Tag: ai

AI can now create a replica of your personality

Imagine sitting down with an AI model for a spoken two-hour interview. A friendly voice guides you through a conversation that ranges from your childhood, your formative memories, and your career to your thoughts on immigration policy. Not long after, a virtual replica of you is able to embody your values and preferences with stunning accuracy.

That’s now possible, according to a new paper from a team including researchers from Stanford and Google DeepMind, which has been published on arXiv and has not yet been peer-reviewed. 

Led by Joon Sung Park, a Stanford PhD student in computer science, the team recruited 1,000 people who varied by age, gender, race, region, education, and political ideology. They were paid up to $100 for their participation. From interviews with them, the team created agent replicas of those individuals. As a test of how well the agents mimicked their human counterparts, participants did a series of personality tests, social surveys, and logic games, twice each, two weeks apart; then the agents completed the same exercises. The results were 85% similar. 

“If you can have a bunch of small ‘yous’ running around and actually making the decisions that you would have made—that, I think, is ultimately the future,” Park says. 

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US calls on Taiwan to stop supplying AI chips to China

Washington has officially demanded that Taiwan Semiconductor Manufacturing Co (TSMC), one of the world’s largest semiconductor manufacturing companies, stop supplying China with chips used in Artificial Intelligence (AI), Reuters reported on November 10. However, Washington’s pressure on China’s semiconductor industry also includes Taiwan once Donald Trump comes to power next year.

TSMC is one of the largest chip producers and cooperates with several technology companies, such as Nvidia and AMD, and specialises in integrated circuit, also known as a microchip, a small device made up of several interconnected electronic components that are etched onto a small piece of semiconductor material.

Taiwan produces about 90% of the world’s most advanced semiconductors, mostly by TSMC, and ensuring these chips do not reach China is a priority for Washington, an effort that will only intensify when Trump becomes president.

“The US ordered Taiwan Semiconductor Manufacturing Co to halt shipments of advanced chips to Chinese customers that are often used in artificial intelligence applications,” Reuters reported, citing sources familiar with the subject.

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AI scans RNA ‘dark matter’ and uncovers 70,000 new viruses

Researchers have used artificial intelligence (AI) to uncover 70,500 viruses previously unknown to science1, many of them weird and nothing like known species. The RNA viruses were identified using metagenomics, in which scientists sample all the genomes present in the environment without having to culture individual viruses. The method shows the potential of AI to explore the ‘dark matter’ of the RNA virus universe.

Viruses are ubiquitous microorganisms that infect animals, plants and even bacteria, yet only a small fraction have been identified and described. There is “essentially a bottomless pit” of viruses to discover, says Artem Babaian, a computational virologist at the University of Toronto in Canada. Some of these viruses could cause diseases in people, which means that characterizing them could help to explain mystery illnesses, he says.

Previous studies have used machine learning to find new viruses in sequencing data. The latest study, published in Cell this week, takes that work a step further and uses it to look at predicted protein structures1.

The AI model incorporates a protein-prediction tool, called ESMFold, that was developed by researchers at Meta (formerly Facebook, headquartered in Menlo Park, California). A similar AI system, AlphaFold, was developed by researchers at Google DeepMind in London, who won the Nobel Prize in Chemistry this week.

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The Pentagon Wants to Use AI to Create Deepfake Internet Users

The United States’ secretive Special Operations Command is looking for companies to help create deepfake internet users so convincing that neither humans nor computers will be able to detect they are fake, according to a procurement document reviewed by The Intercept.

The plan, mentioned in a new 76-page wish list by the Department of Defense’s Joint Special Operations Command, or JSOC, outlines advanced technologies desired for country’s most elite, clandestine military efforts. “Special Operations Forces (SOF) are interested in technologies that can generate convincing online personas for use on social media platforms, social networking sites, and other online content,” the entry reads.

The document specifies that JSOC wants the ability to create online user profiles that “appear to be a unique individual that is recognizable as human but does not exist in the real world,” with each featuring “multiple expressions” and “Government Identification quality photos.”

In addition to still images of faked people, the document notes that “the solution should include facial & background imagery, facial & background video, and audio layers,” and JSOC hopes to be able to generate “selfie video” from these fabricated humans. These videos will feature more than fake people: Each deepfake selfie will come with a matching faked background, “to create a virtual environment undetectable by social media algorithms.”

The Pentagon has already been caught using phony social media users to further its interests in recent years. In 2022, Meta and Twitter removed a propaganda network using faked accounts operated by U.S. Central Command, including some with profile pictures generated with methods similar to those outlined by JSOC. A 2024 Reuters investigation revealed a Special Operations Command campaign using fake social media users aimed at undermining foreign confidence in China’s Covid vaccine.

