AI-driven audio cloning startup gives voice to Einstein chatbot

You’ll need to prick up your ears up for this slice of deepfakery emerging from the wacky world of synthesized media: A digital version of Albert Einstein — with a synthesized voice that’s been (re)created using AI voice cloning technology drawing on audio recordings of the famous scientist’s actual voice.

 

The startup behind the ‘uncanny valley’ audio deepfake of Einstein is Aflorithmic (whose seed round we covered back in February).

While the video engine powering the 3D character rending components of this ‘digital human’ version of Einstein is the work of another synthesized media company — UneeQ — which is hosting the interactive chatbot version on its website.

Alforithmic says the ‘digital Einstein’ is intended as a showcase for what will soon be possible with conversational social commerce. Which is a fancy way of saying deepfakes that make like historical figures will probably be trying to sell you pizza soon enough, as industry watchers have presciently warned.

The startup also says it sees educational potential in bringing famous, long deceased figures to interactive ‘life’.

Or, well, an artificial approximation of it — the ‘life’ being purely virtual and Digital Einstein’s voice not being a pure tech-powered clone either; Alforithmic says it also worked with an actor to do voice modelling for the chatbot (because how else was it going to get Digital Einstein to be able to say words the real-deal would never even have dreamt of saying — like, er, ‘blockchain’?). So there’s a bit more than AI artifice going on here too.

“This is the next milestone in showcasing the technology to make conversational social commerce possible,” Alforithmic’s COO Matt Lehmann told us. “There are still more than one flaws to iron out as well as tech challenges to overcome but overall we think this is a good way to show where this is moving to.”

In a blog post discussing how it recreated Einstein’s voice the startup writes about progress it made on one challenging element associated with the chatbot version — saying it was able to shrink the response time between turning around input text from the computational knowledge engine to its API being able to render a voiced response, down from an initial 12 seconds to less than three (which it dubs “near-real-time”). But it’s still enough of a lag to ensure the bot can’t escape from being a bit tedious.

Laws that protect people’s data and/or image, meanwhile, present a legal and/or ethical challenge to creating such ‘digital clones’ of living humans — at least not without asking (and most likely paying) first.

Of course historical figures aren’t around to ask awkward questions about the ethics of their likeness being appropriated for selling stuff (if only the cloning technology itself, at this nascent stage). Though licensing rights may still apply — and do in fact in the case of Einstein.

“His rights lie with the Hebrew University of Jerusalem who is a partner in this project,” says Lehmann, before ‘fessing up to the artist licence element of the Einstein ‘voice cloning’ performance. “In fact, we actually didn’t clone Einstein’s voice as such but found inspiration in original recordings as well as in movies. The voice actor who helped us modelling his voice is a huge admirer himself and his performance captivated the character Einstein very well, we thought.”

Turns out the truth about high-tech ‘lies’ is itself a bit of a layer cake. But with deepfakes it’s not the sophistication of the technology that matters so much as the impact the content has — and that’s always going to depend upon context. And however well (or badly) the faking is done, how people respond to what they see and hear can shift the whole narrative — from a positive story (creative/educational synthesized media) to something deeply negative (alarming, misleading deepfakes).

Concern about the potential for deepfakes to become a tool for disinformation is rising, too, as the tech gets more sophisticated — helping to drive moves toward regulating AI in Europe, where the two main entities responsible for ‘Digital Einstein’ are based.

Earlier this week a leaked draft of an incoming legislative proposal on pan-EU rules for ‘high risk’ applications of artificial intelligence included some sections specifically targeted at deepfakes.

Under the plan, lawmakers look set to propose “harmonised transparency rules” for AI systems that are designed to interact with humans and those used to generate or manipulate image, audio or video content. So a future Digital Einstein chatbot (or sales pitch) is likely to need to unequivocally declare itself artificial before it starts faking it — to avoid the need for Internet users to have to apply a virtual Voight-Kampff test.

For now, though, the erudite-sounding interactive Digital Einstein chatbot still has enough of a lag to give the game away. Its makers are also clearly labelling their creation in the hopes of selling their vision of AI-driven social commerce to other businesses.

