Black holes are enigmatic entities that, despite our extensive knowledge, continue to perplex our comprehension of physics. Physicists have proposed unconventional hypotheses to address the paradoxes encountered during the study of these phenomena. One hypothesis suggests that these paradoxes indicate that our universe is actually a holographic representation. According to this idea, everything we observe and perceive is encoded at the boundary of our universe, which is a three-dimensional representation of a two-dimensional universe, including time. Moreover, there have been suggestions that this could potentially indicate that our universe exists inside a black hole within a larger universe.

Black holes are regions of space that result from the gravitational collapse of massive stars, exhibiting such intense gravity that even light cannot escape. Their presence presented a challenge when examining them from a thermodynamic perspective. After achieving stability, a black hole’s mass, angular momentum, and electric charge are the only factors that determine its final state.

“According to French astrophysicist Jean-Pierre Luminet’s 2016 review, in classical general relativity, a black hole effectively traps any particle or form of radiation within its cosmic confinement, preventing their escape.” “To an external observer, the moment a material body passes through an event horizon, all information regarding its material properties becomes inaccessible.” Only the updated values of mass (M), angular momentum (J), and electric charge (Q) are retained. Consequently, a black hole engulfs a vast quantity of information.

It may appear straightforward—or at least as straightforward as physics can be. However, if a black hole possesses mass (which is typically substantial), it should theoretically possess a temperature in accordance with the first law of thermodynamics. Furthermore, in accordance with the second law of thermodynamics, it should emit thermal radiation. Stephen Hawking demonstrated that black holes emit radiation, now known as Hawking radiation, which is generated at the boundary of a black hole.

“Hawking subsequently identified a paradox.” “If a black hole undergoes evaporation, a fraction of the information it possesses becomes permanently irretrievable,” Luminet elaborated. A black hole’s thermal radiation does not retain or replicate information about the matter it ate. The irrevocable loss of information contradicts one of the fundamental principles of quantum mechanics. The Schrödinger equation states that in physical systems that undergo changes over time, information cannot be created or destroyed. This property is referred to as unitarity.

This phenomenon is referred to as the black hole information paradox, and due to its apparent contradiction with our existing comprehension of the cosmos, it has been extensively examined and discussed.

Examining the thermodynamics of black holes within the context of string theory led to the discovery of an alternative solution. Gerard ‘t Hooft demonstrated that the total number of independent variables within a black hole is directly proportional to the surface area of its horizon, rather than its volume. This enables the examination of the entropy of a black hole.

“In terms of information, Luminet explains that each bit, represented as either a 0 or a 1, corresponds to four Planck areas. This correspondence enables the derivation of the Bekenstein-Hawking formula for entropy,” Luminet concludes. “To an external observer, it appears that the information regarding the entropy of the black hole, which was previously contained within the three-dimensional arrangement of objects that entered the event horizon, is no longer accessible.” However, according to this perspective, the data is encoded on the flat, two-dimensional surface of a black hole, similar to a hologram. Thus, Hooft concluded that the information consumed by a black hole could be fully recovered through the process of quantum evaporation.

Although it is consoling to know that black holes do not violate the second law of thermodynamics, this has given rise to the unusual idea that a three-dimensional space’s two-dimensional boundary can explain its physics.

It has been suggested that the universe itself could potentially function like a black hole, with all phenomena occurring at its boundary and our observations arising from these interactions. However, this concept does not apply to the space outside of a black hole. This idea is quite unconventional, with some unexpected additions. For example, there is a suggestion that gravity may emerge as a force from entanglement entropy at the boundary.

The theory falls short in its ability to provide a convincing explanation for our universe, as standard physics continues to offer the most accurate description of the observable universe. However, there are valid justifications for why individuals consider it of great importance.

In order for the model to be valid, it is crucial that the Hubble radius of the universe, which represents the radius of our observable universe, is equivalent to its Schwarzschild radius. This refers to the size of a black hole that would form if all the matter within it was compressed into a single point. These two figures are unexpectedly similar, although this could be attributed to a cosmic coincidence.

There are other factors to consider, like this comprehensive chart that indicates the possibility of our existence within a black hole within a larger universe. However, until a theory emerges with substantial evidence and predictions that surpass our current knowledge of physics, we recommend refraining from succumbing to an existential crisis. This applies regardless of whether you perceive yourself as a three-dimensional entity existing within conventional space-time or as a holographic projection originating from a two-dimensional boundary within a larger universe.

