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DeviantArt Is Using AI To Alert Artists When Their Work Is Stolen For NFTs

#artificialintelligence

Art theft has become a major problem in the world of Non-Fungible Tokens (NFTs) as grifters look to make a quick buck from the works of others. The nature of the online goods means it's very difficult to confirm who owns the NFTs being sold and if the sellers have the legal right to sell that work on any platform. Progress on a solution has been slow, but it does appear new tactics from hosting companies like DeviantArt are working. DeviantArt recently implemented a new system designed to help identify stolen artwork in the wild by using machine learning to locate works that may have been stolen. It's even able to detect subtle variations in stolen artwork, including if an image is cropped, flipped or slightly altered to avoid traditional image detection systems.


Everyone will be able to clone their voice in the future

#artificialintelligence

Cloning your voice using artificial intelligence is simultaneously tedious and simple: hallmarks of a technology that's just about mature and ready to go public. All you need to do is talk into a microphone for 30 minutes or so, reading a script as carefully as you can (in my case: the voiceover from a David Attenborough documentary). After starting and stopping dozens of times to re-record your flubs and mumbles, you'll send off the resulting audio files to be processed and, in a few hours' time, be told that a copy of your voice is ready and waiting. Then, you can type anything you want into a chatbox, and your AI clone will say it back to you, with the resulting audio realistic to fool even friends and family -- at least for a few moments. The fact that such a service even exists may be news to many, and I don't believe we've begun to fully consider the impact easy access to this technology will have.


Scammers Are Using Deepfake Videos Now

Slate

Highly realistic deepfake videos didn't quite make the splash some feared they would during the 2020 presidential election. Nevertheless, deepfakes are causing trouble--for regular people. In March, the Federal Bureau of Investigation warned that it expected fraudsters to leverage "synthetic content for cyber … operations in the next 12-18 months." In deepfake videos, which first appeared in 2017, a computer-generated face (often of a real person) is superimposed on someone else. After the swap, the fraudsters can make the target person say or do just about anything.


6 Reasons Why Your AI And Data Science Projects Fail

#artificialintelligence

There are tons of wonderful AI and Data Science projects that are continuously getting developed in recent years. As we continue to advance and progress in these fields, there will be tons more awesome projects that will make their way through the development phase and reach the general audience to explore and be fascinated about. For someone who is getting started with these subjects, it is crucial to understand that Data Science and AI projects can sometimes be more complicated than we imagine. As you climb up the skill ceiling, there are tons of noteworthy points to keep in mind as you work on new ventures. While you might be successful in your initial endeavors on beginner-level projects, the increasing complexity of more advanced-level projects could cause several hindrances when you work on them.


How to do a reverse image search from your phone

Mashable

Depending on which mobile browser you use, it might not be immediately obvious how to do a reverse image search from your mobile device. The most simple solution we've come up with is to download and use Google's free Chrome browser for iOS or Android. This particular browser has a quick and easy built-in method for carrying out reverse image searches. We're taking a look at how you can do this in this simple explainer. Google's "Search by Image" functionality is a useful feature that carries out a reverse image search, allowing you to look for related images by uploading an image or an image URL.


Artificial Intelligence in Dry Eye Disease

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Dry eye disease (DED) has a prevalence of between 5 and 50%, depending on the diagnostic criteria used and population under study. However, it remains one of the most underdiagnosed and undertreated conditions in ophthalmology. Many tests used in the diagnosis of DED rely on an experienced observer for image interpretation, which may be considered subjective and result in variation in diagnosis. Since artificial intelligence (AI) systems are capable of advanced problem solving, use of such techniques could lead to more objective diagnosis. Although the term AI' is commonly used, recent success in its applications to medicine is mainly due to advancements in the sub-field of machine learning, which has been used to automatically classify images and predict medical outcomes.


NYK Tests AI System to Automatically Identify Navigation Hazards

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Efforts are continuing to explore the use of automation, artificial intelligence, and image recognition to improve the navigation and safety of ship operations. Earlier this year, Japan's Mitsui O.S.K. Lines demonstrated its efforts are using augmented reality (AR) technology to enhance navigational awareness and now NYK announced that it has begun a trial on the system that can monitor the horizon to recognize dangerous objects that might be within a ship's range. NYK working with its strategic research and development subsidiary MTI Co. installed the Automatic Ship Target recognition System developed in Israel by Orca AI on one of NYK's vessels. The goal is to verify the detection capability and the contribution the system can make to the role of the lookout on a ship's bridge. Working with Orca, NYK also plans to improve the target detection algorithm through the use of data collection and machine learning on the Israeli company's servers.


AI can detect a deepfake face because its pupils have jagged edges

New Scientist

Could this be a computer-generated face? Creating a fake persona online with a computer-generated face is easier than ever before, but there is a simple way to catch these phony pictures – look at the eyes. The inability of artificial intelligence to draw circular pupils gives away whether or not a face comes from a real photograph. Generative adversarial networks (GANs) – a type of AI that can generate images from a simple prompt – can produce realistic-looking faces.


Technologies Behind the Apple's CSAM Detection System

#artificialintelligence

Apple wants to help protect children from people who use communication tools to recruit and exploit them, and limit the spread of CSAM files. On the other side, Apple's plan has been particularly controversial and has prompted concerns about the system potentially being abused by governments as a form of mass surveillance. But rather than analyzing the benefits and drawbacks of this new feature, I would like to say a few words about the cryptographic techniques and protocols used for this system implementation. Before explaining these technologies, let's step back for a moment and take a quick look at the whole process of CSAM detection and its steps to get some more context around this. NeuralHash is a perceptual hashing function that maps images to numbers. The system computes these hashes by using an embedding network to produce image descriptors and then converting those descriptors to integers using a Hyperplane LSH (Locality Sensitivity Hashing) process.


AI avatars bring deepfakes to the business world

#artificialintelligence

This article was originally published on our sister site, Freethink. A financial consulting firm has created AI avatars for its staff, which they can use to quickly create deepfakes of themselves for presentations, emails, and more. The challenge: During the pandemic, remote work became the norm at many companies, and meetings that might have once taken place over lunch happened over the internet instead. This transition was more difficult for some industries than others, and those that traditionally relied on face-time with clients to build relationships and secure deals may have struggled to find their footing. "[W]hile much has been written about how to collaborate remotely with coworkers … companies still are trying to figure out the best way to connect with clients over teleconferencing platforms," Snjezana Cvoro-Begovic and James Hartling, execs at the software company Cognizant Softvision, wrote in Fast Company.