#alforithmic, #artificial-intelligence, #chatbot, #cloning, #computer-graphics, #ecommerce, #europe, #social-commerce, #special-effects, #synthesized-media, #uneeq

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Epic Games buys photogrammetry software maker Capturing Reality

Epic Games is quickly becoming a more dominant force in gaming infrastructure M&A after a string of recent purchases made to bulk up their Unreal Engine developer suite. Today, the company announced that they’ve brought on the team from photogrammetry studio Capturing Reality to help the company improve how it handles 3D scans of environments and objects.

Terms of the deal weren’t disclosed.

Photogrammetry involves stitching together multiple photos or laser scans to create 3D models of objects that can subsequently be exported as singular files. As the computer vision techniques have evolved to minimize manual fine-tuning and adjustments, designers have been beginning to lean more heavily on photogrammetry to import real world environments into their games. 

Using photogrammetry can help studio developers create photorealistic assets in a fraction of the time it would take to create a similar 3D asset from scratch. It can be used to quickly create 3D assets of everything from an item of clothing, to a car, to a mountain. Anything that exists in 3D space can be captured and as game consoles and GPUs grow more capable in terms of output, the level of detail that can be rendered increases as does the need to utilize more detailed 3D assets.

The Bratislava-based studio will continue operating independently even as its capabilities are integrated into Unreal. Epic announced some reductions to the pricing rates for Capturing Reality’s services, dropping the price of a perpetual license fee from €15,000 to $3,750 USD. In FAQs on the studio’s site, the company notes that they will continue to support non-gaming use clients moving forward.

In 2019, Epic Games acquired Quixel which hosted a library of photogrammetry “mega scans” that developers could access.

 

#3d-imaging, #3d-modeling, #computer-graphics, #epic-games, #forward, #gaming, #laser, #photogrammetry, #tc, #tencent, #unreal-engine, #video-gaming

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How China’s synthetic media startup Surreal nabs funding in 3 months

What if we no longer needed cameras to make videos and can instead generate them through a few lines of coding?

Advances in machine learning are turning the idea into a reality. We’ve seen how deepfakes swap faces in family photos and turn one’s selfies into famous video clips. Now entrepreneurs with AI research background are devising tools to let people generate highly realistic photos, voices, and videos using algorithms.

One of the startups building this technology is China-based Surreal. The company is merely three months old but has already secured a seed round of $2-3 million from two prominent investors, Sequoia China and ZhenFund. Surreal received nearly ten investment offers in this round, founder and CEO Xu Zhuo told TechCrunch, as investors jostled to bet on a future shaped by AI-generated content.

Prior to founding Surreal, Xu spent six years at Snap, building its ad recommendation system, machine learning platform, and AI camera technology. The experience convinced Xu that synthetic media would become mainstream because the tool could significantly “lower the cost of content production,” Xu said in an interview from Surreal’s a-dozen-person office in Shenzhen.

Surreal has no intention, however, to replace human creators or artists. In fact, Xu doesn’t think machines can surpass human creativity in the next few decades. This belief is embodied in the company’s Chinese name, Shi Yun, or The Poetry Cloud. It is taken from the title of a novel by science fiction writer Liu Cixin, who tells the story of how technology fails to outdo the ancient Chinese poet Li Bai.

“We have an internal formula: visual storytelling equals creativity plus making,” Xu said, his eyes lit up. “We focus on the making part.”

In a way, machine video generation is like a souped-up video tool, a step up from the video filters we see today and make Douyin (TikTok’s Chinese version) and Kuaishou popular. Short video apps significantly lower the barrier to making a professional-looking video, but they still require a camera.

“The heart of short videos is definitely not the short video form itself. It lies in having better camera technology, which lowers the cost of video creation,” said Xu, who founded Surreal with Wang Liang, a veteran of TikTok parent ByteDance.

Commercializing deepfakery

Some of the world’s biggest tech firms, such as Google, Facebook, Tencent and ByteDance, also have research teams working on GAN. Xu’s strategy is not to directly confront the heavyweights, which are drawn to big-sized contracts. Rather, Surreal is going after small and medium-sized customers.

Surreal’s face swapping software for e-commerce sellers

Surreal’s software is currently only for enterprise customers, who can use it to either change faces in uploaded content or generate an entirely new image or video. Xu calls Surreal a “Google Translate for videos,” for the software can not only swap people’s faces but also translate the languages they speak accordingly and match their lips with voices.