Last year, Special Operations Command, or SOCOM, expressed interest in using video “deepfakes,” a general term for synthesized audiovisual data meant to be indistinguishable from a genuine recording, for “influence operations, digital deception, communication disruption, and disinformation campaigns.” Such imagery is generated using a variety of machine learning techniques, generally using software that has been “trained” to recognize and recreate human features by analyzing a massive database of faces and bodies. This year’s SOCOM wish list specifies an interest in software similar to StyleGAN, a tool released by Nvidia in 2019 that powered the globally popular website “This Person Does Not Exist.” Within a year of StyleGAN’s launch, Facebook said it had taken down a network of accounts that used the technology to create false profile pictures. Since then, academic and private sector researchers have been engaged in a race between new ways to create undetectable deepfakes, and new ways to detect them. Many government services now require so-called liveness detection to thwart deepfaked identity photos, asking human applicants to upload a selfie video to demonstrate they are a real person — an obstacle that SOCOM may be interested in thwarting.

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If AI Companies Are Trying To Build God, Shouldn’t They Get Our Permission First?

AI companies are on a mission to radically change our world. They’re working on building machines that could outstrip human intelligence and unleash a dramatic economic transformation on us all.

Sam Altman, the CEO of ChatGPT-maker OpenAI, has basically told us he’s trying to build a god — or “magic intelligence in the sky,” as he puts it. OpenAI’s official term for this is artificial general intelligence, or AGI. Altman says that AGI will not only “break capitalism” but also that it’s “probably the greatest threat to the continued existence of humanity.”

There’s a very natural question here: Did anyone actually ask for this kind of AI? By what right do a few powerful tech CEOs get to decide that our whole world should be turned upside down?

As I’ve written before, it’s clearly undemocratic that private companies are building tech that aims to totally change the world without seeking buy-in from the public. In fact, even leaders at the major companies are expressing unease about how undemocratic it is.

Jack Clark, the co-founder of the AI company Anthropic, told Vox last year that it’s “a real weird thing that this is not a government project.” He also wrote that there are several key things he’s “confused and uneasy” about, including, “How much permission do AI developers need to get from society before irrevocably changing society?” Clark continued:

Technologists have always had something of a libertarian streak, and this is perhaps best epitomized by the ‘social media’ and Uber et al era of the 2010s — vast, society-altering systems ranging from social networks to rideshare systems were deployed into the world and aggressively scaled with little regard to the societies they were influencing. This form of permissionless invention is basically the implicitly preferred form of development as epitomized by Silicon Valley and the general ‘move fast and break things’ philosophy of tech. Should the same be true of AI?

I’ve noticed that when anyone questions that norm of “permissionless invention,” a lot of tech enthusiasts push back. Their objections always seem to fall into one of three categories. Because this is such a perennial and important debate, it’s worth tackling each of them in turn — and why I think they’re wrong.

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Invisible text that AI chatbots understand and humans can’t? Yep, it’s a thing.

What if there was a way to sneak malicious instructions into Claude, Copilot, or other top-name AI chatbots and get confidential data out of them by using characters large language models can recognize and their human users can’t? As it turns out, there was—and in some cases still is.

The invisible characters, the result of a quirk in the Unicode text encoding standard, create an ideal covert channel that can make it easier for attackers to conceal malicious payloads fed into an LLM. The hidden text can similarly obfuscate the exfiltration of passwords, financial information, or other secrets out of the same AI-powered bots. Because the hidden text can be combined with normal text, users can unwittingly paste it into prompts. The secret content can also be appended to visible text in chatbot output.

The result is a steganographic framework built into the most widely used text encoding channel.

“Mind-blowing”

“The fact that GPT 4.0 and Claude Opus were able to really understand those invisible tags was really mind-blowing to me and made the whole AI security space much more interesting,” Joseph Thacker, an independent researcher and AI engineer at Appomni, said in an interview. “The idea that they can be completely invisible in all browsers but still readable by large language models makes [attacks] much more feasible in just about every area.”

To demonstrate the utility of “ASCII smuggling”—the term used to describe the embedding of invisible characters mirroring those contained in the American Standard Code for Information Interchange—researcher and term creator Johann Rehberger created two proof-of-concept (POC) attacks earlier this year that used the technique in hacks against Microsoft 365 Copilot. The service allows Microsoft users to use Copilot to process emails, documents, or any other content connected to their accounts. Both attacks searched a user’s inbox for sensitive secrets—in one case, sales figures and, in the other, a one-time passcode.

When found, the attacks induced Copilot to express the secrets in invisible characters and append them to a URL, along with instructions for the user to visit the link. Because the confidential information isn’t visible, the link appeared benign, so many users would see little reason not to click on it as instructed by Copilot. And with that, the invisible string of non-renderable characters covertly conveyed the secret messages inside to Rehberger’s server. Microsoft introduced mitigations for the attack several months after Rehberger privately reported it. The POCs are nonetheless enlightening.

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Open AI Wants to Build Data Centres That Would Consume More Electricity Per Year Than the Whole of the U.K.

Over the past few months, the newswires have been hot with stories about the large-scale data centres that will be required to meet the needs of the forthcoming revolution in Artificial Intelligence (AI). How much electricity will these new data centres consume and what does that mean for the electricity demand forecasts underpinning the plans for Net Zero?

