. I personally like this approach of sourcing data from multiple places in order to provide better results.

I particularly like the integration with Apple Maps on iPhone as I can quickly search for a place and then launch the directions in Apple Maps. Google Search obviously integrates with Google Maps, and that’s yet another service I’ve chosen not to use.

Although DuckDuckGo has sponsored search results, they aren’t based on targeted data they know about you. On top of that, Google’s search results have, in my use, started showing increasingly more ads above the organic results, so it’s become even harder to use. DuckDuckGo lets me quickly find what I need.

Changing your default is easy

While Apple still ships Google as the default browser search engine, it’s straightforward to switch to DuckDuckGo as your default. On the Mac, there is a tab in your preferences for default search in Safari.

Changing your default is easy

On iOS, go to Setting > Safari > Search Engine, and you’ll see the option to switch to DuckDuckGo.

DuckDuckGo 1

Now, all of your Safari searches will be routed through DDG instead of Google. I have the DuckDuckGo homepage set as my default homepage on the Mac as it loads super fast with only a search window.

Google isn’t selling your data

A common misconception with Google (and Facebook) is that they collect all of this information and then “sell” it to other companies. The truth is your data is so valuable that they want to be the only ones that have it. They sell access to your data by letting companies advertise to use in a targeted way based on the data Google and Facebook knows about you. For some people, that’s a fair trade. They love Facebook and Google’s services enough that they’re willing to trade that data for access to free services.

I was willing to do that for a long time, but today, I am not. I’ve personally been off of Facebook since 2009 and Instagram from 2016. I use iCloud for my personal email. I’ve started using ‘Sign in with Apple’ whenever possible when signing up for new services. When I am on Wi-Fi networks that I don’t manage, I use a VPN service to protect my privacy. I want to use services that aren’t interesting in knowing who I am in order to better target me with ads.

Should Apple buy DuckDuckGo?

I’ve seen this comment floated around the tech community for years, and while it’s an excellent idea, I don’t think it’s needed. DuckDuckGo’s mission aligns nicely with Apple’s mission of protecting personal privacy. Apple should be making more aggressive moves to teach its users about your search history, though.

Apple’s problem is they make billions each year from Google from being the default search provider. I don’t think Apple should change the default, not for privacy reasons, but from a user experience reason. If Apple set DDG as the default search provider in iOS 15, it would create chaos for Apple Support as people would be confused about what was happening. What Apple should do is when Safari is launched for the first time, asking users which search engine they want to use. Under the icon for DDG, there should be a mention that they don’t track you, store identifiable information, etc. Doing this would undoubtedly cause many people to switch, but they would be choosing to change so they’d understand the experience.

Wrap up on DuckDuckGo as my default search

I didn’t think to write this article until recently as I’ve become so used to having DuckDuckGo as my provider that it stopped seeming different. In my head, I replaced one search engine for another. In reality, I traded a search engine that wants to know more about me to one that actively works to avoid knowing anything about me.

The older I get, the more I turn into Ron Swanson from Parks and Rec in terms of privacy. The right to privacy is something I place more importance on as the years go by. The more we rely on technology to power our lives, the easier it is for companies to think they have the right to know as much about us as possible. Changing your default search engine to DuckDuckGo is an easy first step to taking back your privacy. Give it a shot for 30 days to see how easy is it to take back a small part of your privacy.

 [Source: This article was published in 9to5mac.com By Bradley Chambers - Uploaded by the Association Member: Eric Beaudoin]
Categorized in Search Engine

One of the recent issues that have emerged within the field of artificial intelligence (AI) is that of bias in computer vision. Many experts are now discovering bias within AI systems, leading to skewed results in various different applications, such as courtroom sentencing programs.

There is a large effort going forward attempting to fix some of these issues, with the newest development coming from Princeton University. Researchers at the institution have created a new tool that is able to flag potential biases in images that are used to train AI systems.

The work was presented on Aug. 24 at the virtual European Conference on Computer Vision. 

Bias in AI Systems

One of the major reasons for the bias present in current AI systems is that they are often trained on large sets of images coming from online sources. These images can be stereotypical, and when they go toward developing computer vision, the result can be unintentionally influenced by models. Computer vision is what enables computers to identify people, objects, and actions. 

The tool that was developed by the researchers is open-source, and it is capable of automatically revealing potential biases in visual data sets. It works by taking action before the image sets are used to train the computer vision models, and issues surrounding underrepresentation and stereotypes can be remedied before they cause an effect. 


The new tool is called REVISE, and it relies on statistical methods to identify potential biases in a data set. It focuses on the three areas of object-based, gender-based and geography-based. 

