A deepfake porn Telegram bot is being used to abuse thousands of women

For example, online nudification software which virtually strips women of their clothing creates credible manipulated images. Use of nudification software is increasing at rapid pace – in 2020, a website called DeepSukebe was launched and received 38 million hits in 2021. These are not sites with an innocent intention which some users then bypass – DeepSukebe’s own Twitter bio described it as an ‘AI-leveraged nudifier’ whose mission was to ‘make all men’s dreams come true’. The website offered priced options, paid for in cryptocurrency and all images had to be female; the software did not work on men. The sharing of face-swapped pornographic videos of celebrities on Reddit has been banned two months after people started creating them. Reddit’s move to prohibit “involuntary porn” follows moves by other sites and services to ban the sharing and hosting of such material.

Deep learning has powerful applications in a variety of complex real-world problems, ranging from big-data analytics, computer-vision perception to unmanned control systems. Unfortunately, with the advancement of deep learning technologies, threats to the privacy, stability and security of machine learning-based systems have also developed. Deep fakes are videos or images created using AI to replace one person’s face with another’s, often so verisimilarly that they are almost indistinguishable from reality. The term “deep fake” is a neologism created by merging the terms “fake” and “deep learning,” a particular AI technology. Five years ago, in late 2017, something insidious was brewing in the darker depths of popular chatrooms. Reddit users began violating celebrities on a mass scale, by using deepfake software to blend run-of-the-mill red-carpet images or social media posts into pornography.

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“That’s because car brands have market force incentives to make genuine good cars, not fake cars. So maybe in future you just have to trust brands with ground truth content like video too. In 2016, with the election of Donald Trump, the world learned of Fake News – traditional text-based stories which had been distorted.

Some people even told her the way she dressed and posted images on social media contributed to the harassment — essentially blaming her for the images instead of the creators. It is important to be aware of these risks and to develop robust detection methods and countermeasures to mitigate the potential harm caused by deepfakes. Antti Karppinen is a photographer and digital artist who has already used generative AI for commercial projects, for example to place models in different settings after taking photographs of them and using the images to train the AI. He says he’s keeping an open mind and exploring how AI image generators could create opportunities for his work. Although it depends on what the AI model has been trained on, words like ‘masterpiece’, ‘ultrarealistic’, ‘art photography’, ‘UHD’ and ‘Kodak’ are said to work well.

Sex and the City and the Internet of Things

The bot is free to use although it limits people to ten images per day and payments have to be made to remove watermarks from images. Pornographic deepfakes are being weaponised at an alarming scale with at least 104,000 women targeted by a bot operating on the messaging app Telegram since July. The bot is used by thousands of people every month who use it to create nude images of friends and family members, some of whom appear to be under the age of 18.

The researchers said prompts were able to attack OpenAI’s GPT-3.5 and GPT-4 with a success rate of up to 84%, and 66% for Google’s PaLM-2. Facebook’s new software runs deepfakes through a network to search for imperfections left during the manufacturing process, which the scientists say alter an image’s digital “fingerprint.” Facebook chief Mark Zuckerberg later said the social media firm should have flagged it quicker. In September, Facebook announced it was teaming up with Microsoft to launch a $10m contest for researchers to better detect deepfakes.

In a battle of AI versus AI, researchers are preparing for the coming wave of deepfake propaganda

Yakov Livshits

Artificial Intelligence has shown troubling signs of bias, the work of Safiya Umoja Noble’s Algorithms of Oppression (2018), showed how seemingly ‘impartial information sorting tools’ actually perpetuate systematic racism. A new study by LCFI researchers has found that films entrench gender inequality in AI. Last month, The Guardian found that AI tools rate photos of women as more sexually suggestive than those of men, especially if nipples, pregnant bellies or exercise is involved. It was through chatrooms like this, that I discovered the £5 bot that created the scarily realistic nude of myself.

• Some of them (pruning, quantization) can be applied after the fact to models that already exist, while others (compact filters, knowledge distillation) require developing models from scratch.
• For example, in the AI-generated image of the pope wearing a white puffy jacket, his glasses are deformed and don’t seem to fit right.
• In short, today’s cutting-edge AI systems excel at System 1 tasks but struggle mightily with System 2 tasks.
• A new study by LCFI researchers has found that films entrench gender inequality in AI.
• Edge AI is also lower latency since all processing happens locally; this makes a critical difference for time-sensitive applications like autonomous vehicles or voice assistants.

She suspects someone likely took a picture posted on her social media page or elsewhere and doctored it into porn. Clips of politicians apparently urging violence, or ‘saying’ things that could harm their prospects, had been red flagged. Despite deepfake porn outnumbering videos of political figures by the millions, clamping down on that aspect of the tech was merely a happy by-product. genrative ai However, the right to be forgotten may encounter difficulties in practical application in certain cases. Nevertheless, there are also significant difficulties in identifying the origin of the manipulated image. This can make it difficult to determine who created the image and with what intent, making it difficult to identify those responsible and take appropriate legal action.

Speaking in an interview with Forbes, Mr Altman gave examples of things he found “cool” about the technology, as well as things that scared him. The boss of OpenAI has revealed what he finds most scary about the rapid emergence of advanced artificial intelligence. Authoritarian states are following China’s lead and are trending toward more digital rights abuses by increasing the mass digital surveillance of citizens, censorship, and controls on individual expression. —How a political consultant working for Sam Bankman-Fried described the kinds of causes he should fund, Motherboard reports. Our senior biotech reporter Jessica Hamzelou has been in Lisbon, Portugal this week to attend  a scientific conference on brain stimulation. Neuroscientists, brain surgeons, psychiatrists, and ethicists gathered to discuss how to best use the technologies that use magnetic or electrical pulses to change the way our brains work.

But while the medium was digital, the content remained analogue, and while sex between avatars is not unknown, and is available on Second Life for example,[1] it has not exactly taken off as a global market. Our over-consumption of distressing news stories is not entirely our fault. Media sites know that – due to this ‘negative bias’ – bad news garners more clicks than good genrative ai news. In the aftermath of the 2004 Indian Ocean earthquake and tsunami, news broadcasters sites saw their ratings ‘soar’ as they displayed images of what journalist Susan Llewelyn Leach deemed as nothing other than ‘gratuitous gore’. Psychologists argue that humans are predisposed to be more attracted to bad news, as it enables us to identify danger and react accordingly.

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Just over half (55%) of Brits said social networks should take responsibility for combatting them. Generative AI can be used to create and share harmful content that incites violence, hate speech and online harassment. At times when even visuals can be faked so easily while being so disturbingly realistic, it is crucial to know how to spot deepfakes to avoid misinformation and propaganda.

Like artificial intelligence more broadly, generative AI has inspired both widely beneficial and frighteningly dangerous real-world applications. As the two networks iteratively work against one another—the generator trying to fool the discriminator, the discriminator trying to suss out the generator’s creations—they hone one another’s capabilities. Eventually the discriminator’s classification success rate falls to 50%, no better than random guessing, meaning that the synthetically generated photos have become indistinguishable from the originals. Large technology companies are actively acquiring startups in this category, underscoring the technology’s long-term strategic importance. Earlier this year Apple acquired Seattle-based Xnor.ai for a reported $200 million; Xnor’s technology will help Apple deploy edge AI capabilities on its iPhones and other devices. In 2019 Tesla snapped up DeepScale, one of the early pioneers in this field, to support inference on its vehicles.