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consagous · 4 years ago

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How AI & ML are Transforming Social Media?

With the advancement in technology and artificial intelligence, various AI-based application platforms have been gaining popularity for a long time. AI has turned out to be a boom for popular Social Media platforms like Facebook and Instagram. To know more about AI and Machine Learning development services in Social Media, continue reading this article!

Today Artificial Intelligence has been a major component of popular Social Media platforms. At the current level of progress, AI for social media has been a powerful tool.

What is Artificial Intelligence? The term artificial intelligence (AI) refers to any human-like intelligence shown by a machine, robot, or computer. It refers to the ability of machines to mimic or copy the intelligence level of the human mind. This may include actions like understanding and responding to voice commands, learning from previous records, problem-solving, and decision-making. Many companies are providing AI application development services, which has made it easy for organizations to adopt AI and ML-based applications. What is Machine Learning?

In general terms, Machine learning (ML) is a subset of AI focusing on building applications and software that can learn from past experiences and data and improve accuracy without being specifically programmed to do so. Machine learning applications learn more from data and are designed to deliver accurate results.

How AI works? Not going deep into the engineerings and software development part of AI, here is just a basic description of working of AI:

Using ML, AI tries to mimic human intelligence. AI can make predictions using algorithms and historical data.

AI and ML in Social Media

Today, there exist several applications of AI and ML in different social media platforms. Big Companies have been using AI for a long time and are still into improvising their platforms and also acquiring small firms. There exist varieties of

AI and Machine Learning App Development Services

that are making the adoption of AI and ML possible.

AI is being used on Social Media platforms in various ways. Some of them are mentioned below:

Analyzing pictures and texts

Advertising

Avoiding unwanted or negative promotions

Spam detection

Data collection

Content flow decisions

Social media insights, etc.

It may sound surprising but your favorite social media apps are already using Artificial Intelligence and Machine Learning.

1. Facebook and AI

Whenever it comes to social media, the first name that comes to mind is Facebook. Talking about cutting-edge technology, repurposing user data broken down into billions of accounts, Facebook is the leading social media platform.

Users on Facebook are allowed to upload pictures, watch videos, read texts and blogs, engage with different social groups, and perform many other functions.

Thinking of such a crazy and huge amount of data, a question arises how Facebook handles such data? Here, AI in Facebook comes in handy.

Facebook and the use of AI in Social Media

Here are some major examples of AI applications in Social Media:

* Facebook’s Text Analyzing

Facebook has an AI-based tool “DeepText”. This tool provides deep learning and helps the back-end team to understand the texts better and that too around multiple languages and hence provide better and more accurate advertising to the users.

* Facebook’s Picture Analyzing

Facebook uses Machine Learning to recognize faces in the photos being uploaded. Using face recognition, Facebook helps you find users that are not known to you. This feature also helps in detecting Catfishes (fake profiles created using your profile picture).

The algorithm also has an amazing feature of text explanations that can help visually disabled people by explaining to them what’s in the picture.

* Facebook’s Bad Content Handling

Using the same tool, DeepText, Facebook has been hailing the inappropriate or bad content that gets posted. After getting notified by AI, the team gets to work to understand and investigate the content.

As per the company guidelines, we get to see a few things that are flagged as inappropriate content:

Nudity or sexual activity

Hate Speech or symbols

Spam

Fake Profiles or fraud

Contents containing excessive violence or self-harm.

Violence or Dangerous organizations

Sale of illegal goods

Intellectual property violations, etc.

Facebook’s Suicide Preventions

With the same tool, DeepText, Facebook can recognize posts or searches that represent suicidal thoughts or activities.

Facebook has been playing a crucial role in suicide prevention. With the support of an analysis based on human moderators, Facebook can send videos and ads containing suicide prevention content to these specific users.

Facebook’s Automatic Translation

Facebook has also adapted AI for translating posts automatically in various languages. This helps the translation be more personalized and accurate.

2. Instagram with AI

Instagram is a photo and video-sharing social media platform that has been owned by Facebook since 2012. Users can upload pictures, videos (reels and IGTV) of their lifestyle, and other stuff and share them with their followers.

This platform is used by individuals, businesses, fictional characters, and pets as well. Managing all the data manually is next to impossible. Therefore, Instagram has developed AI algorithms and models making it the best platform experience for its regular users.