Recent Date Centre Announcements

To give a flavour of the scale of data centre developments that are coming, it is helpful to look at recent announcements from large tech companies. Back in March, it was announced that Amazon had bought a 960MW data centre that is powered by an adjacent nuclear power station. In April, Mark Zuckerberg CEO of Meta that owns Facebook and Instagram said energy requirements may hold back the build out of AI data centres. He also talked about building data centres that would consume 1GW of power.

Last month, Oracle chairman Larry Ellison announced that Oracle was designing a data centre that would consume more than 1GW that would be powered by three small modular nuclear reactors (SMRs). Then Microsoft also got in on the act when it announced it had done a deal with U.S. utility Constellation to restart the 835MW Three Mile Island (TMI) Unit 1 nuclear power plant to power its data centres. Anxious not to be left out, Sundar Pichai, CEO of Google said they too were working on 1GW data centres and saw money being invested in SMRs.

Finally, Sam Altman of OpenAI, the creator of ChatGPT has trumped them all by pitching the idea of 5GW data centres to the White House. Altman has been heard talking of building five to seven of these leviathans.

Bloomberg, usually a driver of the Net Zero band wagon, has reluctantly admitted that there’s not enough clean energy – nuclear or otherwise – to satisfy AI’s voracious appetite and gas will have to fill the gap. America’s national security and energy security is eclipsing climate concerns.

This admission is important because it acknowledges that such important infrastructure cannot rely upon the vicissitudes of the weather. These data centres need a source of electricity that is reliable and always available. It would be absurd to think that a ChatGPT user will want to receive a message saying their request cannot be processed because it is not windy enough.

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How the Army is using AI during Hurricane Helene relief

The Army’s 18th Airborne Corps is for the first time using a battlefield capability to map road closures, cellular outages, supply needs and other data in real time to help the Federal Emergency Management Agency and U.S. Northern Command help people whose homes and communities were battered by Hurricane Helene late last month.

The Army is using its Maven Smart System to provide responders with the information needed to make quick, on-the-ground decisions, such as where to send medical supplies or how many truckloads of water to take into certain storm-ravaged areas, defense officials told reporters Monday.

Weeks after the deadly hurricane tore a path from Florida’s Gulf Coast into the Appalachian Mountains, some residents in the southeast are still sifting through the wreckage caused by floods and landslides that destroyed entire towns.

More damage is feared as Hurricane Milton bears down on Florida this week as well.

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The Big Tech Think Tank Campaigning to Censor Satire

The Brookings Institution, seems to believe it has solved the problem faced by those who would like to censor memes. The problem is that memes are a form of satire, and censoring them while claiming to be a democracy is a difficult task.

But now, senior Brookings Institution fellow Nicol Turner Lee and Isabella Panico Hernandez, a project assistant, have revealed their thinking: AI memes should be treated as election disinformation “manifested” through satire.

One could use a similar form of mental gymnastics to say that this kind of argument represents a call for censorship manifested through supposed concern about disinformation.

The Brookings, meanwhile, is not just any foot soldier in the “war on memes”: it is a powerful think tank funded by the likes of Amazon, Google, Meta, Microsoft, but also massive financial institutions like JPMorgan Chase (via its philanthropic foundation) and that of Mastercard, Impact Fund.

Brookings speaks about memes, particularly those AI-generated (adding some AI panic into the mix can only help the cause), as an extremely dangerous phenomenon hidden behind humor, and perceived as humor by pretty much everyone.

But the think tank, and others going after memes, present themselves as smarter and able to understand the true nature of this clearly humorous and often satirical imagery, which they say only “seem harmless” and “appear innocuous.”

Instead, the authors of the article say memes can influence how voters perceive candidates and other election-related information, “could potentially lead to violence” – and are “globally perceived” as being capable to “fuel extremist behavior” – which is in contrast to the US, supposedly because of the lack of appropriate regulation.

And so, less than a month before the presidential election, these according to the authors insidious messages use humor merely as a vehicle to spread dangerous influence, but are not properly tackled in the US.

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Meta’s new “Movie Gen” AI system can deepfake video from a single photo

On Friday, Meta announced a preview of Movie Gen, a new suite of AI models designed to create and manipulate video, audio, and images, including creating a realistic video from a single photo of a person. The company claims the models outperform other video-synthesis models when evaluated by humans, pushing us closer to a future where anyone can synthesize a full video of any subject on demand.

The company does not yet have plans of when or how it will release these capabilities to the public, but Meta says Movie Gen is a tool that may allow people to “enhance their inherent creativity” rather than replace human artists and animators. The company envisions future applications such as easily creating and editing “day in the life” videos for social media platforms or generating personalized animated birthday greetings.

Movie Gen builds on Meta’s previous work in video synthesis, following 2022’s Make-A-Scene video generator and the Emu image-synthesis model. Using text prompts for guidance, this latest system can generate custom videos with sounds for the first time, edit and insert changes into existing videos, and transform images of people into realistic personalized videos.

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