Yeah, but can it play… y’know what, I’m not even gonna go there.
Category: supercomputing
Brain cells simulated in the electronic brain
Europe now has an exascale supercomputer which runs entirely on renewable energy. Of particular interest: one of the 30 inaugural projects for the machine focuses on realistic simulations of biological neurons (see https://www.fz-juelich.de/en/news/effzett/2024/brain-research)
[ https://www.nature.com/articles/d41586-025-02981-1](https://www.nature.com/articles/d41586-025-02981-1)
Large language models (LLMs) work with artificial neural networks inspired by the way the brain works. Dr. Thorsten Hater (JSC) is focused on the nature-inspired models of LLMs: neurons that communicate with each other in the human brain. He wants to use the exascale computer JUPITER to perform even more realistic simulations of the behaviour of individual neurons.
Many models treat a neuron merely as a point that is connected to other points. The spikes, or electrical signals, travel along these connections. “Of course, this is overly simplified,” says Hater. “In our model, the neurons have a spatial extension, as they do in reality. This allows us to describe many processes in detail on the molecular level. We can calculate the electric field across the entire cell. And we can thus show how signal transmission varies right down to the individual neuron. This gives us a much more realistic picture of these processes.”
For the simulations, Hater uses a program called Arbor. This allows more than two million individual cells to be interconnected computationally. Such models of natural neural networks are useful, for example, in the development of drugs to combat neurodegenerative diseases like Alzheimer’s. The physicist and software developer would like to simulate and study the changes that take place in the neurons in the brain on the exascale computer.
Elon’s Cryptic Post Sparks Big Questions
Questions to inspire discussion.
🌐 Q: What distinguishes embedded AI from language models like ChatGPT? A: Embedded AI interacts with the real world, while LLMs (Large Language Models) primarily answer questions based on trained information.
Chip Production and Supply.
💻 Q: What are Samsung’s plans for chip production in Texas? A: Samsung’s new Texas chip plant will produce 2nm chips with 16,000 wafers/month by the end of 2024, boosted by a $16B Tesla deal.
🔧 Q: How will the Samsung-Tesla deal impact Tesla’s chip supply? A: The deal will significantly boost Tesla’s chip supply, producing 17,000 wafers per month of 2 nanometer chips reserved solely for Tesla.
AI Infrastructure and Applications.
Elon Musk Pushes Tesla Forward
Questions to inspire discussion.
📷 Q: What camera technology does the Optimus bot use? A: Optimus uses car cameras with macro modes for reading small text, supplied by Simco (a Samsung division), featuring a miniaturized camera assembly with internal movement mechanisms.
Tesla AI and Chip Development.
🧠 Q: How does Tesla’s AI5 chip compare to competitors? A: The AI5 chip is potentially the best inference chip for models under 250 billion parameters, offering the lowest cost, best performance per watt, and is milliseconds faster than competitors.
💻 Q: What advantages does Tesla have in chip development? A: Tesla controls the chip design, silicon talent, and has vertical integration, giving them a significant edge over competitors in AI chip development.
Tesla Product and Business Updates.
Elon Musk’s Drops Hints About His Next Master Plan
Questions to inspire discussion.
AI and Supercomputing Developments.
🖥️ Q: What is XAI’s Colossus 2 and its significance? A: XAI’s Colossus 2 is planned to be the world’s first gigawatt-plus AI training supercomputer, with a non-trivial chance of achieving AGI (Artificial General Intelligence).
⚡ Q: How does Tesla plan to support the power needs of Colossus 2? A: Elon Musk plans to build power plants and battery storage in America to support the massive power requirements of the AI training supercomputer.
💰 Q: What is Musk’s prediction for universal income by 2030? A: Musk believes universal high income will be achieved, providing everyone with the best medical care, food, home, transport, and other necessities.
🏭 Q: How does Musk plan to simulate entire companies with AI? A: Musk aims to simulate entire companies like Microsoft with AI, representing a major jump in AI capabilities but limited to software replication, not complex physical products.
What came before the Big Bang? Supercomputers may hold the answer
Scientists are rethinking the universe’s deepest mysteries using numerical relativity, complex computer simulations of Einstein’s equations in extreme conditions. This method could help explore what happened before the Big Bang, test theories of cosmic inflation, investigate multiverse collisions, and even model cyclic universes that endlessly bounce through creation and destruction.
Simulations reveal pion’s interaction with Higgs field with unprecedented precision
With the help of innovative large-scale simulations on various supercomputers, physicists at Johannes Gutenberg University Mainz (JGU) have succeeded in gaining new insights into previously elusive aspects of the physics of strong interaction.
Associate Professor Dr. Georg von Hippel and Dr. Konstantin Ottnad from the Institute of Nuclear Physics and the PRISMA+ Cluster of Excellence have calculated the interaction of the pion with the Higgs field with unprecedented precision based on quantum chromodynamics. Their findings were recently published in Physical Review Letters.
Mitsui Works With Quantinuum and QSimulate to Launch Quantum-Integrated Chemistry Platform
Mitsui & Co. has formally launched a new quantum-enabled chemistry platform, QIDO, in collaboration with U.S.-based Quantinuum and QSimulate. The system, designed to accelerate the discovery of new materials and pharmaceuticals, blends classical and quantum computing resources to streamline complex chemical calculation, according to a story in Nikkei and a Quantinuum blog post.
Quantum computers hold promise for modeling chemical reactions beyond the reach of traditional supercomputers. But fully fault-tolerant systems remain years away, leaving companies searching for ways to extract value from today’s noisy, early-stage machines. QIDO, short for Quantum-Integrated Discovery Orchestrator, attempts to bridge that gap.
The platform runs most computations on powerful classical hardware while sending only the most computationally expensive steps — such as the modeling of strongly correlated electrons — to a quantum computer. This hybrid workflow allows companies to perform higher-precision chemical simulations today, without waiting for fully mature quantum systems, Nikkei reports.
New AI model advances fusion power research by predicting the success of experiments
Practical fusion power that can provide cheap, clean energy could be a step closer thanks to artificial intelligence. Scientists at Lawrence Livermore National Laboratory have developed a deep learning model that accurately predicted the results of a nuclear fusion experiment conducted in 2022. Accurate predictions can help speed up the design of new experiments and accelerate the quest for this virtually limitless energy source.
In a paper published in Science, researchers describe how their AI model predicted with a probability of 74% that ignition was the likely outcome of a small 2022 fusion experiment at the National Ignition Facility (NIF). This is a significant advance as the model was able to cover more parameters with greater precision than traditional supercomputers.
Currently, nuclear power comes from nuclear fission, which generates energy by splitting atoms. However, it can produce radioactive waste that remains dangerous for thousands of years. Fusion generates energy by fusing atoms, similar to what happens inside the sun. The process is safer and does not produce any long-term radioactive waste. While it is a promising energy source, it is still a long way from being a viable commercial technology.