The crystal is able to forever cycle between states without losing energy. Researchers working in partnership with Google may have just used the tech giant's quantum computer to create a completely new phase of matter -- a time crystal. With the ability to forever cycle between two states without ever losing energy, time crystals dodge one of the most important laws of physics -- the second law of thermodynamics, which states that the disorder, or entropy, of an isolated system must always increase. These bizarre time crystals remain stable, resisting any dissolution into randomness, despite existing in a constant state of flux. According to a research article posted July 28 to the preprint database arXiv, scientists were able to create the time crystal for roughly 100 seconds using qubits (quantum computing's version of the traditional computer bit) inside the core of Google's Sycamore quantum processor.

The artificial intelligence (AI) program DeepMind has gotten closer to proving a math conjecture that's bedeviled mathematicians for decades and revealed another new conjecture that may unravel how mathematicians understand knots. The two pure math conjectures are the first-ever important advances in pure mathematics (or math not directly linked to any non-math application) generated by artificial intelligence, the researchers reported Dec. 1 in the journal Nature. Conjectures are mathematical ideas that are suspected to be true but have yet to be proven in all circumstances. Machine-learning algorithms have previously been used to generate such theoretical ideas in mathematics, but thus far these algorithms have tackled problems smaller than the ones DeepMind has cracked. "What hasn't happened before is using [machine learning] to make significant new discoveries in pure mathematics," said Alex Davies, a machine-learning specialist at DeepMind and one of the authors of the new paper.

The artificial intelligence (AI) program DeepMind has gotten closer to proving a math conjecture that's bedeviled mathematicians for decades and revealed another new conjecture that may unravel how mathematicians understand knots. The two pure math conjectures are the first-ever important advances in pure mathematics (or math not directly linked to any non-math application) generated by artificial intelligence, the researchers reported Dec. 1 in the journal Nature. Conjectures are mathematical ideas that are suspected to be true but have yet to be proven in all circumstances. Machine-learning algorithms have previously been used to generate such theoretical ideas in mathematics, but thus far these algorithms have tackled problems smaller than the ones DeepMind has cracked. "What hasn't happened before is using [machine learning] to make significant new discoveries in pure mathematics," said Alex Davies, a machine-learning specialist at DeepMind and one of the authors of the new paper.

The same fundamental platform that allows Schrödinger's cat to be both alive and dead, and also means two particles can "speak to each other" even across a galaxy's distance, could help to explain perhaps the most mysterious phenomena: human behavior. Quantum physics and human psychology may seem completely unrelated, but some scientists think the two fields overlap in interesting ways. Both disciplines attempt to predict how unruly systems might behave in the future. The difference is that one field aims to understand the fundamental nature of physical particles, while the other attempts to explain human nature -- along with its inherent fallacies. "Cognitive scientists found that there are many'irrational' human behaviors," Xiaochu Zhang, a biophysicist and neuroscientist at the University of Science and Technology of China in Hefei, told Live Science in an email.

You could see it answered in an interactive conversation powered by artificial intelligence (AI) and using video responses that Shatner prerecorded. This two-way conversational video platform was developed by StoryFile, and the company recently introduced the "conversation" with Shatner on its website as a way to commemorate the actor's 90th birthday this past spring. In the video, a jovial-looking Shatner sits in a room awaiting users' questions about his life and career, which can be posed as audio or text. Once Shatner is asked a question, the system swiftly selects an appropriate answer from the prerecorded options, providing the response in real time. The company recorded Shatner's answers in front of a greenscreen at StoryFile's studio in Los Angeles over four days; questions covered various topics, including details of his life story, according to a behind-the-scenes video that StoryFile shared March 22 on Vimeo.

Artificial intelligence could lead to an Orwellian future if laws to protect the public aren't enacted soon, according to Microsoft President Brad Smith. Smith made the comments to the BBC news program "Panorama" on May 26, during an episode focused on the potential dangers of artificial intelligence (AI) and the race between the United States and China to develop the technology. The warning comes about a month after the European Union released draft regulations attempting to set limits on how AI can be used. There are few similar efforts in the United States, where legislation has largely focused on limiting regulation and promoting AI for national security purposes. "I'm constantly reminded of George Orwell's lessons in his book '1984,'" Smith said.

A new map of dark matter made using artificial intelligence reveals hidden filaments of the invisible stuff bridging galaxies. The map focuses on the local universe -- the neighborhood surrounding the Milky Way. Despite being close by, the local universe is difficult to map because it's chock full of complex structures made of visible matter, said Donghui Jeong, an astrophysicist at Pennsylvania State University and the lead author of the new research. "We have to reverse engineer to know where dark matter is by looking at galaxies," Jeong told Live Science. Dark matter is a mysterious, invisible substance that interacts with visible matter via gravity.

Almost like animated, moving portraits in the Harry Potter franchise, photos once frozen in time are being brought to life with an artificial intelligence (A.I.) program called Deep Nostalgia. The technology, which was released on February 25 by the genealogy website MyHeritage, has since gone viral. Social media users have created lifelike moving portraits of mathematician Alan Turing, abolitionist Frederick Douglass and physicist Marie Curie, reports Mindy Weisberger for Live Science. The historical figures can blink, move their heads side-to-side, and even smile. The tech is also being used to animate artwork, statues and photos of ancestors.

DARPA, the Department of Defense's research arm, is paying scientists to invent ways to instantly read soldiers' minds using tools like genetic engineering of the human brain, nanotechnology and infrared beams. Thought-controlled weapons, like swarms of drones that someone sends to the skies with a single thought or the ability to beam images from one brain to another. This week, DARPA (Defense Advanced Research Projects Agency) announced that six teams will receive funding under the Next-Generation Nonsurgical Neurotechnology (N3) program. Participants are tasked with developing technology that will provide a two-way channel for rapid and seamless communication between the human brain and machines without requiring surgery. "Imagine someone who's operating a drone or someone who might be analyzing a lot of data," said Jacob Robinson, an assistant professor of bioengineering at Rice University, who is leading one of the teams.

Astronauts on NASA's Apollo missions to the moon captured astounding movies of the lunar surface, but recent enhancements with artificial intelligence (AI) have really made the films out of this world. In remastered movies shared online by by DutchSteamMachine, a YouTube channel run by a film restoration specialist in the Netherlands, details from lunar scenes are astonishingly crisp and vivid; from mission commander Neil Armstrong's first steps on the moon in 1969 to bumpy lunar rover drives during Apollo 15 and 16 in 1971 and 1972, respectively. The film restorer behind DutchSteamMachine, who also goes by "Niels," used AI to stabilize shaky footage and generate new frames in NASA moon landing films; increasing the frame rate (the number of frames that play per second) smoothed the motion and made it look more like movement in high-definition (HD) video. Related: Can machines be creative? The Apollo program launched 11 lunar spaceflight missions between 1968 and 1972; of those, four missions tested equipment and six landed on the moon, allowing 12 men to walk, drive and/or leap over the dusty, cratered lunar surface, according to NASA.