Artificial intelligence turns people's thoughts into pictures with an accuracy of 80%!

The new AI-powered algorithm reconstructed about 1,000 images, including a teddy bear and an airplane, from these brain scans with an accuracy of 80%.

Researchers from Osaka University used the famous stable diffusion model, embedded in OpenAI's DALL-E 2, which can generate any images based on text input.

The team showed the participants individual sets of images and functional magnetic resonance imaging (fMRI) scans, which the AI ​​then decoded.

The team participated in the study published in bioRxiv: "We showed that our method can reconstruct high-resolution images with high semantic fidelity from human brain activity. And unlike previous studies of image reconstruction, our method does not require training or fine-tuning of complex deep learning models."

The algorithm pulls information from parts of the brain involved in image perception, such as the temporal lobes, according to Yu Takagi, who led the research.

The team used fMRI because it picks up blood flow changes in active brain regions, Science.org reports.

And FMRI can detect oxygen molecules, so the scanners can see where neurons — brain nerve cells — are working harder (and pulling in the most oxygen) while we're having thoughts or emotions.

A total of four participants were used in this study, each showing a set of 10,000 images.

The AI ​​begins by creating the images as noise similar to static TV, which is then replaced by discernible features that the algorithm sees in activity by pointing to the images it was trained on and finding a match.

According to the study, we show that our simple framework can reconstruct high-resolution images (512 x 512) of brain activity with high semantic accuracy. We quantitatively interpret each component of LDM from a neuroscience perspective by mapping specific components to distinct brain regions. We provide an objective explanation of how the text-to-image process implemented by the LDM [Latent Diffusion Model] integrates the semantic information expressed by the conditional text while preserving the appearance of the original image.

The combination of artificial intelligence and brain scanning devices has been a hit among the scientific community, which they believe hold new keys to unlocking our inner worlds.

In a November study, scientists used the techniques to analyze the brainwaves of non-verbal and paralyzed patients and convert them into sentences on a computer screen in real time.

The "mind-reading" machine can decode brain activity when a person silently tries to spell words out loud to create complete sentences.

Researchers from the University of California said that the communication neuron has the potential to restore communication in people who are unable to speak or write due to paralysis.

In tests, the device decoded a volunteer's brain activity as he tried to silently speak each phonetic letter to produce sentences from a vocabulary of 1,152 words at a speed of 29.4 characters per minute and an average letter error rate of 6.13 percent.

In other experiments, the researchers found that the approach generalized to large vocabulary containing more than 9,000 words, with an average error rate of 8.23%. Source: Daily Mail

To save physics, experts suggest we need to assume that the future can influence the past!

In 2022, the Nobel Prize in Physics is awarded for experimental work that shows the quantum realm must crack some of our basic intuitions about how the universe works.

Many look at these experiences and conclude that they defy "locality"—the intuition that distant objects need a physical medium to interact. Indeed, the mysterious association between distant particles would be one way to interpret these experimental results.

Others believe instead that the experiences defy "realism" — the intuition that there is an objective state underlying our experience. After all, experiments are difficult to interpret only if our measurements are believed to correspond to something real.

Either way, many physicists agree about the so-called "death experience" of local realism.

But what if both of these intuitions could be salvaged, at the cost of a third?

A growing group of experts believes that we should instead abandon the assumption that current actions cannot influence past events. Called "retro-causal," this option claims to save both space and realism.

Let's start with the line everyone knows: correlation is not causation. Some of the associations are causal, but not all. What is the difference?

Consider two examples. (1) There is a relationship between the barometer needle and the weather - that is why we learn about the weather by looking at the barometer. But no one believes that the barometer needle causes the weather. (2) Drinking strong coffee is associated with a higher heart rate. Here it seems right to say that the first causes the second.

The difference is that if we "shake" the barometer needle, we won't change the weather. Both the barometer needle and the weather are controlled by a third element, atmospheric pressure - which is why they are related to each other. When we control the needle ourselves, we break the link with the pneumatics, and the link disappears.

But if we intervene to change someone's coffee consumption, we usually change their heart rate as well. Causal associations are those that linger when we twist a variable.

These days, the science of looking for these strong connections is called causal discovery. It's a great name for a simple idea: discovering what else changes when we twist things around us.

In ordinary life, we usually assume that the effects of an oscillation will appear later than the oscillation itself. This is such a natural assumption that we don't even notice that we're making it.

But there is nothing in the scientific method that requires this to happen, and it can easily be given up in the imagination.

We imagine that something we do now can affect something in the past. This is retrograde.

