All posts in “Artificial Intelligence”

Openbook is the latest dream of a digital life beyond Facebook

As tech’s social giants wrestle with antisocial demons that appear to be both an emergent property of their platform power, and a consequence of specific leadership and values failures (evident as they publicly fail to enforce even the standards they claim to have), there are still people dreaming of a better way. Of social networking beyond outrage-fuelled adtech giants like Facebook and Twitter.

There have been many such attempts to build a ‘better’ social network of course. Most have ended in the deadpool. A few are still around with varying degrees of success/usage (Snapchat, Ello and Mastodon are three that spring to mine). None has usurped Zuckerberg’s throne of course.

This is principally because Facebook acquired Instagram and WhatsApp. It has also bought and closed down smaller potential future rivals (tbh). So by hogging network power, and the resources that flow from that, Facebook the company continues to dominate the social space. But that doesn’t stop people imagining something better — a platform that could win friends and influence the mainstream by being better ethically and in terms of functionality.

And so meet the latest dreamer with a double-sided social mission: Openbook.

The idea (currently it’s just that; a small self-funded team; a manifesto; a prototype; a nearly spent Kickstarter campaign; and, well, a lot of hopeful ambition) is to build an open source platform that rethinks social networking to make it friendly and customizable, rather than sticky and creepy.

Their vision to protect privacy as a for-profit platform involves a business model that’s based on honest fees — and an on-platform digital currency — rather than ever watchful ads and trackers.

There’s nothing exactly new in any of their core ideas. But in the face of massive and flagrant data misuse by platform giants these are ideas that seem to sound increasingly like sense. So the element of timing is perhaps the most notable thing here — with Facebook facing greater scrutiny than ever before, and even taking some hits to user growth and to its perceived valuation as a result of ongoing failures of leadership and a management philosophy that’s been attacked by at least one of its outgoing senior execs as manipulative and ethically out of touch.

The Openbook vision of a better way belongs to Joel Hernández who has been dreaming for a couple of years, brainstorming ideas on the side of other projects, and gathering similarly minded people around him to collectively come up with an alternative social network manifesto — whose primary pledge is a commitment to be honest.

“And then the data scandals started happening and every time they would, they would give me hope. Hope that existing social networks were not a given and immutable thing, that they could be changed, improved, replaced,” he tells TechCrunch.

Rather ironically Hernández says it was overhearing the lunchtime conversation of a group of people sitting near him — complaining about a laundry list of social networking ills; “creepy ads, being spammed with messages and notifications all the time, constantly seeing the same kind of content in their newsfeed” — that gave him the final push to pick up the paper manifesto and have a go at actually building (or, well, trying to fund building… ) an alternative platform. 

At the time of writing Openbook’s Kickstarter crowdfunding campaign has a handful of days to go and is only around a third of the way to reaching its (modest) target of $115k, with just over 1,000 backers chipping in. So the funding challenge is looking tough.

The team behind Openbook includes crypto(graphy) royalty, Phil Zimmermann — aka the father of PGP — who is on board as an advisor initially but billed as its “chief cryptographer”, as that’s what he’d be building for the platform if/when the time came. 

Hernández worked with Zimmermann at the Dutch telecom KPN building security and privacy tools for internal usage — so called him up and invited him for a coffee to get his thoughts on the idea.

“As soon as I opened the website with the name Openbook, his face lit up like I had never seen before,” says Hernández. “You see, he wanted to use Facebook. He lives far away from his family and facebook was the way to stay in the loop with his family. But using it would also mean giving away his privacy and therefore accepting defeat on his life-long fight for it, so he never did. He was thrilled at the possibility of an actual alternative.”

On the Kickstarter page there’s a video of Zimmermann explaining the ills of the current landscape of for-profit social platforms, as he views it. “If you go back a century, Coca Cola had cocaine in it and we were giving it to children,” he says here. “It’s crazy what we were doing a century ago. I think there will come a time, some years in the future, when we’re going to look back on social networks today, and what we were doing to ourselves, the harm we were doing to ourselves with social networks.”

“We need an alternative to the social network work revenue model that we have today,” he adds. “The problem with having these deep machine learning neural nets that are monitoring our behaviour and pulling us into deeper and deeper engagement is they already seem to know that nothing drives engagement as much as outrage.

“And this outrage deepens the political divides in our culture, it creates attack vectors against democratic institutions, it undermines our elections, it makes people angry at each other and provides opportunities to divide us. And that’s in addition to the destruction of our privacy by revenue models that are all about exploiting our personal information. So we need some alternative to this.”