Users are charged per video or picture. In the future, Surreal aims to not just animate faces but also people’s clothes and motions. While Surreal declined to disclose its financial performance, Xu said the company has accumulated around 10 million photo and video orders.

Much of the demand now is from Chinese e-commerce exporters who use Surreal to create Western models for their marketing material. Hiring real foreign models can be costly, and employing Asian models doesn’t prove as effective. By using Surreal “models”, some customers have been able to achieve 100% return on investment (ROI), Xu said. With the multi-million seed financing in its pocket, Surreal plans to find more use cases like online education so it can collect large volumes of data to improve its algorithm.

Uncharted territory

The technology powering Surreal, called generative adversarial networks, is relatively new. Introduced by machine learning researcher Ian Goodfellow in 2014, GANs consist of a “generator” that produces images and a “discriminator” that detects whether the image is fake or real. The pair enters a period of training with adversarial roles, hence the nomenclature, until the generator delivers a satisfactory result.

In the wrong hands, GANs can be exploited for fraud, pornography and other illegal purposes. That’s in part why Surreal starts with enterprise use rather than making it available to individual users.

Companies like Surreal are also posing new legal challenges. Who owns the machine-generated images and videos? To avoid violating copyright, Surreal requires that the client has the right to the content they upload for moderation. To track and prevent misuse, Surreal adds an encrypted and invisible watermark to each piece of the content it generates, to which it claims ownership. There’s an odd chance that the “person” Surreal produces would match someone in real life, so the company runs an algorithm that crosschecks all the faces it creates with photos it finds online.

“I don’t think ethics is something that Surreal itself can address, but we are willing to explore the issue,” said Xu. “Fundamentally, I think [synthetic media] provides a disruptive infrastructure. It increases productivity, and on a macro level, it’s inexorable, because productivity is the key determinant of issues like this.”

#artificial-intelligence, #asia, #bytedance, #camera-technology, #computer-graphics, #funding, #idg-capital, #machine-learning, #sequoia-china, #shenzhen, #snap, #surreal, #synthetic-media, #tc, #tiktok

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3D model provider CGTrader raises $9.5M Series B led by Evli Growth Partners

3D model provider CGTrader, has raised $9.5M in a Series B funding led by Finnish VC fund Evli Growth Partners, alongside previous investors Karma Ventures and LVV Group. Ex-Rovio CEO Mikael Hed also invested and joins as Board Chairman. We first covered the Vilnius-based company when it raised 200,000 euro from Practica Capital.

Founded in 2011 by 3D designer Marius Kalytis (now COO), CGTrader has become a signifiant 3D content provider – it even claims to be the world’s largest. In its marketplace are 1.1M 3D models and 3.5M 3D designers, service 370,000 businesses including Nike, Microsoft, Made.com, Crate & Barrel, and Staples.

Unlike photos, 3D models can also be used to create both static images as well as AR experiences, so that users can see how a product might fit in their home. The company is also looking to invest in automating 3D modeling, QA, and asset management processes with AI. 

Dalia Lasaite, CEO and co-founder of CGTrader said in a statement: “3D models are not only widely used in professional 3D industries, but have become a more convenient and cost-effective way of generating amazing product visuals for e-commerce as well. With our ARsenal enterprise platform, it is up to ten times cheaper to produce photorealistic 3D visuals that are indistinguishable from photographs.”

CGTrader now plans to consolidate its position and further develop its platform.

The company competes with TurboSquid (which was recently acquired for $75 million by Shutterstock) and Threekit.

#3d, #3d-modeling, #arsenal, #artificial-intelligence, #ceo, #cgtrader, #computer-graphics, #coo, #crate-barrel, #designer, #e-commerce, #europe, #graphics, #image-processing, #karma-ventures, #made-com, #microsoft, #nike, #practica-capital, #rovio, #shutterstock, #staples, #tc, #visual-effects

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Adobe expands Acrobat Web, adds PDF text and image editing

For the longest time, Acrobat was Adobe’s flagship desktop app for working with — and especially editing — PDFs. In recent years, the company launched Acrobat on the web, but it was never quite as fully featured as the desktop version, and one capability a lot of users were looking for, editing text and images in PDFs, remained a desktop-only feature. That’s changing. With its latest update to Acrobat on the web, Adobe is bringing exactly this ability to its online service.