Quantum causation

The quantum threat to region (that distant objects need a physical medium to interact) stems from an argument by the Northern Irish physicist John Bell in the 1960s.

Bell looked at experiments in which two hypothetical physicists, Alice and Bob, received particles from a common source. Each selects one of several measurement settings, and then records the measurement result. The experiment is repeated several times, and a list of results is generated.

And Bell realized that quantum mechanics predicted (now confirmed) strange correlations in this data. They seem to imply that Alice's choice of setting has a subtle "non-local" effect on Bob's score, and vice versa - even though Alice and Bob may be light years apart.

Bell's argument is said to pose a threat to Albert Einstein's special theory of relativity, which is an essential part of modern physics.

But that's because Bell assumed that quantum particles don't know what measurements they will encounter in the future. Retrograde models suggest that Alice and Bob's measurement choices affect the particles at the source. This can explain the strange correlations, without breaking special relativity.

In recent work, he proposed a simple mechanism for the odd relationship — it involves a familiar statistical phenomenon called Berkson bias.

There is now a group of scientists working on quantum causation. But it is still not visible to some experts in the broader field. It is confused with a different view called "superdeterminism".

Super determinism

Superdeterminism agrees with retrocausality that measurement choices and fundamental properties of particles are interconnected in some way.

But superdeterminism treats it like the correlation between weather and a barometer needle. It assumes that there is a mysterious third thing - a "superdeterminant" - that controls and connects both our choices and particles, and the way atmospheric pressure controls both the weather and the barometer.

So superdeterminism denies that measurement choices are things we are free to move at will, because they are predetermined. Free vibrations may break the link, just as in the case of a barometer.

Critics object that superdeterminism undermines the basic assumptions needed to conduct scientific experiments. They also say that this means denying free will, because something controls both measurement and particle choices.

These objections do not apply to causation. Causal scientists make causal scientific discoveries in the usual free and vacillating way. And we say that the people who reject causation are the ones who forget the scientific method, if they refuse to follow the evidence that leads to it.

Critics demand experimental evidence, but that's the easy part: Relevant experiments just won a Nobel Prize. The difficult part is showing that reference to causation gives the best explanation for these results.

She mentioned the possibility of removing the threat to Einstein's special relativity. This is a pretty big tip, and it's surprising that it took me so long to explore it. Confusion with hyperdeterminism seems to be mainly to blame.

In addition, the researchers argued, retrocausality makes better sense of the fact that the microscopic world of particles does not care about the difference between the past and the future. The biggest concern about going back is the possibility of sending signals to the past, which opens the door to the paradoxes of time travel.

But to make a paradox, the effect must be measured in the past. And if our young grandmother couldn't read our advice to avoid marrying grandfather, which means we wouldn't exist, there is no contradiction. In the quantum case, it is well known that we can never measure everything at once.

There is still work to be done in devising concrete retro-models that impose the limitation that you can't measure everything at once.

So at this point, it's reactionary causation that blows the wind in its sails, so they head for the ultimate prize of all: saving space and realism from "death by experience."

The report was prepared by Hu Price, Honorary Fellow of Trinity College, University of Cambridge, and Ken Wharton, Professor of Physics and Astronomy, San Jose State University. Source: ScienceAlert

The Russian army acquires a "silent" submarine armed with Kalibr cruise missiles

The Russian Ministry of Defense announced that the Army Navy will acquire a new submarine of the "Lada" type equipped with Kalibr long-range cruise missiles.

During a video conference meeting with the country's military leaders, Russian Defense Minister Sergei Shoigu said: "The Russian army's Northern Fleet will acquire a 'Lada' type Kronstadt submarine. This submarine will be equipped with Caliber winged missiles and the latest sonar navigation and reconnaissance systems."

Russia began developing this submarine in 2005 within the framework of Government Project No. 677 in the Russian Admiralty Shipyards, and it launched it into the water for the first time in 2018, and subjected it to a series of tests over the past three years.

The Lada submarines that Russia is developing within the framework of Project 677 belong to the category of fourth-generation submarines, and they are powered by diesel and electric engines that make very low noise levels during movement, which makes these submarines undetectable by the enemy.

The length of a submarine of this type is 66.8 m, its width is 7.1 m, and its displacement of water is equivalent to 1765 tons. These submarines can work away from their bases on missions that last for 45 days, and the movement is at a speed of 21 nautical knots, in addition to that they are armed with six platforms to launch torpedoes of caliber 533 mm. Source: Russia's weapon