Instagram and the use of AI

* Instagram Decides What Gets on Your Feed

The Explore feature in Instagram uses AI. The suggested posts that you get to see on your explore section are based on the accounts that you follow and the posts you’ve liked.

Through an AI-based system, Instagram extracts 65 billion features and does 90 million model predictions per second.

The huge amount of data that they collect, helps them to show the users what they like.

* Instagram’s Fighting against Cyberbullying

While Facebook and Twitter are dependent mostly on reports from users, Instagram automatically checks content based on hashtags from other users, using AI. In case something is found against the community guidelines, the AI makes sure that the content is removed from Instagram.

* Instagram’s Spam Filtering

Instagram’s AI is capable of recognizing and removing Spam messages from user’s inboxes and that too in 9 different languages.

With the help of Facebook’s DeepText tool, Instagram’s AI can understand the spam context in most situations for more filtration.

* Instagram’s Improved Target Advertising

Instagram can keep a track of which posts have most of the user engagements or the user’s search preferences. Later, Instagram with the help of AI makes target advertisements for companies based on all such databases.

* Instagram handling Bad Contents

Since Instagram is owned by Facebook, more or less, Instagram also follows the same community guidelines over bad content.

3. Twitter and Use of AI

On average, Twitter users post around 6,000 tweets per second. In such a case, AI gets necessary for dealing with such a huge amount of data.

* Tweet Recommendations - AI in Twitter

Twitter firstly implemented AI to improve and give users a better user experience (UX) that would be capable of finding interesting tweets. Now, with the help of AI, Twitter also detects and removes fraud, propaganda, inappropriate content, and hateful accounts.

This recommendation algorithm works in a very interesting way as it learns from your actions over the platform. The tweets are ranked to decide their level of interest, based on the individual users.

AI also considers your past activities of engaging with various types of tweets and uses it to recommend similar tweets.

* Twitter Enhancing Your Pictures - AI in Twitter

Posting of pictures on Twitter was introduced in the year, 2011. Since then, it has been working over an algorithm that is capable of cropping images automatically.

Firstly, they created an algorithm that focused on cropping images based on face recognition, because not every image is supposed to have a face on it. Thus the algorithm was not acceptable.

AI is now used over the platform to crop images before posting them, to make the image look more attractive.

* Tweets Filtration - AI in Twitter

Twitter uses AI to take down inappropriate images and accounts from the platform. Accounts connected to terrorism, manipulation, or spam are taken down using this feature.

* Twitter Fastening the Process - AI in Twitter

How did Twitter use AI to speed up the platform?

For this, Twitter uses a technique called Knowledge Distillation to train smaller networks imitating the slower but strong networks. The larger network was used to generate predictions over a set of images. Then, they developed a pruning algorithm to remove the part of the neutral network.

Using these two models Twitter managed to work over cropping of images 10x faster than ever before.

4. AI in Snapchat

Snapchat started by acquiring two AI companies. In 2015, it first acquired Looksery, a Ukrainian startup, to improvise its animated lenses feature. Secondly, it acquired AI Factory to enhance its video capabilities.

* Snapchat’s Text Recognition in Videos

Snapchat uses AI to recognize texts in the video, which then adds content to your “Snap”. If you type “Hello”, it automatically creates a comic icon or Bitmoji in the video.

* Snapchat- Cameo Feature

AI in Snapchat can be used to edit one’s face in a video. Using the Cameo feature, the users can create a cartoon video of themselves.

From the above-mentioned renowned, we can extract a list of benefits of AI and ML in Social Media, which is given below:

Prediction of user’s behavior

Recognition of inappropriate or bad content

Helps in improving user’s experience

More personalized experience to the users

Gathering of valuable information and user data.

AI has also helped understand human psychology, tracking multiple characteristics of your behavior and responses.

If you are looking for the best

AI & Machine Learning Solutions Provider

for your organization, Consagous Technologies is one of the best

AI Application Development Company in USA

. With years of experience, all the company professionals are great at their work.

Original Source:

https://www.consagous.co/blog/how-ai-ml-are-transforming-social-media

#AI Application Development Company in USA

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riccphoto · 7 years ago

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Shooting with Babe @angelinaaboyko for @lookseri in the beautiful @sohohouse in #miami #riccphoto http://ift.tt/2vxNShA

#IFTTT #Instagram

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pickyme · 5 months ago

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#lookseri #luxury #swimwear #fashion #inspiration

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thetechforlife · 4 years ago

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What is Facial Recognition Technology?