“[Acrobat Web] is strategically important to us because we have more and more people working in the browser,” Todd Gerber, Adobe’s VP for Document Cloud, told me. “Their day begins by logging into whether it’s G Suite or Microsoft Office 365. And so we want to be in all the surfaces where people are doing their work.” The team first launched the ability to create and convert PDFs, but as Gerber noted, it took a while to get to the point where being able to edit PDFs in a performant and real-time way was possible. “We could have done it earlier, but it wouldn’t have been up to the standards of being fast, nimble and quality.” He specifically noted that working with fonts was one of the more difficult problems the team faced in bringing this capability online.

He also noted that even though we tend to think of PDF as an Adobe format, it is an open standard and lots of third-party tools can create PDFs. That large ecosystem, with the potential for variations between implementations, also makes it more difficult to offer editing capabilities for Adobe.

With today’s launch, Adobe is also introducing a couple of additional browser-based features: protecting PDFs, splitting them into two and merging multiple PDFs. In addition, after working with Google last year to offer a handful of Acrobat shortcuts using the .new domain, Adobe is now launching a set of new shortcuts like EditPDF.new. The company plans to roll out more of these over the course of the next year.

In total, Adobe says, the company saw about 10 million clicks on its existing shortcuts, which just goes to show how many people try to convert or sign PDFs every day.

As Gerber noted, a lot of potential users don’t necessarily think of Acrobat first. Instead, what they want to do is compress a PDF or convert it. Acrobat Web and the .new domains help the company bring a new audience to the platform, he believes. “It’s unlocking a new audience for us that didn’t initially think of Adobe. They think about PDFs, they think about what they need to do with them,” he said. “So it’s allowing us to expand our customer base by being relevant in the way that they’re looking to discover and ultimately transact. Our journey with Acrobat web actually started with that notion: let’s go after the non-branded searches.”

Adobe, of course, funnels to the Acrobat desktop app all branded searches where users are explicitly looking for Acrobat, but for the more casual user, it brings them to Acrobat Web where they can easily perform whatever action they came for without even signing up for the service.

#acrobat, #adobe, #adobe-creative-cloud, #cloud, #computer-graphics, #enterprise, #pdf, #software, #tc

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MIT aims to speed up robot movements to match robot thoughts using custom chips

MIT researchers are looking to address the significant gap between how quickly robots can process information (relatively slowly), and how fast they can move (very quickly thanks to modern hardware advances), and they’re using something called ‘robomorphic computing’ to do it. The method, designed by MIT Computer Science and Artificial Intelligence (CSAIL) graduate Dr. Sabrina Neuman, results in custom computer chips that can offer hardware acceleration as a means to faster response times.

Custom-built chips tailored to a very specific purpose are not new – if you’re using a modern iPhone, you have one in that device right now. But they have become more popular as companies and technologists look to do more local computing on devices with more conservative power and computing constraints, rather than round-tripping data to large data centers via network connections.

In this case, the method involves creating hyper-specific chips that are designed based on a robot’s physical layout and and its intended use. By taking into account the requirements a robot has in terms of its perception of its surroundings, its mapping and understanding of its position within those surroundings, and its motion planning resulting from said mapping and its required actions, researchers can design processing chips that greatly increase the efficiency of that last stage by supplementing software algorithms with hardware acceleration.

The classic example of hardware acceleration that most people encounter on a regular basis is a graphics processing unit, or GPU. A GPU is essentially a processor designed specifically for the task of handling graphical computing operations – like display rendering and video playback. GPUs are popular because almost all modern computers run into graphics-intensive applications, but custom chips for a range of different functions have become much more popular lately thanks to the advent of more customizable and efficient small-run chip fabrication techniques.