Hernández actually pinged TechCrunch’s tips line back in April — soon after the Cambridge Analytica Facebook scandal went global — saying “we’re building the first ever privacy and security first, open-source, social network”.

We’ve heard plenty of similar pitches before, of course. Yet Facebook has continued to harvest global eyeballs by the billions. And even now, after a string of massive data and ethics scandals, it’s all but impossible to imagine users leaving the site en masse. Such is the powerful lock-in of The Social Network effect.

Regulation could present a greater threat to Facebook, though others argue more rules will simply cement its current dominance.

Openbook’s challenger idea is to apply product innovation to try to unstick Zuckerberg. Aka “building functionality that could stand for itself”, as Hernández puts it.

“We openly recognise that privacy will never be enough to get any significant user share from existing social networks,” he says. “That’s why we want to create a more customisable, fun and overall social experience. We won’t follow the footsteps of existing social networks.”

Data portability is an important ingredient to even being able to dream this dream — getting people to switch from a dominant network is hard enough without having to ask them to leave all their stuff behind as well as their friends. Which means that “making the transition process as smooth as possible” is another project focus.

Hernández says they’re building data importers that can parse the archive users are able to request from their existing social networks — to “tell you what’s in there and allow you to select what you want to import into Openbook”.

These sorts of efforts are aided by updated regulations in Europe — which bolster portability requirements on controllers of personal data. “I wouldn’t say it made the project possible but… it provided us a with a unique opportunity no other initiative had before,” says Hernández of the EU’s GDPR.

“Whether it will play a significant role in the mass adoption of the network, we can’t tell for sure but it’s simply an opportunity too good to ignore.”

On the product front, he says they have lots of ideas — reeling off a list that includes the likes of “a topic-roulette for chats, embracing Internet challenges as another kind of content, widgets, profile avatars, AR chatrooms…” for starters.

“Some of these might sound silly but the idea is to break the status quo when it comes to the definition of what a social network can do,” he adds.

Asked why he believes other efforts to build ‘ethical’ alternatives to Facebook have failed he argues it’s usually because they’ve focused on technology rather than product.

“This is still the most predominant [reason for failure],” he suggests. “A project comes up offering a radical new way to do social networking behind the scenes. They focus all their efforts in building the brand new tech needed to do the very basic things a social network can already do. Next thing you know, years have passed. They’re still thousands of miles away from anything similar to the functionality of existing social networks and their core supporters have moved into yet another initiative making the same promises. And the cycle goes on.”

He also reckons disruptive efforts have fizzled out because they were too tightly focused on being just a solution to an existing platform problem and nothing more.

So, in other words, people were trying to build an ‘anti-Facebook’, rather than a distinctly interesting service in its own right. (The latter innovation, you could argue, is how Snap managed to carve out a space for itself in spite of Facebook sitting alongside it — even as Facebook has since sought to crush Snap’s creative market opportunity by cloning its products.)

“This one applies not only to social network initiatives but privacy-friendly products too,” argues Hernández. “The problem with that approach is that the problems they solve or claim to solve are most of the time not mainstream. Such as the lack of privacy.

“While these products might do okay with the people that understand the problems, at the end of the day that’s a very tiny percentage of the market. The solution these products often present to this issue is educating the population about the problems. This process takes too long. And in topics like privacy and security, it’s not easy to educate people. They are topics that require a knowledge level beyond the one required to use the technology and are hard to explain with examples without entering into the conspiracy theorist spectrum.”

So the Openbook team’s philosophy is to shake things up by getting people excited for alternative social networking features and opportunities, with merely the added benefit of not being hostile to privacy nor algorithmically chain-linked to stoking fires of human outrage.

The reliance on digital currency for the business model does present another challenge, though, as getting people to buy into this could be tricky. After all payments equal friction.

To begin with, Hernández says the digital currency component of the platform would be used to let users list secondhand items for sale. Down the line, the vision extends to being able to support a community of creators getting a sustainable income — thanks to the same baked in coin mechanism enabling other users to pay to access content or just appreciate it (via a tip).

So, the idea is, that creators on Openbook would be able to benefit from the social network effect via direct financial payments derived from the platform (instead of merely ad-based payments, such as are available to YouTube creators) — albeit, that’s assuming reaching the necessary critical usage mass. Which of course is the really, really tough bit.