REVISE is fully automatic and was built upon previous methods that included filtering and balancing data set images so that the user could have more control. 

The new tool relies on existing image annotations and measurements to analyze the content within a data set. Some of those existing annotations include object count and countries of origin for the images.

In one example of the tool working, REVISE showed how images of both people and flowers were different depending on gender. Males were more likely to appear with flowers in ceremonies or meetings, and females were more likely to appear with flowers in paintings or staged scenarios.

Olga Russaskovsky is an assistant professor of computer science and principal investigator of the Visual AI Lab. The paper was co-authored with graduate student Angelina Wang and associate professor of computer science, Arvind Narayanan.

After the tool identifies discrepancies, “then there’s the question of whether this is a totally innocuous fact, or something deeper is happening, and that’s very hard to automate,” Russaskovsky said. 

Underrepresented or Misrepresented Regions

Various regions around the world are underrepresented in computer vision data sets, and this can lead to bias in AI systems. One of the findings was that a dramatically larger amount of images come from the United States and European countries. REVISE also revealed that images from other parts of the world often do not have image captions in the local language, meaning many could come from a tourist’s view of a nation. 

“…this geography analysis shows that object recognition can still be quite biased and exclusionary and can affect different regions and people unequally,” Russaskovsky continued. 

“Data set collection practices in computer science haven’t been scrutinized that thoroughly until recently,” said Wang.  When it comes to image collection, they are “scraped from the internet, and people don’t always realize that their images are being used [in data sets]. We should collect images from more diverse groups of people, but when we do, we should be careful that we’re getting the images in a way that is respectful.”

Vicente Ordonez-Roman is an assistant professor of computer science at the University of Virginia. 

“Tools and benchmarks are an important step … they allow us to capture these biases earlier in the pipeline and rethink our problem setup and assumptions as well as data collection practices,” said Ordonez-Roman. “In computer vision, there are some specific challenges regarding representation and the propagation of stereotypes. Works such as those by the Princeton Visual AI Lab help elucidate and bring to the attention of the computer vision community some of these issues and offer strategies to mitigate them.”

The new tool developed by the researchers is an important step to help remedy the bias present in AI systems. Now is the time to fix these issues, as it will become much more difficult as the system progress and get more complex. 

[Source: This article was published in unite.ai By Alex McFarland - Uploaded by the Association Member: Daniel K. Henry]
Categorized in Internet Technology

The process of getting your social media accounts verified is mysterious and extremely desirable. For those who don’t know, social media verification is when your account handle has a blue check next to it. You will see A-list celebrities, athletes, musicians, successful brands, and top social media personalities with the blue verified account checks. Simply put, the blue check signifies massive credibility and digital fame.

What most people don’t understand is what it actually takes to qualify and receive the blue check. A few months ago, my TikTok account and personal Instagram account were verified. Here is how it happened. 

Four years ago, I created a liquor brand with my two best friends. The marketing and branding plan was to create an exciting and engaging social media presence. We saw that the liquor industry was largely boring and run by traditional executives who did not understand social media or modern-day digital marketing. While we were building the brand, I became a social media expert and developed a deep understanding of what it would take to become successful. I also took content creation to the next level with unique-point-of-view videos using GoPros. Instead of traditional industry content, we leveraged people and an exciting lifestyle to position the brand. The success of the brand earned me frequent news interviews, a newspaper column, and many interviews in major publications.

During the beginning of the Covid-19 pandemic, I became frustrated with the ever-increasing pay-to-play growth and engagement models of most social media platforms. So, I decided to get serious about TikTok. It seemed to be the only platform where huge organic growth was still possible. This paid off big. My video style was working for the audience, and I began growing quickly. My account has gone from 2,000 followers to almost 100,000 followers. A few videos early on had over 10,000 views, then 50,000 views, 100,000 views, and 500,000 views — and now, many have over 1,000,000 views. 

During a flight when I was flying a privately owned fighter jet trainer, I passed out from the massive G-forces. This video immediately went viral. It had over 3 million views within a few weeks. I decided to license the video, and it really exploded immediately after that. The Daily Mail featured the video, and then many other news sources and social media accounts followed suit. Currently, the video has over 50 million total views across all digital platforms. The Daily Mail article headline directly referenced my TikTok account and that the video had 3 million views. One week later, I opened up my TikTok, and there it was: the blue check.

After my TikTok account was verified, I opened my Instagram app, took a picture of my driver's license, and submitted it directly to Instagram for verification. Within a few hours, there it was: the blue check.

