The tool – still in its developmental phase – allows artists to protect their work by subtly altering pixels in images, rendering them imperceptibly different to the human eye but confusing to AI models.

Many artists and creators have expressed concern over the use of their work in training commercial AI products without their consent.

AI models rely on vast amounts of multimedia data – including written material and images, often scraped from the web – to function effectively. Nightshade offers a potential solution by sabotaging this data.

When integrated into digital artwork, Nightshade misleads AI models, causing them to misidentify objects and scenes.

For instance, Nightshade transformed images of dogs into data that appeared to AI models as cats. After exposure to a mere 100 poison samples, the AI reliably generated a cat when asked for a dog—demonstrating the tool’s effectiveness.

This technique not only confuses AI models but also challenges the fundamental way in which generative AI operates. By exploiting the clustering of similar words and ideas in AI models, Nightshade can manipulate responses to specific prompts and further undermine the accuracy of AI-generated content.

Developed by computer science professor Ben Zhao and his team, Nightshade is an extension of their prior product, Glaze, which cloaks digital artwork and distorts pixels to baffle AI models regarding artistic style.

While the potential for misuse of Nightshade is acknowledged, the researchers’ primary objective is to shift the balance of power from AI companies back to artists and discourage intellectual property violations.

The introduction of Nightshade presents a major challenge to AI developers. Detecting and removing images with poisoned pixels is a complex task, given the imperceptible nature of the alterations.

If integrated into existing AI training datasets, these images necessitate removal and potential retraining of AI models, posing a substantial hurdle for companies relying on stolen or unauthorised data.

As the researchers await peer review of their work, Nightshade is a beacon of hope for artists seeking to protect their creative endeavours.

(Photo by Josie Weiss on Unsplash)

See also: UMG files landmark lawsuit against AI developer Anthropic

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Deepfakes leverage machine learning and AI techniques to convincingly manipulate or generate visual and audio content. Their high potential to deceive makes them a powerful tool for spreading disinformation, committing fraud, trolling, and more.

“Every time we improve these tools, we’re actually in a sense building a toolset to create fake media — and we’re seeing it happening now,” said Cameron in a BBC video interview.

“Right now the tools are — the people just playing around on apps aren’t that great. But over time, those limitations will go away. Things that you see and fully believe you’re seeing could be faked.”

Have you ever said “I’ll believe it when I see it with my own eyes,” or similar? I certainly have. As humans, we’re subconsciously trained to believe what we can see (unless it’s quite obviously faked.)

The problem is amplified with today’s fast news cycle. It’s a well-known problem that many articles get shared based on their headline before moving on to the next story. Few people are going to stop to analyse images and videos for small imperfections.

Often the stories are shared with reactions to the headline without reading the story to get the full context. This can lead to a butterfly effect of people seeing their contacts’ reactions to the headline and feel they don’t need additional context—often just sharing in whatever emotional response the headline was designed to invoke (generally outrage.)

“News cycles happen so fast, and people respond so quickly, you could have a major incident take place between the interval between when the deepfake drops and when it’s exposed as a fake,” says Cameron.

“We’ve seen situations — you know, Arab Spring being a classic example — where with social media, the uprising was practically overnight.”

It’s a difficult problem to tackle as it is. We’ve all seen the amount of disinformation around things such as the COVID-19 vaccines. However, an article posted with convincing deepfake media will be almost impossible to stop from being posted and/or shared widely.

AI tools for spotting the increasingly small differences between real and manipulated media will be key to preventing deepfakes from ever being posted. AI tools for spotting the increasingly small differences between real and manipulated media will be key to preventing deepfakes from ever being posted. However, researchers have found that current tools can easily be deceived.

Images and videos that can be verified as original and authentic using technologies like distributed ledgers could also be used to help give audiences confidence the media they’re consuming isn’t a manipulated version and they really can trust their own eyes.

In the meantime, Cameron suggest using Occam’s razor—a problem-solving principle that’s can be summarised as the simplest explanation is the likeliest.

“Conspiracy theories are all too complicated. People aren’t that good, human systems aren’t that good, people can’t keep a secret to save their lives, and most people in positions of power are bumbling stooges.

“The fact that we think that they could realistically pull off these — these complex plots? I don’t buy any of that crap! Bill Gates is not really trying to microchip you with the flu vaccine!”

However, Cameron admits his scepticism of new technology.

“Every single advancement in technology that’s ever been created has been weaponised. I say this to AI scientists all the time, and they go, ‘No, no, no, we’ve got this under control.’ You know, ‘We just give the AIs the right goals…’

“So who’s deciding what those goals are? The people that put up the money for the research, right? Which are all either big business or defense. So you’re going to teach these new sentient entities to be either greedy or murderous.”

Of course, Skynet gets an honourary mention.

“If Skynet wanted to take over and wipe us out, it would actually look a lot like what’s going on right now. It’s not going to have to — like, wipe out the entire, you know, biosphere and environment with nuclear weapons to do it. It’s going to be so much easier and less energy required to just turn our minds against ourselves.

“All Skynet would have to do is just deepfake a bunch of people, pit them against each other, stir up a lot of foment, and just run this giant deepfake on humanity.”

Russia’s infamous state-sponsored “troll farms” are one of the largest sources of disinformation and are used to conduct online influence campaigns.

In a January 2017 report issued by the United States Intelligence Community – Assessing Russian Activities and Intentions in Recent US Elections (PDF) – described the ‘Internet Research Agency’ as one such troll farm.