In a recent practice dogfight, a fighter jet run by artificial intelligence (AI) faced off against a jet run by a human.

The ground-breaking test flight happened in September 2023, but DARPA’s Air Combat Evolution program just recently released video of it.

The video depicts two planes performing a variety of “dynamic combat maneuvers,” such as dogfighting positions nose-to-nose, while flying at 1,931 kilometers per hour (1,200 miles per hour).

For the US Air Force Test Pilot School, Lockheed Martin Skunk Works and Calspan Corporation created the one-of-a-kind AI-guided plane model.

The project was first made as a simulator to help train pilots. It was called the X-62A or VISTA (Variable In-flight Simulator Test Aircraft). The first software had AI, but it could only work in the virtual world, making it more like a very realistic video game.

And things changed in December 2022, when the AI agents were put in charge of a real plane, letting it fly along a flight path on its own. Since then, it has done a lot of real-life test flights and a lot of practice flights, getting ready for its ultimate goal: fighting within visual range, also known as “dogfighting.”

“DARPA looked for the hardest kind of problem it could find when it came to this one, and dogfighting is a great example of how machine learning can be used.” Colonel James Valpiani, commandant of the Air Force Test Pilot School, said in the video, “If machine learning can work well in an environment as dangerous as air-to-air combat, it has a great chance to earn the trust of humans as we look to applications that are less dangerous but equally complex.”

On May 2, 2024, US Secretary of the Air Force Frank Kendall flew on the X-62A jet on an AI-guided flight. This was another sign of the program’s progress.

To not have it is to risk your safety. “We have to have it now,” Kendall told the AP when they got off the plane.

It’s possible that AI-assisted weapons will be more accurate than human-guided ones. This could mean fewer civilian deaths, damage, and friendly fire. But this uncharted territory brings up a lot of legal, moral, security, and humanitarian problems. One big question is whether it is safe or right to leave most of the decision-making about life and death to sensors and software, which are basically killer robots, with little human oversight. Another question is whether AI systems can be held responsible if something goes wrong.

This kind of question still hasn’t been answered, and some people have called for strict rules on militarized AI before it gets out of hand. However, some people think that the AI arms race has already begun and shows no signs of stopping.

People are social animals, and their relationships are complicated and change all the time. Several fields of study and theories have tried to figure out how these social networks work and how they change over time. The social balance theory was one of them. It was first put forward in the 1940s. Using statistical physics, researchers have now been able to prove it.

Just like the name says, social balance theory is based on the idea of balance. People in their networks want and try to keep relationships balanced. There should be rules to keep the system balanced. Relationships that are positive are balanced, but relationships that are negative or mixed are not. The classical model is based on the simple idea that relationships that are good are “friends” and relationships that are bad are “enemies.”

First, a friend of a friend is still a friend. Now, this is a made-up example, so don’t think right away of that friend of yours that you hate. Another rule says that a friend of an enemy is also an enemy, and of course, an enemy of a friend is also an enemy. We need to protect our friends. The last rule is a bit more subtle: a friend of an enemy is a friend of an enemy. It looks like the new analysis mostly meets this need, but the scientists had to add a lot of complexity before they could model it.

It’s finally possible to say that social networks match up with expectations that were set 80 years ago, said Bingjie Hao, the study’s lead author from Northwestern University. “Our results can also be used in many different ways in the future.” Because of how we do math, we can put limits on the connections and take into account what each entity in the system wants. That will help when making models of systems other than social networks.

Two things were very important to the new model: not everyone knows each other in real life, and some people are more positive than others. When you use both constraints, you get a social network that is exactly the same as the one Fritz Heider predicted 80 years ago.

“We always thought this social intuition worked, but we didn’t know why,” said István Kovács, who was the lead author of the study. “All that was left was to do the math.” There have been a lot of studies on this idea, but they don’t all point to the same conclusion. We kept getting it wrong for decades. It’s because real life is hard sometimes. We realized we had to deal with both problems at the same time: “who knows whom” and “some people are just friendlier than others.”

The study has been written up in the Science Advances journal.