So what does it take to get your social media accounts verified? The answer is generally to be an A-list celebrity or be a leader in your industry who gains massive press and extremely viral content. If you don’t have the above, there is no third-party service I know of that can help you get a blue check. Do not fall for the rampant verification scam services out there. 

If you want to get your social media accounts verified, start off by identifying your unique skill sets and expertise. Next, work hard to become a leader in your field of expertise. Start sharing this expertise and provide value to those around you. Share your ideas on social media and work to get published in small publications. Then, small publications can become large publications.

Next, leverage your skill sets and share them in creative ways on social media. This will take time but can pay off in huge dividends. I never wanted to start a TikTok account, but I learned this was the only place I could quickly grow a massive audience. Spend time mastering social media and staying ahead of the trends. This even includes moving on to new platforms when they launch.

Now, go work on taking your content to the next level, earning major press, and getting your social media accounts verified.

[Source: This article was published in forbes.com By Alex Kowtun - Uploaded by the Association Member: Deborah Tannen] 
Categorized in Investigative Research

“We believe that the main challenge lies in the programming paradigm mismatch between existing software libraries and AutoML”

Recently, Google Brain researchers have introduced a new way of programming automated machine learning (AutoML) based on symbolic programming. The researchers also proposed PyGlove, a general symbolic programming library for Python, to implement the symbolic formulation of AutoML. 

AutoML, designed to fill the machine learning industry’s talent gap, is gaining traction among various organizations. Here, we discuss the challenges AutoML faces and how to resolve them using symbolic programming.

Why This Research

According to the researchers, existing machine learning software libraries are quite limited in handling the dynamic interactions among automated machine learning components. For instance, efficient neural architecture search (NAS) algorithms, such as DARTs, ENAS, demand an implementation coupling between the search algorithm and search space. 

It is also challenging to implement a complex search flow, such as searching architectures within a loop of searching hardware configurations. The researchers stated, “We believe the main challenge lies in the programming paradigm mismatch between existing software libraries and AutoML. 

“Most existing libraries are built on the premise of immutable programs, where a fixed program is used to process different data. On the contrary, AutoML requires programs to be mutable, as they must be dynamically modified by another program whose job is exploring the search space,” they added.

Due to such inconsistency, predefined interfaces for search algorithms and search spaces struggle to accommodate the unanticipated interactions, making it challenging for AI researchers to try new AutoML approaches. In light of these limitations, the researchers have developed a new method to program automated ML. 

Use of Symbolic Programming

Symbolic programming, originated from LISP, allows a program to manipulate its components as if they were plain data. The researchers reformulated AutoML as an automated process to manipulate ML programs symbolically. 

Under the new formulation, programs act as mutable objects that can be cloned as well as modified. These mutable objects can be expressed as standard machine learning concepts where all parts of the machine learning program are mutable. Through symbolic programming, programs can be modified, resulting in dynamic interactions between the child program, search space, and search algorithm in an AutoML program.

How It Works

AutoML is an automated process of searching for a child program from a search space to maximize a reward. The researchers broke down the process into a sequence of symbolic operations. Meaning, a child program is turned into a symbolic child program. The symbolic program is further hyperified into a search space by replacing some of the fixed parts with to-be-determined specifications. 

During the search, the search space materializes into different child programs based on search algorithm decisions. It can also be rewritten into a super-program to apply complex search algorithms such as efficient NAS (ENAS).

About PyGlove

PyGlove is a general symbolic programming library on Python. Using this library, Python classes, as well as functions, can be made mutable through brief Python annotations, making it easier to write AutoML programs. 

The library also allows AutoML techniques to be quickly dropped into preexisting machine learning pipelines while benefiting open-ended research which requires extreme flexibility. PyGlove implements various popular search algorithms, such as PPO, Regularised Evolution and Random Search.

Research Contributions

  • Reformulated AutoML under the symbolic programming paradigm. The researchers simplified the programming interface for automated machine learning by accommodating unanticipated interactions among the child programs, search spaces, and search algorithms through a mutable object model.
  • Introduced PyGlove, a general symbolic programming library for Python that implements the symbolic formulation of AutoML. With this library, automated ML can be quickly dropped into preexisting ML programs, with all program parts searchable, allowing rapid exploration on different dimensions of AutoML.
  • Demonstrated the expressiveness of PyGlove in real-world search spaces. The research showed how PyGlove allows AutoML practitioners to change search spaces, search algorithms and search flows with minimum code.

Wrapping Up

Researchers said PyGlove library could reduce the engineering cost when exploring complex search flows. 

They concluded, ‘We see a big potential in symbolic programming/PyGlove in making machine learning researchers more productive. Symbolic programming and PyGlove makes it easier to develop search-based programs which could be used in a broad spectrum of research and product areas.’