Here’s a description of how Neuman’s system works specifically in the case of optimizing a hardware chip design for robot control, per MIT News:

The system creates a customized hardware design to best serve a particular robot’s computing needs. The user inputs the parameters of a robot, like its limb layout and how its various joints can move. Neuman’s system translates these physical properties into mathematical matrices. These matrices are “sparse,” meaning they contain many zero values that roughly correspond to movements that are impossible given a robot’s particular anatomy. (Similarly, your arm’s movements are limited because it can only bend at certain joints — it’s not an infinitely pliable spaghetti noodle.)

The system then designs a hardware architecture specialized to run calculations only on the non-zero values in the matrices. The resulting chip design is therefore tailored to maximize efficiency for the robot’s computing needs. And that customization paid off in testing.

Neuman’s team used an field-programmable gate array (FPGA), which is sort of like a midpoint between a fully custom chip and an off-the-shelf CPU, and it achieved significantly better performance than the latter. That means that were you to actually custom manufacture a chip from scratch, you could expect much more significant performance improvements.

Making robots react faster to their environments isn’t just about increase manufacturing speed and efficiency – though it will do that. It’s also about making robots even safer to work with in situations where people are working directly alongside and in collaboration with them. That remains a significant barrier to more widespread use of robotics in everyday life, meaning this research could help unlock the sci-fi future of humans and robots living in integrated harmony.

#artificial-intelligence, #computer-chips, #computer-graphics, #computer-hardware, #computing, #fpga, #hardware-acceleration, #iphone, #mit, #robotics, #science, #tc

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Skylum launches Luminar AI, its AI photo editor

Over the course of the last few years, Skylum made a name for itself with a set of photo-editing apps like Aurora HDR and Luminar. With Luminar AI, it is now launching a brand-new photo editor, starting at $79. The new application, available as a standalone product for Mac and Windows and as a plug-in for Lightroom and Photos for MacOS, was built from the ground up and offers many of the traditional photo-editing features you’re probably familiar with from the likes of Lightroom. The focus, though, is on its new AI-based tools, with a special focus on editing landscapes (and skies in general) and portrait shoots.

In total, Skylum added 13 AI features to the application. You can use those to improve your composition, replace the sky in your images (and relight the scene accordingly), add fog, mist and haze, and manipulate the faces and bodies of your portrait subjects by simply dragging a few sliders.

The idea here is to make it very easy for beginners to improve their photos while also giving pros the tools to quickly get the results they are looking for.

“Our approach to AI lines up with that of the best minds in the field. What differentiates it, however, is our human-centric application of this incredibly powerful technology. In my experience, only 30% of our time is actually spent being creative,” said Alex Tsepko, CEO of Skylum. “Luminar AI uses artificial intelligence to flip those metrics. We created Luminar AI so people can focus on the outcomes and photos, and not worry so much about the editing process.”

Image Credits: Skylum / Jeong Kyu Kim

Image Credits: Skylum / Iurie Belegurschi

For beginners, the place to start is Luminar AI’s templates, which you can think of as very advanced filters that go well beyond what Instagram is capable of. The application automatically classifies the image to get started (say landscape or portrait) and gives you a list of matching templates. That’s cool and often a good start, but chances are if you invest in a tool like this, you’ll want more granular control.

Luminar AI’s marquee feature is its Sky AI, which lets you replace the sky in your images with a few clicks. To do this, you choose from a set of pre-made skies, including sunsets, or create your own library. Either way, the application can then relight the whole scene based on what that sky looks like. It works surprisingly well. There’s also an Augmented Sky AI, which is a bit more gimmicky and lets you add birds, planes and balloons to the sky. It’s not for me, but expect to see a lot of balloons in your favorite influencers’ images in the near future. For more subtle changes, you can opt for the Sky Enhancer AI, which makes your sky pop a little bit more.

Image Credits: Skylum

For more general editing, the Accent AI tool is quite useful to adjust brightness, contrast and color, while Structure AI brings more clarity to an image.

Skylum promises that those adjustments won’t look unnatural, but your mileage may vary. Indeed — and this depends on your personal tastes — I found that for the best results, only moving the sliders 10 or 20 points was often enough. Anything more and you run the risk of creating some pretty garish images.

The portrait features include Body AI, Iris AI, Face AI and Skin AI. They make it exceedingly easy to perform the kind of retouching operations that would usually take a long time in Photoshop, be that bringing out a subject’s eyes, whitening teeth or removing blemishes from their skin.