“Lower cuts than any existing solution, great content creation tools, great administration and overview panels, fine-grained control over the view-ability of their content and more possibilities for making a stable and predictable income such as creating extra rewards for people that accept to donate for a fixed period of time such as five months instead of a month to month basis,” says Hernández, listing some of the ideas they have to stand out from existing creator platforms.

“Once we have such a platform and people start using tips for this purpose (which is not such a strange use of a digital token), we will start expanding on its capabilities,” he adds. (He’s also written the requisite Medium article discussing some other potential use cases for the digital currency portion of the plan.)

At this nascent prototype and still-not-actually-funded stage they haven’t made any firm technical decisions on this front either. And also don’t want to end up accidentally getting into bed with an unethical tech.

“Digital currency wise, we’re really concerned about the environmental impact and scalability of the blockchain,” he says — which could risk Openbook contradicting stated green aims in its manifesto and looking hypocritical, given its plan is to plough 30% of its revenues into ‘give-back’ projects, such as environmental and sustainability efforts and also education.

“We want a decentralised currency but we don’t want to rush into decisions without some in-depth research. Currently, we’re going through IOTA’s whitepapers,” he adds.

They do also believe in decentralizing the platform — or at least parts of it — though that would not be their first focus on account of the strategic decision to prioritize product. So they’re not going to win fans from the (other) crypto community. Though that’s hardly a big deal given their target user-base is far more mainstream.

“Initially it will be built on a centralised manner. This will allow us to focus in innovating in regards to the user experience and functionality product rather than coming up with a brand new behind the scenes technology,” he says. “In the future, we’re looking into decentralisation from very specific angles and for different things. Application wise, resiliency and data ownership.”

“A project we’re keeping an eye on and that shares some of our vision on this is Tim Berners Lee’s MIT Solid project. It’s all about decoupling applications from the data they use,” he adds.

So that’s the dream. And the dream sounds good and right. The problem is finding enough funding and wider support — call it ‘belief equity’ — in a market so denuded of competitive possibility as a result of monopolistic platform power that few can even dream an alternative digital reality is possible.

In early April, Hernández posted a link to a basic website with details of Openbook to a few online privacy and tech communities asking for feedback. The response was predictably discouraging. “Some 90% of the replies were a mix between critiques and plain discouraging responses such as “keep dreaming”, “it will never happen”, “don’t you have anything better to do”,” he says.

(Asked this April by US lawmakers whether he thinks he has a monopoly, Zuckerberg paused and then quipped: “It certainly doesn’t feel like that to me!”)

Still, Hernández stuck with it, working on a prototype and launching the Kickstarter. He’s got that far — and wants to build so much more — but getting enough people to believe that a better, fairer social network is even possible might be the biggest challenge of all. 

For now, though, Hernández doesn’t want to stop dreaming.

“We are committed to make Openbook happen,” he says. “Our back-up plan involves grants and impact investment capital. Nothing will be as good as getting our first version through Kickstarter though. Kickstarter funding translates to absolute freedom for innovation, no strings attached.”

You can check out the Openbook crowdfunding pitch here.

NASA’s Parker Solar Probe launches tonight to “touch the sun”

NASA’s ambitious mission to go closer to the Sun than ever before is set to launch in the small hours between Friday and Saturday — at 3:33 AM Eastern from Kennedy Space Center in Florida, to be precise. The Parker Solar Probe, after a handful of gravity assists and preliminary orbits, will enter a stable orbit around the enormous nuclear fireball that gives us all life and sample its radiation from less than 4 million miles away. Believe me, you don’t want to get much closer than that.

If you’re up late tonight (technically tomorrow morning), you can watch the launch live on NASA’s stream.

This is the first mission named after a living researcher, in this case Eugene Parker, who in the ’50s made a number of proposals and theories about the way that stars give off energy. He’s the guy who gave us solar wind, and his research was hugely influential in the study of the sun and other stars — but it’s only now that some of his hypotheses can be tested directly. (Parker himself visited the craft during its construction, and will be at the launch. No doubt he is immensely proud and excited about this whole situation.)

“Directly” means going as close to the sun as technology allows — which leads us to the PSP’s first major innovation: its heat shield, or thermal protection system.

There’s one good thing to be said for the heat near the sun: it’s a dry heat. Because there’s no water vapor or gases in space to heat up, find some shade and you’ll be quite comfortable. So the probe is essentially carrying the most heavy-duty parasol ever created.

It’s a sort of carbon sandwich, with superheated carbon composite on the outside and a carbon foam core. All together it’s less than a foot thick, but it reduces the temperature the probe’s instruments are subjected to from 2,500 degrees Fahrenheit to 85 — actually cooler than it is in much of the U.S. right now.

