I noticed that the word “DeepFake” was coming up in my newsfeed again and again, and after around the 6th or 7th time I came across it, I began wondering if that is something I should know about. I mean, if the large tech companies like Amazon, Facebook and Microsoft are working together on a war against DeepFake, and the CNBC is reporting of its dangers, it must be something serious.
It turns out that with DeepFake, you can create a face image of a person that does not even exist, manipulate videos to swap faces of people, and fabricate speech using someone’s voice, without them even agreeing to it. Try out this website thispersonedoesnotexist.com and you will be amazed. This website generates an image of a person imagined by GAN (according to the note on the bottom left corner of the website). Below are some face images generated by that website. I bet you wouldn’t have guessed that these images are fake, and neither would I.
DeepFakes are created by a deep learning technique known as Generative Adversarial Networks (GANs), where two machine learning models are used to make the counterfeits more believable. By studying the images and videos of a person, in the form of training data, the first model creates a video, while the second model attempts to detect its flaws. These two models work hand-in-hand until they create a video that is believable.
DeepFake opens up a whole new world when it comes to unsupervised learning, which is a sub-field of machine learning where machines can learn to teach themselves, and it has been argued to hold great promise when it comes to self-driving vehicles’ to detect and recognize obstacles on the road and virtual assistants such as Siri, Cortana and Alexa learning to be more conversational.
The real question is, what potential does it have of being misused, like any other technology. Using DeepFake as a form of revenge by using it in pornography, manipulating politicians’ photographs and influencing political campaigns are just the tip of the iceberg.
It raises a serious concern about whether we can trust any digital information, in the form of image, video or sound, that is presented to us.
According to BBC News, DeepFake videos have doubled in just nine months, of which, 96% were pornographic in nature. What does this mean for the victims of DeepFake? Who should be held responsible for creating and sharing such fake media and defaming another person?
The tech giants, realizing the danger of DeepFake, have taken initiative to take a stand against the misuse of DeepFake. Facebook and Microsoft announced a competition DeepFace Detection Challenge (DFDC) in September to help detect DeepFakes and manipulated media, where Facebook is helping by creating a large dataset of _DeepFake_videos and Amazon is providing cloud resources for the challenge worth $1 million. This competition will launch in December and the total prize is $10 million.
Google, on the other hand, is also creating a dataset of DeepFake videos so that researchers at the Technical University of Munchin, the University Federico II of Naples and the University of Erlangen-Nurembergcan use it for the FaceForensics project, a project to detect manipulated facial images.
To sum up, technology is becoming smarter and more intelligent day after day and the creation of DeepFake is proof of how machines have advanced to such a level that they can synthesise photos, videos and speech, that even we cannot tell apart from a real one. There are certain benefits to DeepFake, one of which is to create more training data for the betterment of autonomous vehicles. But, as with every other technology, people are misusing it to create fake videos and sharing misinformation on social media. Tech giants have stepped up against this hopefully in the near future, we will have a system that can detect DeepFakes.
What can we do to help prevent misuse of DeepFake and ensure it is used in a safe way? Leave your thoughts as comments below.
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Short news apps are the future, and if they will play a defining role in changing the way consumers consume their content and how the news presenters write their report.
If you want to build an app for short news then you can check out some professional app development companies for your app project As we head into the times where mobile applications and smartphones will be used for anything and everything, the short news applications will allow the reader to choose from various options and read what they want to read.
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Technology has taken a place of more productiveness and give the best to the world. In the current situation, everything is done through the technical process, you don’t have to bother about doing task, everything will be done automatically.This is an article which has some important technologies which are new in the market are explained according to the career preferences. So let’s have a look into the top trending technologies followed in 2021 and its impression in the coming future in the world.
First in the list of newest technologies is surprisingly Data Science. Data Science is the automation that helps to be reasonable for complicated data. The data is produces in a very large amount every day by several companies which comprise sales data, customer profile information, server data, business data, and financial structures. Almost all of the data which is in the form of big data is very indeterminate. The character of a data scientist is to convert the indeterminate datasets into determinate datasets. Then these structured data will examine to recognize trends and patterns. These trends and patterns are beneficial to understand the company’s business performance, customer retention, and how they can be enhanced.
Next one is DevOps, This technology is a mixture of two different things and they are development (Dev) and operations (Ops). This process and technology provide value to their customers in a continuous manner. This technology plays an important role in different aspects and they can be- IT operations, development, security, quality, and engineering to synchronize and cooperate to develop the best and more definitive products. By embracing a culture of DevOps with creative tools and techniques, because through that company will gain the capacity to preferable comeback to consumer requirement, expand the confidence in the request they construct, and accomplish business goals faster. This makes DevOps come into the top 10 trending technologies.
Next one is Machine learning which is constantly established in all the categories of companies or industries, generating a high command for skilled professionals. The machine learning retailing business is looking forward to enlarging to $8.81 billion by 2022. Machine learning practices is basically use for data mining, data analytics, and pattern recognition. In today’s scenario, Machine learning has its own reputed place in the industry. This makes machine learning come into the top 10 trending technologies. Get the best machine learning course and make yourself future-ready.
To want to know more click on Top 10 Trending Technologies in 2021
You may also read more blogs mentioned below
How to Become a Salesforce Developer
The Scope of Hadoop and Big Data in 2021
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Do you want to keep up with new mobile app development trends to better serve your clients? From AppClues Infotech here, you can check out our complete guide to mobile app development trends to watch out for in the year 2021.
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Big Data is increasingly growing in scope in India, affecting the way industries function as well as boosting economies in its wake. Regardless of the size of an organisation, Big Data helps to make better organisational decisions and thereby brings order to the proceedings, making the world a more habitable place in its turn. Especially the transformations happened in Finance and Insurance Industry is tremendous.
At some point in the past, this was not the reality. Data was not always this “Big”. Only large-scale corporations had access to data then because only they could afford the technology that could process this data. In any case, their requirement was for a data analytics system that could take care of massive amounts of data, so they had hardly any choice in the matter.
Since that time, data has evolved at a terribly fast rate, allowing even smaller organisations to make use of the data they gather – all thanks to the internet and cloud technology. With big data cloud solutions, since they offer remote access to data using just the internet, there no longer remains any need for elaborate setups or data experts (who are not easy to acquire), thus saving these small organisations a fortune in internal spending.
The nuances that come with Big Data can now be handled just as easily by organisations that are intent on leveraging the value that it can bring. Moving beyond a simple IT Trend – as these things come and go, but mostly go, without being sustainable for development – Big Data has forged itself into the veins of the tech world, becoming one of its most prized assets.
And even as we write this, we are aware that Big Data is not one monolithic thing. It grows and changes to meet the demands of the various industries that it is a part of, seeking to solve its problems.
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