 [Source: This article was published in analyticsindiamag.com By Ambika Choudhury - Uploaded by the Association Member: Rene Meyer]
Categorized in Search Engine

The largest-ever study of facial-recognition data shows how much the rise of deep learning has fueled a loss of privacy.

In 1964, mathematician and computer scientist Woodrow Bledsoe first attempted the task of matching suspects’ faces to mugshots. He measured out the distances between different facial features in printed photographs and fed them into a computer program. His rudimentary successes would set off decades of research into teaching machines to recognize human faces.

Now a new study shows just how much this enterprise has eroded our privacy. It hasn’t just fueled an increasingly powerful tool of surveillance. The latest generation of deep-learning-based facial recognition has completely disrupted our norms of consent.

Deborah Raji, a fellow at nonprofit Mozilla, and Genevieve Fried, who advises members of the US Congress on algorithmic accountability, examined over 130 facial-recognition data sets compiled over 43 years. They found that researchers, driven by the exploding data requirements of deep learning, gradually abandoned asking for people’s consent. This has led more and more of people’s personal photos to be incorporated into systems of surveillance without their knowledge.

It has also led to far messier data sets: they may unintentionally include photos of minors, use racist and sexist labels, or have inconsistent quality and lighting. The trend could help explain the growing number of cases in which facial-recognition systems have failed with troubling consequences, such as the false arrests of two Black men in the Detroit area last year.

People were extremely cautious about collecting, documenting, and verifying face data in the early days, says Raji. “Now we don’t care anymore. All of that has been abandoned,” she says. “You just can’t keep track of a million faces. After a certain point, you can’t even pretend that you have control.”

A history of facial-recognition data

The researchers identified four major eras of facial recognition, each driven by an increasing desire to improve the technology. The first phase, which ran until the 1990s, was largely characterized by manually intensive and computationally slow methods.

But then, spurred by the realization that facial recognition could track and identify individuals more effectively than fingerprints, the US Department of Defense pumped $6.5 million into creating the first large-scale face data set. Over 15 photography sessions in three years, the project captured 14,126 images of 1,199 individuals. The Face Recognition Technology (FERET) database was released in 1996.

The four eras of facial recognition


The following decade saw an uptick in academic and commercial facial-recognition research, and many more data sets were created. The vast majority were sourced through photoshoots like FERET’s and had full participant consent. Many also included meticulous metadata, Raji says, such as the age and ethnicity of subjects, or illumination information. But these early systems struggled in real-world settings, which drove researchers to seek larger and more diverse data sets.

In 2007, the release of the Labeled Faces in the Wild (LFW) data set opened the floodgates to data collection through a web search. Researchers began downloading images directly from Google, Flickr, and Yahoo without concern for consent. LFW also relaxed standards around the inclusion of minors, using photos found with search terms like “baby,” “juvenile,” and “teen” to increase diversity. This process made it possible to create significantly larger data sets in a short time, but facial recognition still faced many of the same challenges as before. This pushed researchers to seek yet more methods and data to overcome the technology’s poor performance.

Then, in 2014, Facebook used its user photos to train a deep-learning model called DeepFace. While the company never released the data set, the system’s superhuman performance elevated deep learning to the de facto method for analyzing faces. This is when manual verification and labeling became nearly impossible as data sets grew to tens of millions of photos, says Raji. It’s also when really strange phenomena start appearing, like auto-generated labels that include offensive terminology.

The way the data sets were used began to change around this time, too. Instead of trying to match individuals, new models began focusing more on classification. “Instead of saying, ‘Is this a photo of Karen? Yes or no,’ it turned into ‘Let’s predict Karen’s internal personality or her ethnicity,’ and boxing people into these categories,” Raji says.

Amba Kak, the global policy director at AI Now, who did not participate in the research, says the paper offers a stark picture of how the biometrics industry has evolved. Deep learning may have rescued the technology from some of its struggles, but “that technological advance also has come at a cost,” she says. “It’s thrown up all these issues that we now are quite familiar with: consent, extraction, IP issues, privacy.”

Harm that begets harm

Raji says her investigation into the data has made her gravely concerned about deep-learning-based facial recognition.

“It’s so much more dangerous,” she says. “The data requirement forces you to collect incredibly sensitive information about, at minimum, tens of thousands of people. It forces you to violate their privacy. That in itself is a basis of harm. And then we’re hoarding all this information that you can’t control to build something that likely will function in ways you can’t even predict. That’s really the nature of where we’re at.”