Image Credits: Skylum

But while tools to change clouds in your landscapes and add bokeh to your shots are pretty uncontroversial for anybody but the most extreme of photography purists, having tools that can easily slim down anybody’s body or face with just a few clicks is something else.

This isn’t necessarily the place to litigate the ethics of portrait retouching and the toxicity of body shaming on social networks, but it’s something to be aware of, especially given how easy Luminar AI makes it to retouch bodies and faces and how effective the tool is. For what it’s worth, I tend to find myself feeling rather queazy using this side of Luminar AI’s tools.

#adobe-lightroom, #adobe-photoshop, #artificial-intelligence, #computer-graphics, #instagram, #microsoft-windows, #photo-editor, #skylum, #social-networks, #tc

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Adobe’s Document Services make PDFs easier to work with for developers

Over the course of the last year, Adobe has quietly continued to expand its tools for helping developers use PDFs in their applications. In April, the company launched a couple of SDKs, for example, which are now known as the PDF Embed API and PDF Tools API, and with that update, the company also launched its Adobe Documents Services platform. The idea here is to provide developers with easy-to-use tools to build PDFs into their applications and workflows. Today, the company is announcing a new partnership with Microsoft that brings Document Services to Power Automate, Microsoft’s low-code workflow automation platform.

“We had this vision about a year and a half back where we said, ‘how about bringing the best of what we provide in our own apps to third-party apps as well?’ ” Vibhor Kapoor, Adobe’s SVP for its Document Cloud business, told me. “That’s kind of the simple mindset where we said: let’s decompose the capabilities of Acrobat as microservices [and] as APIs and give it to developers and publishers because frankly, a PDF for developers and publishers has been a pain for lack of a better word. So we brought these services to life.”

The team worked to make embedding PDFs into web experiences better, for example (and Kapoor frankly noted that previously, the developer experience had always been “very suboptimal” and that the user experience, too, was not always intuitive). Now, with Document Services and the Embed API, it’s just a matter of a few lines of JavaScript to embed a PDF.

Image Credits: Adobe

Kapoor acknowledged that exposing these features in SDKs and APIs was a bit of a challenge, simply because the teams didn’t originally have to worry about this use case. But on top of the technical challenges, this was also a question of changing the overall mindset. “We never had a very developer-oriented offering in the past and that means that we need to build a team that understands developers, and figure out how we package these APIs and make them available,” he noted.

The new Power Automate integration brings over 20 new PDF-centric actions from the PDF Tools API to Microsoft’s platform. These will allow users to do things like create PDFs from documents in a OneDrive folder, for example, covert images to PDFs or apply optical character recognition to PDFs.

Since Adobe launched the platforms, about 6,000 developers have now started using it and Kapoor tells me that he is seeing “significant growth” in terms of the number of API calls that are being made. From a business perspective, adding Power Automate will also likely function as a new funnel for getting new developers on board.

#acrobat, #adobe, #adobe-creative-cloud, #computer-graphics, #developer, #javascript, #microsoft, #optical-character-recognition, #tc, #workflow

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Microsoft launches a deepfake detector tool ahead of US election

Microsoft has added to the slowly growing pile of technologies aimed at spotting synthetic media (aka deepfakes) with the launch of a tool for analyzing videos and still photos to generate a manipulation score.

The tool, called Video Authenticator, provides what Microsoft calls “a percentage chance, or confidence score” that the media has been artificially manipulated.

“In the case of a video, it can provide this percentage in real-time on each frame as the video plays,” it writes in a blog post announcing the tech. “It works by detecting the blending boundary of the deepfake and subtle fading or greyscale elements that might not be detectable by the human eye.”

If a piece of online content looks real but ‘smells’ wrong chances are it’s a high tech manipulation trying to pass as real — perhaps with a malicious intent to misinform people.

And while plenty of deepfakes are created with a very different intent — to be funny or entertaining — taken out of context such synthetic media can still take on a life of its own as it spreads, meaning it can also end up tricking unsuspecting viewers.

While AI tech is used to generate realistic deepfakes, identifying visual disinformation using technology is still a hard problem — and a critically thinking mind remains the best tool for spotting high tech BS.

