In this world, technology has left everyone behind and made the impossible possible. Artificial intelligence has advanced so much that we can’t even imagine, and it has become an “unthinkable” thing because it can now read your mind.
Artificial intelligence will now convert your thoughts into images, as an experiment was conducted at Osaka University in Japan, which had an accuracy of 80%.
The stable diffusion method was used to conduct this experiment, which is a popular method.
According to a recent study by researchers at Osaka University, an AI-powered algorithm was able to reconstruct about 1,000 images from brain scans, including an airplane and a teddy bear, with an accuracy rate of 80 percent. The researchers used the Stable Diffusion model, a popular method included in OpenAI’s DALL-E 2, and can generate images based on text inputs.
A group of people were kept in a lab and then they were shown some images.
Here are the images that were shown to the people
After that fMRI technology was used that collect images of the brain and use artificial intelligence to decode the information in those images. This is indeed a groundbreaking experiment that could potentially allow us to understand what someone is thinking based on images of their brain activity. By using machine learning algorithms to analyze the patterns of brain activity, researchers may be able to decipher the meaning behind those patterns and translate them into meaningful information. However, it’s important to note that this technology is still in its early stages of development and there are many ethical and privacy concerns that need to be addressed before it can be used widely.
The scientists who showed four participants the initial images have now started the experiment, and when they extracted the data from their brains, the results were shocking.
Here is the result which they obtained:
The result is 80% accurate.
In a study published in bioRxiv, the research team announced that they had developed a method to reconstruct high-resolution images with high semantic fidelity from human brain activity. Their approach is unique because it does not require training or fine-tuning complex deep-learning models.
Here is the complete video demonstration how this experiment was held:
Yu Takagi, who led the research, explained that the algorithm extracts information from the occipital and temporal lobes of the brain, which are involved in image perception. The team used fMRI to detect changes in blood flow in active brain areas while the participants viewed 10,000 images.
According to Science.org, fMRI detects oxygen molecules to see which areas of the brain are working hardest while we have thoughts or emotions. The AI starts generating the images as noise, similar to television static. It is then replaced with distinguishable features the algorithm sees in the activity by referring to the pictures it was trained on and finding a match.
Scientists believe that their experiment doesn’t need complex training. Instead, they suggest using simple methods unlike the previous models, including training, tuning, and deep learning models.
The study claims that the team’s simple framework can reconstruct high-resolution (512 x 512) images with high semantic fidelity from brain activity. They also interpret each latent diffusion model (LDM) component from a neuroscience perspective by mapping specific components to distinct brain regions.
Overall, the team provides an objective interpretation of how the text-to-image conversion process implemented by an LDM incorporates the semantic information expressed by the conditional text while maintaining the appearance of the original image.
This groundbreaking experiment could revolutionize how we understand the workings of the human brain, particularly in individuals with paralysis.
By decoding the activity in the brain using advanced technologies like fMRI and AI, we can unlock a whole new level of insight into how the brain functions. This could pave the way for new treatments and therapies to help those paralyzed, giving them hope for a brighter future. The possibility of turning dreams into reality is no longer a distant dream but a tangible goal we can work towards.