She hopes the paper will provoke researchers to reflect on the trade-off between the performance gains derived from deep learning and the loss of consent, meticulous data verification, and thorough documentation. “Was it worth abandoning all of these practices in order to do deep learning?” she says.

She urges those who want to continue building facial recognition to consider developing different techniques: “For us to really try to use this tool without hurting people will require re-envisioning everything we know about it.”

[Source: This article was published in technologyreview.com By Karen Haoarchive - Uploaded by the Association Member: Jay Harris]
Categorized in Internet Privacy

has become a platform for most people to find answers to their everyday queries. Whenever one needs or wants to know something, they google. However, many of the times, one does not get specific or relevant answers to the queries.

Nevertheless, this problem can be sorted by conducting some smart Google search tips. Here are a few of them:

1. Search using Google Scholar

Search using Google Scholar.png


If you are into academic research, you need to go to Google Scholar and enter your queries in the search tab so that you find more scholarly and reliable sources of information.

2. Search using ‘+’ sign

Search using.png

When one uses the ‘+’ sign (plus sign) before the keyword, this indicator firmly directs Google that s/he requires that keyword in every search result.

3. Search using ‘-‘ sign


The use of ‘-‘ sign (minus) with some words commands Google that it is not required in the search results. For example, if one wants to search for the recipe of gluten-free bread, they can type ‘bread recipe-gluten’.

4. Search using quotation marks


By the use of quotation marks (”  “), one directs Google to find the webpages which have those words written with quotation marks in the exact order of words and spelling of the words. One can use this tip while searching for books, lyrics of the songs, writers, etc.

5. Search using file type


If one is looking for a particular file type, be it pdf or Word or PowerPoint or Excel, one can simply type ‘filetype:’ and mention the file type and search for the results. By being specific about the file type, you can find about 10 times fewer search results.

6. Search using an asterisk


While searching, if one is confused about the spelling or does not know the particular word in a phrase or partly remembers something, one can use ‘*’  (asterisk sign) instead of that word. This way, Google will try to find that word and shows the search results accordingly.

7. Search using specific websites


Some of the information one looks for can be found on a particular website only. For example, one has to go the official website of Nepal Rastra Bank to know the official forex rate in Nepal. In such case or in the case where one wants to find out about that word/phrase on one specific website, one can type ‘site:sitename.com’ along with the keyword.

8. Search using specific tabs


There lie eight tabs (All, Images, News, Videos, Maps, More, Settings, and Tools) just below the Google search bar. One can narrow down their search result by using these tools. For example, if you are searching for some image, click on the ‘Images’ tab.

[Source: This article was published in english.onlinekhabar.com By Chaim Gartenberg - Uploaded by the Association Member: Dana W. Jimenez]
Categorized in Search Engine

Google detailed a host of new improvements at its “Search On” event that it will make to its foundational Google search service in the coming weeks and months. The changes are largely focused on using new AI and machine learning techniques to provide better search results for users. Chief among them: a new spell checking tool that Google promises will help identify even the most poorly spelled queries.

According to Prabhakar Raghavan, Google’s head of search, 15 percent of Google search queries each day are ones that Google has never seen before, meaning the company has to constantly work to improve its results.

Screenshot 1

Part of that is because of poorly spelled queries. According to Cathy Edwards, VP engineering at Google, 1 in 10 search queries on Google are misspelled. Google has long tried to help with its “did you mean” feature that suggests proper spellings. By the end of the month, it’ll be rolling out a massive update to that feature, which uses a new spelling algorithm powered by a neural net with 680 million parameters. It runs in under three milliseconds after each search, and the company promises it’ll offer even better suggestions for misspelled words.

Another new change: Google search can now index individual passages from webpages, instead of just the whole webpage. For example, if users search for the phrase “how can I determine if my house windows are UV glass,” the new algorithm can find a single paragraph on a DIY forum to find an answer. According to Edwards, when the algorithm starts to roll out next month, it’ll improve 7 percent of queries across all languages.

Screenshot 3

Google is also using AI to divide broader searches into subtopics to help provide better results (say, helping find home exercise equipment designed for smaller apartments versus just providing general workout gear information).

Screenshot 4

Lastly, the company is also starting to use computer vision and speech recognition to automatically tag and divide videos into parts, an automated version of the existing chapter tools it already provides. Cooking videos, for example, or sports games can be parsed and automatically divided into chapters (something Google already offers to creators to do by hand), which can then be surfaced in search. It’s a similar effort to the company’s existing work in surfacing specific podcast episodes in search, instead of just showing the general feed.

[Source: This article was published in theverge.com By Chaim Gartenberg - Uploaded by the Association Member: Logan Hochstetler]
Categorized in Search Engine


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