Nonetheless, technologists continue to work on deepfake spotters — including this latest offering from Microsoft.

Although its blog post warns the tech may offer only passing utility in the AI-fuelled disinformation arms race: “The fact that [deepfakes are] generated by AI that can continue to learn makes it inevitable that they will beat conventional detection technology. However, in the short run, such as the upcoming U.S. election, advanced detection technologies can be a useful tool to help discerning users identify deepfakes.”

This summer a competition kicked off by Facebook to develop a deepfake detector served up results that were better than guessing — but only just in the case of a data-set the researchers hadn’t had prior access to.

Microsoft, meanwhile, says its Video Authenticator tool was created using a public dataset from Face Forensic++ and tested on the DeepFake Detection Challenge Dataset, which it notes are “both leading models for training and testing deepfake detection technologies”.

It’s partnering with the San Francisco-based AI Foundation to make the tool available to organizations involved in the democratic process this year — including news outlets and political campaigns.

“Video Authenticator will initially be available only through RD2020 [Reality Defender 2020], which will guide organizations through the limitations and ethical considerations inherent in any deepfake detection technology. Campaigns and journalists interested in learning more can contact RD2020 here,” Microsoft adds.

The tool has been developed by its R&D division, Microsoft Research, in coordination with its Responsible AI team and an internal advisory body on AI, Ethics and Effects in Engineering and Research Committee — as part of a wider program Microsoft is running aimed at defending democracy from threats posed by disinformation.

“We expect that methods for generating synthetic media will continue to grow in sophistication,” it continues. “As all AI detection methods have rates of failure, we have to understand and be ready to respond to deepfakes that slip through detection methods. Thus, in the longer term, we must seek stronger methods for maintaining and certifying the authenticity of news articles and other media. There are few tools today to help assure readers that the media they’re seeing online came from a trusted source and that it wasn’t altered.”

On the latter front, Microsoft has also announced a system that will enable content producers to add digital hashes and certificates to media that remain in their metadata as the content travels online — providing a reference point for authenticity.

The second component of the system is a reader tool, which can be deployed as a browser extension, for checking certificates and matching the hashes to offer the viewer what Microsoft calls “a high degree of accuracy” that a particular piece of content is authentic/hasn’t been changed.

The certification will also provide the viewer with details about who produced the media.

Microsoft is hoping this digital watermarking authenticity system will end up underpinning a Trusted News Initiative announced last year by UK publicly funded broadcaster, the BBC — specifically for a verification component, called Project Origin, which is led by a coalition of the BBC, CBC/Radio-Canada, Microsoft and The New York Times.

It says the digital watermarking tech will be tested by Project Origin with the aim of developing it into a standard that can be adopted broadly.

“The Trusted News Initiative, which includes a range of publishers and social media companies, has also agreed to engage with this technology. In the months ahead, we hope to broaden work in this area to even more technology companies, news publishers and social media companies,” Microsoft adds.

While work on technologies to identify deepfakes continues, its blog post also emphasizes the importance of media literacy — flagging a partnership with the University of Washington, Sensity and USA Today aimed at boosting critical thinking ahead of the US election.

This partnership has launched a Spot the Deepfake Quiz for voters in the US to “learn about synthetic media, develop critical media literacy skills and gain awareness of the impact of synthetic media on democracy”, as it puts it.

The interactive quiz will be distributed across web and social media properties owned by USA Today, Microsoft and the University of Washington and through social media advertising, per the blog post.

The tech giant also notes that it’s supporting a public service announcement (PSA) campaign in the US encouraging people to take a “reflective pause” and check to make sure information comes from a reputable news organization before they share or promote it on social media ahead of the upcoming election.

“The PSA campaign will help people better understand the harm misinformation and disinformation have on our democracy and the importance of taking the time to identify, share and consume reliable information. The ads will run across radio stations in the United States in September and October,” it adds.

#artificial-intelligence, #canada, #computer-graphics, #deep-learning, #deepfakes, #disinformation, #election-interference, #facebook, #media, #media-literacy, #microsoft-research, #online-content, #san-francisco, #science-and-technology, #social-media, #special-effects, #synthetic-media, #the-new-york-times, #united-kingdom, #united-states, #university-of-washington, #usa-today

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