Go on – it’s quite cool.

The car-sized Parker will orbit the sun and constantly rotate itself so that the heat shield is facing inwards and blocking the brunt of the solar radiation. The instruments mostly sit behind it in a big insulated bundle.

And such instruments! There are three major experiments or instrument sets on the probe.

WISPR (Wide-Field Imager for Parker Solar Probe) is a pair of wide-field telescopes that will watch and image the structure of the corona and solar wind. This is the kind of observation we’ve made before — but never from up close. We generally are seeing these phenomena from the neighborhood of the Earth, nearly 100 million miles away. You can imagine that cutting out 90 million miles of cosmic dust, interfering radiation, and other nuisances will produce an amazingly clear picture.

SWEAP (Solar Wind Electrons Alphas and Protons investigation) looks out to the side of the craft to watch the flows of electrons as they are affected by solar wind and other factors. And on the front is the Solar Probe Cup (I suspect this is a reference to the Ray Bradbury story, “Golden Apples of the Sun”), which is exposed to the full strength of the sun’s radiation; a tiny opening allows charged particles in, and by tracking how they pass through a series of charged windows, they can sort them by type and energy.

FIELDS is another that gets the full heat of the sun. Its antennas are the ones sticking out from the sides — they need to in order to directly sample the electric field surrounding the craft. A set of “fluxgate magnetometers,” clearly a made-up name, measure the magnetic field at an incredibly high rate: two million samples per second.

They’re all powered by solar panels, which seems obvious, but actually it’s a difficult proposition to keep the panels from overloading that close to the sun. They hide behind the shield and just peek out at an oblique angle, so only a fraction of the radiation hits them.

Even then, they’ll get so hot that the team needed to implement the first ever active water cooling system on a spacecraft. Water is pumped through the cells and back behind the shield, where it is cooled by, well, space.

The probe’s mission profile is a complicated one. After escaping the clutches of the Earth, it will swing by Venus, but not to get a gravity boost, but “almost like doing a little handbrake turn,” as one official described it. It slows it down and sends it closer to the sun — and it’ll do that 7 more times, each time bringing it closer and closer to the sun’s surface, ultimately arriving in a stable orbit 3.83 million miles above the surface — that’s 95 percent of the way from the Earth to the sun.

On the way it will hit a top speed of 430,000 miles per hour, which will make it the fastest spacecraft ever launched.

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Parker will make 24 total passes through the corona, and during these times communication with Earth may be interrupted or impractical. If a solar cell is overheating, do you want to wait 20 minutes for a decision from NASA on whether to pull it back? No. This close to the sun even a slight miscalculation results in the reduction of the probe to a cinder, so the team has imbued it with more than the usual autonomy.

It’s covered in sensors in addition to its instruments, and an onboard AI will be empowered to make decisions to rectify anomalies. That sounds worryingly like a HAL 9000 situation, but there are no humans on board to kill, so it’s probably okay.

The mission is scheduled to last 7 years, after which time the fuel used to correct the craft’s orbit and orientation is expected to run out. At that point it will continue as long as it can before drift causes it to break apart and, one rather hopes, become part of the sun’s corona itself.

The Parker Solar Probe is scheduled for launch early Saturday morning, and we’ll update this post when it takes off successfully or, as is possible, is delayed until a later date in the launch window.

Autonomous drones could herd birds away from airports

Bird strikes on aircraft may be rare, but not so rare that airports shouldn’t take precautions against them. But keeping birds away is a difficult proposition: how do you control the behavior of flocks of dozens or hundreds of birds? Perhaps with a drone that autonomously picks the best path to do so, like this one developed by CalTech researchers.

Right now airports may use manually piloted drones, which are expensive and of course limited by the number of qualified pilots, or trained falcons — which as you might guess is a similarly difficult method to scale.

Soon-Jo Chung at CalTech became interested in the field after seeing the near-disaster in 2009 when US Airways 1549 nearly crashed due to a bird strike but was guided to a comparatively safe landing in the Hudson.

“It made me think that next time might not have such a happy ending,” he said in a CalTech news release. “So I started looking into ways to protect airspace from birds by leveraging my research areas in autonomy and robotics.”

A drone seems like an obvious solution — put it in the air and send those geese packing. But predicting and reliably influencing the behavior of a flock is no simple matter.

“You have to be very careful in how you position your drone. If it’s too far away, it won’t move the flock. And if it gets too close, you risk scattering the flock and making it completely uncontrollable,” Chung said.