“The likely financier of the so-called Internet Research Agency of professional trolls located in Saint Petersburg is a close ally of [Vladimir] Putin with ties to Russian intelligence,” commenting that “they previously were devoted to supporting Russian actions in Ukraine.”

Western officials have warned that Russia may use disinformation campaigns – including claims of an attack from Ukrainian troops – to rally support and justify an invasion of Ukraine. It’s not out the realms of possibility that manipulated content will play a role, so it could be too late to counter the first large-scale disaster supported by deepfakes.

Related: University College London: Deepfakes are the ‘most serious’ AI crime threat

(Image Credit: Gage Skidmore. Image cropped. CC BY-SA 3.0 license)

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Silicon Valley darling Nuance is one of the world’s most recognisable AI companies for the creation of Siri, the voice assistant that would later go on to become Apple’s first-party solution.

Nuance now focuses its efforts predominantly on enterprise communications, particularly in the healthcare space which has seen increased interest amid the COVID-19 pandemic. Using technology from Nuance, medical staff can reduce their reliance on pen-and-paper and free up more time for improving patient outcomes.

Bloomberg initially reported Microsoft’s interest in Nuance.

Anurag Rana, Senior Analyst at Bloomberg Intelligence, commented in the report: “This can really help Microsoft accelerate the digitisation of the healthcare industry, which has lagged other sectors such as retail and banking.

“The biggest near-term benefit that I can see is in the area of telehealth, where Nuance transcription product is currently being used with Microsoft Teams.”

Nuance’s shares [NUAN] closed yesterday at $45.58 but Microsoft is reportedly prepared to pay $56 per share – over 20 percent higher. Nuance’s shares have increased pre-market to $54.90 per share, seemingly boosted by the rumours.

Microsoft has all but killed off its Cortana voice assistant for consumer-facing purposes, removing it from the App Store and Play Store earlier this month. Redmond now appears to be pivoting its efforts towards developing AI solutions for specific enterprise areas.

In addition to Nuance’s AI expertise, Microsoft would also be gaining access to the company’s over 3,500 patents.

If the deal goes ahead, it would represent Microsoft’s largest acquisition after its $24 billion takeover of Linkedin. Microsoft is also reportedly in talks to acquire gaming communications platform Discord for over $10 billion. This could be a very big news month for Redmond.

Update: Well, we did say the deal was expected to be announced imminently. Mere hours after this article went live Microsoft confirmed its acquisition of Nuance in an all-cash transaction valued at $19.7 billion.

“Nuance provides the AI layer at the healthcare point of delivery and is a pioneer in the real-world application of enterprise AI,” said Satya Nadella, CEO, Microsoft. “AI is technology’s most important priority, and healthcare is its most urgent application. Together, with our partner ecosystem, we will put advanced AI solutions into the hands of professionals everywhere to drive better decision-making and create more meaningful connections, as we accelerate growth of Microsoft Cloud for Healthcare and Nuance.”

“Over the past three years, Nuance has streamlined its portfolio to focus on the healthcare and enterprise AI segments, where there has been accelerated demand for advanced conversational AI and ambient solutions,” said Mark Benjamin, CEO, Nuance. “To seize this opportunity, we need the right platform to bring focus and global scale to our customers and partners to enable more personal, affordable and effective connections to people and care. The path forward is clearly with Microsoft —  who brings intelligent cloud-based services at scale and who shares our passion for the ways technology can make a difference. At the same time, this combination offers a critical opportunity to deliver meaningful and certain value to our shareholders who have driven and supported us on this journey.”

“Nuance not only brings an attractive set of healthcare customers in AI – a huge bid for Microsoft – but also deep domain expertise as well. This has been the missing ingredient for Microsoft until now,” comments Nicholas McQuire, Chief of Enterprise Research at CCS Insight.

“In the past, we have seen firms like IBM buy industry specialism in datasets but Nuance delivers Microsoft a more mature set of AI solutions in areas such as speech recognition, document processing, fraud detection, and image recognition. Ultimately these will prove key to differentiating Azure to healthcare customers against its largely horizontal competitors.”

(Image Credit: Apple)

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The propeller-forward designs of most drones are inefficient and reduce flight time. Researchers from MIT, Dartmouth, and the University of Washington have proposed a new hybrid design which aims to combine the perks of both helicopters and fixed-wing planes.

In order to support the new design, a new AI system was developed to switch between hovering and gliding with a single flight controller.

Speaking to VentureBeat, MIT CSAIL graduate student and project lead Jie Xu said:

 “Our method allows non-experts to design a model, wait a few hours to compute its controller, and walk away with a customised, ready-to-fly drone.

The hope is that a platform like this could make more these more versatile ‘hybrid drones’ much more accessible to everyone.”

Existing fixed-wing drones require engineers to build different systems for hovering (like a helicopter) and flying horizontally (like a plane). Controllers are also needed to switch between.

Today’s control systems are designed around simulations, causing a discrepancy when used in actual hardware in real-world scenarios.

Using reinforcement learning, the researchers trained a model which can detect potential differences between the simulation and reality. The controller is then able to use this model to transition from hovering to flying, and back again, just by updating the drone’s target velocity.

OnShape, a popular CAD platform, is used to allow users to select potential drone parts from a data set. The proposed design’s performance can then be tested in a simulator.

“We expect that this proposed solution will find application in many other domains,” wrote the researchers in the paper. It’s easy to imagine the research one day being scaled up to people-carrying ‘air taxis’ and more.

The researchers will present their paper later this month at the Siggraph conference in Los Angeles.

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