New Book: 0 and 1 – From Elemental Math to Quantum AI
The book is available on our E-store, here. It all started with the number 1. This e-book offers a trip deep into the most elusive and fascinating multi-century old conjecture in number theory: are the binary digits of the fundamental math constants evenly distributed? No one even knows if the proportions of ‘0’ and ‘1’ […]
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Quantum Dynamics, Logistic Map, and Digit Distribution of Special Math Constants
Using the logistic map instead of the base quadratic system as in paper 53 (here), I obtain very similar quantum dynamics, this time for the function sin2(√x) instead of exp(x). When x is a small integer or a product of consecutive primes, my framework reveals new insights on the digit distribution of major math constants. […]
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Doing Better with Less: LLM 2.0 for Enterprise
Standard LLMs are trained to predict the next tokens or missing tokens. It requires deep neural networks (DNN) with billions or even trillions of tokens, as highlighted by Jensen Huang, CEO of Nvidia, in his keynote talk at the GTC conference earlier this year. Yet, 10 trillion tokens cover all possible string combinations; the vast […]
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What is LLM 2.0?
LLM 2.0 refers to a new generation of large language models that mark a significant departure from the traditional deep neural network (DNN)-based architectures, such as those used in GPT, Llama, Claude, and similar models. The concept is primarily driven by the need for more efficient, accurate, and explainable AI systems, especially for enterprise and […]
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LLMs – Key Concepts Explained in Simple English, with Focus on LLM 2.0
The following glossary features the main concepts attached to LLM 2.0, with examples, rules of thumb, caveats, best practices, contrasted against standard LLMs. For instance, OpenAI has billions of parameters while xLLM, our proprietary LLM 2.0 system has none. This is true if we consider a parameter as a weight connecting neurons in a deep […]
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10 Must-Read Articles and Books About Next-Gen AI in 2025
You could call it the best kept secret for professionals and experts in AI, as you won’t find these books and articles in traditional outlets. Yet, they are read by far more people than documents posted on ArXiv or published in scientific journals, so not really a secret. Actually, one of these books is also […]
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