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:
Have you ever considered a tree as an electrical system? Certainly there are some insights to be gained by doing so… Check out these related Links! Query 1: Let’s consider plant biology, specifically the electrical properties of living plant cells. Plant cells contain a cell wall, which is a dielectric medium, and interior to this
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This article is a simple set of notes and links for some research into the practicality of spectroscopy methods for use with plastic polymers. “Polycarbonates contain several phenyl-based molecular groups, which are very energy-rich due to the π electrons of the double bond in the ring. In fluorescence, electrons can be lifted into higher energetic
So I decided to create a variant of the SparkOne Bot, using the same client side android application modifying it only slightly to include the necessary changes to switch from using a locally run transformer model to a locally run quantized Llama3 model. This is a screenshot from the client side Application. It features text
Well this is one of my first attempts at working with a docker container in order to isolate various AUR packages and perform patches or version control on dependencies, without interfering with package dependencies on my primary system. Up until this point, I have worked with various virutal python environments when experimenting with AI tools
So I was bored at work and engaged in some loose speculation. This is an idea that the Moon, Mars and suppression of energy technology on Earth are all connected: In the distant past, an advanced civilization thrived on the planet Mars. They developed remarkable technologies, including the ability to tap into the fundamental energy