The team studied models of how groups of animals move and affect one another, and arrived at their own that described how birds move in response to threats. From this can be derived the flight path a drone should follow that will cause the birds to swing aside in the desired direction but not panic and scatter.

Armed with this new software, drones were deployed in several spaces with instructions to deter birds from entering a given protected area. As you can see below (an excerpt from this video), it seems to have worked:

More experimentation is necessary, of course, to tune the model and get the system to a state that is reliable and works with various sizes of flocks, bird airspeeds, and so on. But it’s not hard to imagine this as a standard system for locking down airspace: a dozen or so drones informed by precision radar could protect quite a large area.

The team’s results are published in IEEE Transactions on Robotics.

Scale, whose army of humans annotate raw data to train self-driving and other AI systems, nabs $18M

The artificial intelligence revolution is underway in the world of technology, but as it turns out, some of the most faithful foot soldiers are still humans. A startup called Scale, which works with a team of contractors who examine and categorise visual data to train AI systems in a two-sided marketplace model, announced that it has raised an additional $18 million in a Series B round. The aim will be to expand Scale’s business to become — in the words of CEO Alexandr Wang, the 21-year-old MIT grad who co-founded Scale with Lucy Guo — “the AWS of AI, with multiple services that help companies build AI algorithms.”

“Our mission is to accelerate the development of AI apps,” Wang said. “The first product is visual data labelling, but in the future we have a broad vision of what we hope to provide.”

Wang declined to comment on the startup’s valuation in an interview. But according to Pitchbook, which notes that this round actually closed in May of this year, the post-money valuation of Scale is now $93.50 million ($75 million pre-money).

The money comes on the back of an eventful two years since the company first launched, with revenues growing 15-fold in the last year, and “multiple millions of dollars in revenue” from individual customers. (It doesn’t disclose specific numbers, however.)

Today, Scale’s base of contractors numbers around 10,000, and it works with a plethora of businesses that are developing autonomous vehicle systems such as General Motors’ Cruise, Lyft Zoox, Nuro, Voyage, nuTonomy and Embark. These companies send Scale’s contractors raw, unlabelled data sets by way of Scale’s API, which provides services like Semantic Segmentation, Image Annotation, and Sensor Fusion, in conjunction with its clients LIDAR and RADAR data sets. In total, it says it’s annotated 200,000 “miles of data” collected by self-driving cars.

AV companies are not its only customers, though. Scale also works with several non-automotive companies like Airbnb and Pinterest, to help build their AI-based visual search and recommendation systems. Airbnb, for example, is looking for more ways of being able to ascertain what kinds of homes repeat customers like and don’t like, and also to start to provide other ways of discovering places to stay that are based not just on location and number of bedrooms (which becomes more important especially in cities where you may have too many choices and want a selection more focused on what you are more likely to rent).

This latest funding round was led by Index, with existing investors Accel and Y Combinator (where Scale was incubated), also participated in this Series B, along with some notable, new individual investors such as Dropbox CEO Drew Houston and Justin Kan (two YC alums themselves who have been regular investors in other YC companies). This latest round brings the total raised by Scale to $22.7 million.

When Scale first made its debut in July 2016 as part of YC’s summer cohort, the company presented itself as a more intelligent alternative to Mechanical Turk, specifically to address the demands of artificial intelligence systems that needed more interaction and nuanced responses than the typical microtask asked of a Turker.

“We’re honing in on AI broadly,” Wang said. “Our goal is to be a pick axe in the AI goldrush.”

Early efforts covered a wide spread of applications — categorization/content moderation, comparison, transcription, and phone calling as some examples. But more recently the company has seen a particular interest from self-driving car companies, and specifically the ability to look at, understand and categorise images of what might appear on a road with the kind of recognition that only a human can provide for training purposes. For example, to be able to identify a scooter versus a wagon, a piece of asphalt or an article of granite-colored clothing on a person that could potentially look like asphalt to an unsuspecting camera, or whatever.

“This sub-segment of AI, autonomous vehicles, really took off after we launched, and that segment has been the killer use case for us,” Wang said.

My experience in talking with autonomous car companies and those who work with them has been that many of them are extremely guarded about their data, so much so that there are entire companies being built to help manage this IP standoff so that no one has to share what they know, but they can still benefit from each other.

Wang says that the same holds for Scale’s clients, and part of its unique selling point is that it not only provides data identification services but does so with the assurance that its systems retain none of that data for its own or other companies’ purposes.

“We don’t share across different silos and are very clear about that,” Wang said. “These companies are very sensitive, as are all AI companies about their data and where it goes, and we’ve been able to gain trust as a partner because will not share or sell data to any other parties.”

Scale uses AI itself to help select contractors. “We have built a bunch of algorithms and AI to vet and train contractors,” Wang said. In the training, “we provide feedback and determine if they are getting good enough to do the work, and in terms of ensuring the quality of their work, our algorithms go through what they are doing and verify the work against our models, too. There are a lot of algorithms.”

For clients who are calling in data from the public web — for example Pinterest or Airbnb — Scale uses a broader contractor pool that could include stay-at-home moms, students or others looking for extra money.

For clients who are sensitive about the data that’s being analysed — such as the car companies — the conditions are more restricted, and sometimes include centres where Scale controls the machines that are being used as well as how the data sets can be viewed.

This is one reason why Scale isn’t simply focused on growing the numbers of contractors as its only route for growing business. “We’ve noticed that when you have people who spend more time on this they do better work,” Wang said.

Wang said the Series B funding will be used to expand the kind of work Scale does for existing customers in the area of visual data analysis, as well as to gradually add in other categories of data, such as text.

“Our first goal is to improve algorithms for customers today,” he said. “There is no limit to how accurate they want to make their systems, and they need to be constantly feeding their AI with more data. All of our customers have this, and it’s an evergreen problem.”

The second is to diversify more outside driving and the visual data set, he said. “Right now, so much of the success has been in processing imagery and robotics or other perception challenges, but we really want to be the fabric of the AI world for new applications, including text or audio. That is another use of funds to expand to those areas.”

“Fabric” is the operative word, it seems: “Scale has the potential to become the fabric that connects and powers the Artificial Intelligence world,” said Mike Volpi, General Partner, Index Ventures, in a statement. “For autonomous vehicles in particular, Scale is well-positioned to take over an emerging field of data annotation regardless of which players ultimately come out on top. Alex…has recruited a highly talented and technical team to tackle this challenge and their progress is evident in the marquee list of customers they’ve won in such a short amount of time.”

The U.S. Defense Department is readying for the battle against deepfakes

As concern grows over fake news created by fake AI-generated video, the Defense Department is readying for battle against the imagery known as deepfakes.
As concern grows over fake news created by fake AI-generated video, the Defense Department is readying for battle against the imagery known as deepfakes.

Image: THEGONCAS2/YOUTUBE

The U.S. Defense Department is already preparing itself for the fight against deepfakes, fake audio and video created by artificial intelligence that burst into the mainstream last year thanks to sites like Reddit.

According to MIT Technology Review, the development of tech to catch deepfakes is currently underway. Through the Media Forensics program run by the US Defense Advanced Research Projects Agency (DARPA), researchers have already built some of the tools to expose these fake AI creations. The Media Forensics program was actually originally set up to automate existing forensic tools, however its mission changed due to the concern over the rise of deepfakes. The project’s deepfake mission was announced earlier this year.

In 2017, users on Reddit started utilizing what amounts to extremely convincing face-swap technology to add actor Nicolas Cage into random movies he wasn’t already in. The technology was also being used to insert some female Hollywood celebrities into pornographic video clips. After deepfakes found its way into the daily news cycle and the outrage grew online, some websites banned deepfakes from being posted on their platforms. 

However, deepfake creators kept perfecting the technology, continuously making the fake AI-generated imagery even more realistic. Earlier this year, an app called FakeApp was released effectively making the creation of deepfakes even easier. Concern over the tech quickly turned to its possible use in domestic abuse cases, such as generating sham revenge porn, and in creating fake news. In April, Buzzfeed created an Obama deepfake with Jordan Peele showcasing just how realistic these fake videos were becoming.

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Fast forward to today, where the Defense Department and others are developing tools to combat deepfakes. One such tool comes from Professor Siwei Lyu of SUNY Albany and his students. The AI-generated superimposed video depends heavily on data collected from scanning static imagery. Because of this, Lyu noticed that the face-swapped deepfake videos rarely blink, opening an avenue of detection, at least for now.

Additional tools are being developed as part of the DARPA program to catch other deepfake inaccuracies such as strange or abnormal head and body movements. And while Lyu admits that an experienced deepfake creator or video editor can get around a tool such as one that examines eye-blinking, more sophisticated detection techniques are in the works.

With artificial intelligence becoming more and more advanced in general, it’s clear the deepfake battle will be an arms race between the fake video makers and those looking to unmask the face-swapped truth.

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