What is Facial Recognition? When we see someone we know our brain process a huge of amount of data about them, the data include from the pattern of hairs, the colour of skin to the shape of eyes, lips, teeth, ears, neck etc. which our brain matches it with its database to tell you who’s that person is. A facial recognition is in its simplest form do the same thing as our brain to recognise the face. It is a technology that is built to recognize your face. when you point your phone’s camera to face of one or more people, it will assume it’s a face and stick a box around it, track it and make sure that it will remain in focus, if you point your camera to a crowd it will identify multiple faces The facial recognition or the Biometric Artificial Intelligence are trained to uniquely identify the faces by analysing pattern, shape & textures of your look like your eyes, nose, teeth, smile etc. The advanced facial recognition systems not only billboard your face but also capable of finding out who a particular face belongs to. How does it identify you? Each face has around 80 nodal points or landmarks. The Present Facial Recognition works on Artificial Intelligence algorithms which are designed to read that landmarks of your faces even if you are in a crowd of millions. Some of the nodal points of the face are Distance between the eyes, Width of the nose, depth of the eye sockets, The shape of the cheekbones, The length of the jawline etc. These nodal points are measured creating a facial signature which is a numerical code that represents the face in the database. A probe image when required is compared with the stored facial signature data. Techniques used in Face Acquisition: The face Acquisition process performed in two steps, the first one involves the extraction & selection and second involve classification. Recognition algorithms are broadly divided into four main approaches. 2 Dimensional Recognition 3 Dimensional Recognition Skin Texture Analysis Thermal Sensing Technology 2D or Geometric Approach The geometric approaches look into separate structures of the face and these geometrical structures of the face are extracted from eyes, the shape of the mouth, face boundary etc. and are organized as a graph for modelling and recognition. However, these algorithms can be classified into two broad categories: holistic based and feature-based models. The Holistic based model recognises the face in its entirety while the feature-based model subdivides the subject face into components such as according to features and analyse each as well as its spatial location concerning other features. The various face detection techniques used in this approach are Principal Component Analysis (PCA), Neural Networks, Machine Learning, Hough Transform and Template Matching. Recognition using 3D Approach In this type of approach, 3Dimensional geometry of human face is used to achieve better results than 2D. 3D facial recognition techniques use distinguished topographies of the face which are not changed with time. They are stiff tissue and bones, such as the curves of the eye socket, nose and chin -- to identify the subject. These are all unique to every human and don’t change with coarse of time. Further-more to know that this technique is also not affected by a change in the quantity of light and the face can be identified from different view angles. These 3D recognition techniques used 3D image sensors to capture face geometry. The Sensors are placed on CMOS Chip which is designed to hold dozens of sensors. The sensors throw a sophisticated structured light on the face which was again collected by the sensors. Each sensor captures a different part of the spectrum which was collected and processed to generate the 3D image of the subject. Skin Texture Analysis Our skin has the same kind of details like our fingerprints. The technique called skin textures analysis uses the visual details like unique lines, patterns and spot of the skin and convert into a digital data. This process is called surface texture analysis in which a picture is taken of a particular area (patch) of a skin the picture is then converted into digital blocks, algorithm further used to identify each pattern by distinguishing any lines, pores and the actual skin texture. It can also able to detect the difference between the two identical twins which was not possible with facial recognition software alone. Tests have shown that with the addition of skin texture analysis, performance in recognizing faces can increase 20 to 25 per cent. Thermal Sensing Technology Another technique is thermal Sensing Technology which uses the subject temperature to produce an image. Thermal imagers work by distinguishing and estimating the measure of infrared radiation that is produced and reflected by articles or individuals to outwardly render temperature. A thermal camera utilizes a gadget known as a microbolometer to get this vitality simply outside the scope of obvious light and venture it back to the watcher as an unmistakably characterized picture. Some popular Face Recognition Algorithms are o OpenFace o OpenBR o Face recognition using Tensorflow o Deep Face Recognition with Caffe Implementation o SphereFace o Node FaceNet o Android Face Recognition with Deep Learning o Fisherfaces o FaceMatch Where does it is used? Face recognition is widely used by social media platforms to attract more users in amid of competition. Looksery App which is now owned by snap chat uses to real-time face recognition with a filter that allows the user to modify the look of the face. Similarly, Facebook has also developed a DeepFace which is a facial recognition program. It identifies humans in digital images with its nine-layer neural net with over 120 million connection weight. ID Verification: Growing use of Facial recognition technology has not put an option for many companies to use this technology for identification purposes. In-fact many companies start working to provide this technology to banks and other eCommerce companies. In Security Service: Security is the most important aspect of this technology. Facial recognition systems can monitor people coming and going in airports. The technology is used to identify people who have overstayed their visas or may be under criminal investigation. Many countries like Australia, New Zealand, Canada, UK, Netherland, China etc. are using facial recognition technology for various security purposes like on airport, public places, on borders etc. Besides its advantages in security purposes, we can also not deny its disadvantages. Here are the Six disadvantage of facial recognition. Politically Biased: There are a few concerns that Face Recognition permits governments to undermine security rights. The legislatures have no government has no limit to utilize this technology, he can use it as they see fit. Accordingly, they could keep an eye on their residents and single them out for what they say or whom they meet. In democratic nations, laws can be made to prevent misuse of the technology. But what if rebel components inside government organizations misuse this technology to pursue their private agendas. That is the thing that got a few people concerned. But many countries have not made any effective laws which could guarantee the prevention of misuse? These are some question which are yet to be answered. Individual Privacy Concern The facial recognition systems are capable to recognize the subject from millions of images and video sources. The sources include CCTV, Smartphones, Social Media and other online activities. Police Department, Intelligence Agencies using these techniques to monitor & track down criminals. But what if they decided to track anyone for personal reason, Face recognition technology enables the mass tracking either by govt. or by any private company. It is just like taking your DNA or Finger Print without you know about it. Data Privacy & Data Theft Another reason of concern is data privacy. The data includes images and videos files which are stored in cloud servers which may at risk of being stolen by hackers. In such type of data breaches, the information will get into wrong hands, although the companies are seriously taking steps to prevent any possible breaches but yet no one can guarantee for 100% protection. Lack of Regulation Government around the world are yet to pass laws to check and limit the use of facial recognition techniques. With the increasing use of Business houses adopting facial recognition, needs a plan to avoid risk for data breaches which can only be possible by government intervention. Read Other Stories:Bold and Beautiful ways to get through the Coronavirus lockdown. Read the full article

