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Lets talk about time-dilation. Modern physics discussions always use the same experiment to describe this effect. An atomic clock in a plane disagrees with an atomic clock on the ground. All that would have to happen for this to occur is a slight difference in the rate of electric and magnetic induction. Nothing to do
Understanding the Plasma Confinement Simulation This simulation demonstrates a simplified model of magnetic plasma confinement, similar to what you might find in fusion research devices called “magnetic mirrors.” Let me break down what you’re seeing and what this simulation can (and can’t) show us. What You’re Looking At How It Works The simulation uses several
This visualization shows a plasma system contained within a magnetic field – a common configuration in fusion reactors and plasma physics experiments. Let me break down what you’re seeing: This type of configuration is similar to what’s used in fusion research, where extremely hot plasma needs to be contained without touching the walls of the
Electron Motion in Magnetic Field Let me explain this magnetic field visualization in detail. You’re looking at a three-dimensional simulation that shows how magnetic fields behave around a toroidal (donut-shaped) magnet, along with the motion of electrons within this field. The central donut-shaped object represents the toroidal magnet itself. The magnet has two poles: the
Another WebGL Experiment.
Transformer Model 3D Visualization Click and drag to rotate Scroll to zoom The Blue block is the Input Embeddings, the Red Blocks are Attention Heads, The Large Green Block is the Hidden Feed Forward Network and the Little Green Block is the Feed Forward Network Output.
Abstract This paper proposes a novel approach to reducing the dimensional complexity of Large Language Model (LLM) training by introducing a definition-specific byte encoding system that disambiguates word meanings during the tokenization phase. By attaching a single byte that maps to specific Oxford English Dictionary definitions, we can potentially reduce the embedding dimensions required for
RAG (Retrieval Augmented Generation) is a developing technology for using embedding models to search documents for context based on an embedding generated from the user query. There are problems with the current methods, including loss of contextual information and failure to find relevant information. To circumvent these difficulties, a hybrid keyword search and contextual search
This is a stub to keep a link to the interestingengineering.com‘s article on spinning magnet levitation: “Physicists have deciphered the underlying physics of a perplexing “magnet levitation” phenomenon first reported by a Turkish researcher in 2021. The phenomenon involves the levitation of a nearby magnet caused by the fast rotation of another magnet, which challenges
Particulate and VOC Capture system concept(s): ## Components: ## Coating Process: ## Operational Considerations: ## Safety Measures: ## Potential Enhancements: ## Disposal/Recycling: