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AI asked to generate images of ‘the last selfies ever taken’ produces nightmarish results

People taking pictures of themselves with melting skin, blood-stained faces and mutated bodies, as they face a burning world is what the DALL-E AI believes will be the last selfies taken at the end of time.

DALL-E AI, developed by OpenAI, is a new system that can produce full images with natural language descriptions and TikToker Robot Overlords just asked to ‘show the last selfie ever’.

The nightmarish results each show a human holding a phone and behind them are scenes of bombs falling, colossal tornadoes and cities on fire, along with zombies in the midst of destruction.

One of the selfies is an animated image of a man wearing something that resembles riot gear. He slowly moves his head around with a look as if his life is flashing before his eyes as bombs fall from the sky around him.

Each of the videos has been viewed hundreds of thousands of times, with users commenting on how horrifying each selfie is — one user felt the images would keep them up at night because they’re so hair-raising.

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One of the selfies is an animated image of a man wearing something that resembles riot gear.  He slowly moves his head around with a look as if his life is flashing before his eyes as bombs fall from the sky around him

One of the selfies is an animated image of a man wearing something that resembles riot gear. He slowly moves his head around with a look as if his life is flashing before his eyes as bombs fall from the sky around him

Other users joked about taking a selfie at the end of time, saying, “But first, let me take a selfie” (if no one gets this reference, I’m going to cry).

TikTok user Nessa shared, “and my boss would still ask me to come to work.”

However, not everyone was light-hearted about what the end times would look like.

User Victeur shared: “Imagine hiding in the dark before the war, haven’t seen your face in years and see this when you take one last picture of yourself.”

The nightmarish results each show a human holding a phone and behind them are scenes of bombs falling, colossal tornadoes and cities on fire, along with zombies in the midst of destruction.

The nightmarish results each show a human holding a phone and behind them are scenes of bombs falling, colossal tornadoes and cities on fire, along with zombies in the midst of destruction.

The selfies were generated by a TikToker that told the AI ​​to generate what it thinks the final selfies will look like

The selfies were generated by a TikToker that told the AI ​​to generate what it thinks the final selfies will look like

Most commenters see the fun side of the images, but a dark side has been discovered with DALL-E – it’s racial and gender bias.

The system is public and when OpenAI launched the second version of the AI, it encouraged people to enter descriptions so that the AI ​​can improve image generation over time, NBC News reports.

However, people started to notice that the images were biased. For example, if a user typed in CEO, DALL-E would only produce images of white men, and for “hostess” only images of women.

OpenAI announced last week that it was launching new mitigation techniques to help DALL-E create more diverse images and claims the update will make users 12 times more likely to see images featuring more diverse people.

The nightmarish images, showing zombies in front of burning cities, were created by DALL-E AI

The nightmarish images, showing zombies in front of burning cities, were created by DALL-E AI

Developed by OpenAI, DALL-E is a new system that can produce full images when fed with natural language descriptions, and TikToker Robot Overlords simply asked it to

Developed by OpenAI, DALL-E is a new system that can produce full images when fed with natural language descriptions, and TikToker Robot Overlords simply asked it to “show the last selfie ever.”

The images are so chilling that some TikTok users said they will now have nightmares after seeing them

The images are so chilling that some TikTok users said they will now have nightmares after seeing them

The original version of DALL-E, named after Spanish surrealist artist Salvador Dali, and Pixar robot WALL-E, was released in January 2021 as a limited test of ways AI can be used to represent concepts – from bland descriptions to fantasies.

Some of the early artworks created by the AI ​​include a mannequin in a flannel shirt, an illustration of a radish walking a dog, and a baby penguin emoji.

Examples of phrases used in the second release – to produce realistic images – are ‘an astronaut riding a horse in a photo-realistic style’.

On the DALL-E 2 website this can be modified to produce images ‘on the fly’ including replacing astronaut with teddy bear, horse with basketballs and showing as a pencil drawing or as a ‘pop art’ in Andy Warhol- style painting.

DALL·E 2 has learned the relationship between images and the text used to describe them,” explains OpenAI.

“It uses a process called ‘diffusion’, which starts with a pattern of random dots and gradually changes that pattern into an image as specific aspects of that image are recognized.”

HOW TO LEARN ARTIFICIAL INTELLIGENCE NEURAL NETWORKS?

AI systems rely on artificial neural networks (ANNs), which attempt to simulate the way the brain works for learning.

ANNs can be trained to recognize patterns in information – including speech, text data or visual images – and are the basis for many advances in AI in recent years.

Conventional AI uses input to “learn” an algorithm about a particular topic by giving it massive amounts of information.

AI systems rely on artificial neural networks (ANNs), which attempt to simulate the way the brain works for learning.  ANNs can be trained to recognize patterns in information - including speech, text data or visual images

AI systems rely on artificial neural networks (ANNs), which attempt to simulate the way the brain works for learning. ANNs can be trained to recognize patterns in information – including speech, text data or visual images

Practical applications include Google’s translation services, Facebook’s facial recognition software, and Snapchat’s image-changing live filters.

Entering this data can be very time consuming and limited to one type of knowledge.

A new breed of ANNs called Adversarial Neural Networks pit the minds of two AI bots against each other, allowing them to learn from each other.

This approach is designed to accelerate the learning process and refine the output of AI systems.

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