#TechNews

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prerpm · 5 years ago

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Snapchat Snapshot

Oh Snap! Am I too old for Snapchat?

Statistics say no, not at all.

For years my friends have been trying to get me to join Snapchat. I am an avid Instagram user and when filters were introduced on Instagram, my only incentive to join Snapchat was gone.

As such, as a 29-year-old woman, my go-to excuse for not using Snapchat became “I’m too old for it.”

That has been totally debunked through my research on Snapchat for this week’s Switch Up.

Snapchat reaches 75% of 13 to 34-year-olds, and 90% of 13 to 24-year-olds in the U.S. Approximately 61% of Snapchat users are female and 38% are male.

I decided then to depict some other Snapchat stats in a graphic (below) just to see in a single picture how large and wide-reaching the platform really is:

Statistics from Omnicore

So, what exactly is Snapchat? And how does it work?

Snapchat is a social media messaging app where you can send text, multimedia, gifs (OMG!) - Snaps - to your friends. What sets it apart from other messaging apps is that messages disappear - “self-destruct” - after its allotted time (you can pick how many seconds it will be visible to the recipient).

Snapchat is touted as being the first platform to use Augmented Reality filters which was also later emulated by Instagram, Facebook etc.

What is Augmented Reality (AR)?

Augmented Reality is “a technology that superimposes a computer-generated image on a user's view of the real world, thus providing a composite view.”

Brief history of Snapchat AR filter:

In 2011, CEO Evan Spiegel released Snapchat, then called Picaboo. He then went on to acquire Looksery, a Ukrainian AR company that had began using AR to modify facial images. By 2017, Snapchat had released 3000 AR filters including the beloved dog-sticking-its-tongue-out one and other platforms like Facebook joined the bandwagon.

Today, AR is everywhere.

I find it interesting how a fun feature of Snapchat has now triggered a full-fledged emerging new field in marketing: augmented reality marketing.

In the Fortune article, ‘Augmented Reality: Eight AR Marketing Applications For Brands In 2019,′ author Lorne Fade lists how brands can use AR to boost their business. The list includes increasing customer “dwell time” at live events and company website to building strong relationships with customers via tailored experiential marketing. Read the article here.

“Deloitte identified that almost 90 percent of companies with annual revenues of $100 million to $1 billion are now leveraging AR or VR technology. For smaller firms, a poll conducted by Purch revealed that 10 percent of marketers utilize AR, and 72 percent are planning to in the coming year.”

In trying to differentiate itself from its competitors through innovation and early adoption of emerging technology, Snapchat really was able to create not just a niche space for itself but also snowballed an entire new segment in digital marketing.

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tinydreamkingdom · 5 years ago

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Snapchat quietly acquired AI Factory, the company behind its new Cameos feature, for $166M – TechCrunch After acquiring Ukraine startup Looksery in 2015 to supercharge animated selfie lenses in Snapchat arguably changing the filters game for all social video and photo apps Snap has made another acquisition with roots in the country, co-founded by one of Lookser… Read More

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localbizlift · 5 years ago

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Snapchat quietly acquired AI Factory, the company behind its new Cameos feature, for $166M

After acquiring Ukraine startup Looksery in 2015 to supercharge animated selfie lenses in Snapchat — arguably changing the filters game for all social video and photo apps — Snap has made another acquisition with roots in the country, co-founded by one of Looksery’s founders, to give a big boost to its video capabilities.

The company has acquired AI Factory, a computer vision startup that Snap had worked with to create Snapchat’s new Cameos animated selfie-based video feature, for a price believed to be in the region of $166 million.

The news was first reported by a Ukrainian publication AIN, and while I’m still waiting for a direct reply from Snap about the acquisition, I’ve had the news confirmed by another source close to the deal. Snap also confirmed the news to another publication, VC.ru (in Russian).

Victor Shaburov, the founder of Looksery who then went on to become Snap’s director of engineering — leaving in May 2018 to found and lead AI Factory — declined to provide a comment for this story.

Cameos, launched last month, lets you take a selfie, which is then automatically “animated” and inserted into a short video. The selection of videos, currently around 150, is created by Snap, with the whole concept not unlike the one underpinning ‘deepfakes’ — AI-based videos that look “real” but are actually things that never really happened.

Deepfake videos have been around for a while. But if your experience of that word has strong dystopian undertones, we now appear to be in a moment where consumer apps are tapping into the technology in a race for new — fun, lighthearted — features to attract and keep users. Just today, Josh reported that TikTok has secretly built a deepfake tool, too. I expect we’ll be hearing about Facebook’s newest deepfake tool in 3, 2, 1…

From what I understand, while AI Factory has offices in San Francisco, the majority of the team of around 70 is based out of Ukraine. Part of the team will relocate with the deal, and part will stay there.

Snap had also been an investor in AI Factory. Part of its early interest would have been because of the track record of the talent associated with the startup: lenses have been a huge success for Snap — 70% of its daily active users play with them, and they not only bring in new users, but increase retention and bring in revenues by way of sponsorships or users buying them — so creating new features to give users more ways to play around with their selfies is a good bet.

It’s not clear whether AI Factory will be developing a way to insert selfies into any video, or if the feature will be tied just to specific videos offered by Snap itself, or whether the videos will extend beyond the timing of a GIF. It’s also not clear what else AI Factory was working on: the company’s site is offline and there is very little information about the company beyond its mission to bring more AI-based imaging tools into mainstream apps and usage.

The company’s LinkedIn profile says that AI Factory “provide[s] multiple AI business solutions based on image and video recognition, analysis and processing,” so while the company will come under Snap’s wing, there may be scope for the team to build some of its technology into more innovative ways for businesses to use the Snap platform in the future, too.

We’ll update this post as we learn more, and if/when we hear back from Snap directly.

#marketing

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superbsummers · 5 years ago

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Snapchat quietly acquired AI Factory, the company behind its new Cameos feature, for $166M

The company has acquired AI Factory, a computer vision startup that Snap…

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#Marketing #Online Marketing #Social – TechCrunch #Social Media

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un-enfant-immature · 5 years ago

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Snapchat quietly acquired AI Factory, the company behind its new Cameos feature, for $166M

We’ll update this post as we learn more, and if/when we hear back from Snap directly.

#TechCrunch

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pmsocialmedia · 5 years ago

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Snapchat quietly acquired AI Factory, the company behind its new Cameos feature, for $166M

We’ll update this post as we learn more, and if/when we hear back from Snap directly.

via Social – TechCrunch https://ift.tt/2SS6290

#IFTTT #Social – TechCrunch

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