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AI training method can drastically shorten time for calculations in quantum mechanics

The close relationship between AI and highly complicated scientific computing can be seen in the fact that both the 2024 Nobel Prizes in Physics and Chemistry were awarded to scientists for devising AI for their respective fields of study. KAIST researchers have now succeeded in dramatically shortening the calculation time of highly sophisticated quantum mechanical computer simulations by predicting atomic-level chemical bonding information distributed in 3D space using a novel approach to teach AI.

Chinese researchers build military AI using Meta’s open-source Llama model — ChatBIT allegedly performs at around 90% of the performance of OpenAI GPT-4 LLM

Chinese researchers with ties to China’s People’s Liberation Army (PLA) have built an AI model called ChatBIT, designed for military applications using Meta’s open-source Llama model. According to Reuters, some researchers are associated with the Academy of Military Science (AMS), the PLA’s top research group.

Three academic papers and several analysts have confirmed the information, with ChatBIT using Meta’s Llama 13B large language model (LLM). This LLM has been modified for intelligence gathering and processing, allowing military planners to use it for operational decision-making.

Quantum-tunneling deep neural network for optical illusion recognition

The discovery of the quantum tunneling (QT) effect—the transmission of particles through a high potential barrier—was one of the most impressive achievements of quantum mechanics made in the 1920s. Responding to the contemporary challenges, I introduce a deep neural network (DNN) architecture that processes information using the effect of QT. I demonstrate the ability of QT-DNN to recognize optical illusions like a human. Tasking QT-DNN to simulate human perception of the Necker cube and Rubin’s vase, I provide arguments in favor of the superiority of QT-based activation functions over the activation functions optimized for modern applications in machine vision, also showing that, at the fundamental level, QT-DNN is closely related to biology-inspired DNNs and models based on the principles of quantum information processing.

This “AI-Generated Game” Blatantly Rips Off Minecraft

The most observant of our readers might have already noticed a small little detail about Oasis, a caveat that only the most eagle-eyed OSINT enthusiasts would catch – it’s basically a 1-to-1 copy of Mojang’s Minecraft.

And those readers would be right. Essentially, the “first AI-generated game” is nothing more than blatant plagiarism of everyone’s favorite sandbox, trained on thousands of hours of Minecraft gameplay and recordings of corresponding user actions, which resulted in a nearly identical, but worse in every aspect, “game” with a similar visual style, UI, gameplay mechanics, fonts, visual effects, animations, and so on.

One thing that doesn’t exist in the original Minecraft but is front and center in Oasis is, of course, AI hallucinations. Those who have tried it confirm that the experience is incredibly unstable, with environments often morphing into something else when not in the player’s direct line of sight, making the “first AI-generated game” a proof of concept at best, something that its creators, to their credit, openly admit, describing the current iteration of Oasis as a “technical demo.”

Controlling skyrmions at room-temperature in 2D topological spin structure technology

The Korea Research Institute of Standards and Science (KRISS) has, for the first time in the world, generated and controlled skyrmions at room temperature in two-dimensional (2D) materials. This achievement reduces power consumption compared to traditional three-dimensional (3D) systems while maximizing quantum effects, making it a core technology for the development of room-temperature quantum computers and AI semiconductors.

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