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Minding-reading AI creates images from human brainwaves

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FBInCIAnNSATerroristSlayer

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Sep 4, 2022, 4:37:56 AM9/4/22
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Unfortunately Harry Guinness DOESN'T KNOW that Supercomputer AI
commanded by the EVIL CIA NSA MI6 ASIO psychopaths is 50 years AHEAD of
publicly available AI.


CIA NSA GCHQ Supercomputer AI is in CONTROL of MILLIONS of HUMANS all
over the world including US UK AUS CAN NZ EU and ASIA.



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Minding-reading AI creates images from human brainwaves

Don't panic, we're still a far way off from machines being able to read
our every thought.


https://www.popphoto.com/news/mind-reading-ai-images-from-brainwaves/

n a paper published in Scientific Reports earlier this year, researchers
at Radboud University in the Netherlands, led by PHD candidate Thirza
Dado, combined non-invasive brain imaging and AI-learning models in an
attempt to read peoples’ minds—or at least recreate the image they’re
looking at. It’s a fascinating experiment, though it’s easy to overstate
its success. Still, mind-reading AI might not be as far off as we think.

Functional magnetic resonance imaging (fMRI) is a noninvasive technique
used to detect brain activity by measuring changes in blood flow to
different areas of the brain. It’s been used for the last few decades to
identify which parts of the brain are responsible for which functions.

In this study, Dado’s team went a step further. They used an AI model
(specifically a Generative Adversarial Network, or GAN) to attempt to
interpret the fMRI results and convert the readings back into an image.
The results are pretty impressive.

In the study, Dado’s team showed participants undergoing an fMRI 36
generated faces repeated 14 times for the test set and 1,050 generated
faces for the training set (over nine sessions).

Using the fMRI data from the 1,050 unique faces, they trained the AI
model to convert the brain imaging results into actual images. (It works
like a more primitive version of DALL-E 2 or Stable Diffusion.)

The results of the study, then, are based on the AI model’s
interpretation of the fMRI data from the 36 faces in the test set. You
can see a sample of them above. The image in the first column is the
target image, and the images in the second and third columns are the
AI-generated results from the two subjects.
Is this mind reading?

While it’s easy to cherry-pick a few examples where the image
(re)created by the AI closely matches the target image, it’s hard to
call this mind reading. The results of the study measured the accuracy
of the AI in matching the gender, age, and pose, as well as whether the
generated face was wearing eyeglasses, and whether the generated face
was smiling, not whether or not the generated face was recognizable as
the target.

It’s also important to note that the AI was trained on fMRI data from
the test subjects. If you or I were to hop into an fMRI machine, the
results would likely be incredibly scattershot. We’re still a long way
from being able to accurately read anyone’s mind—with or without a
car-sized scientific instrument. Still, it’s fascinating to see how AI
tools and machine learning can play a role in other areas—rather than
just winning fine art competitions.
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