Explainable AI

Books Explainable AI Featured Posts Generative AI Machine Learning Python Statistical Science Visualization

Mesmerizing Video that will Make you Love Math, Engineering, and Probability

  Featuring the roots of various polynomials whose coefficients are the binary digits of numbers like π. Complex roots cluster around the circle, and the few real ones are on the horizontal X-axis (positive on the right, negative on the left). Download the free paper to see how to interpret the colors and get the […]

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Explainable AI Featured Posts Natural Language Processing Podcasts

Podcast with Vincent Granville: Hallucination-Free AI Models

Fireside chat with Vincent Granville, CAIO & Co-Founder at BondingAI.io. Hosted by Benjamin Johnson, CEO & Co-Founder at Particle41. Dive into AI advancements with Vincent Granville, as he reveals breakthrough methods in hallucination-free AI models and synthetic data innovations. Join us in this episode of the Particle Accelerator Podcast as we welcome Vincent Granville, Co-Founder […]

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Explainable AI Featured Posts Generative AI Machine Learning Natural Language Processing Python

xLLM Version 2.0: GitHub Repository with Innovative AI Agents

I am putting all the new code and documentation about xLLM v 2.0 on GitHub, starting with various AI agents. At least, what is open-source and public (there is a lot more behind the public material). All home-made from scratch with radically different technology. You can check the new repository, here. Start with the README […]

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Explainable AI Featured Posts Generative AI Machine Learning Python Statistical Science Stochastic Systems Synthetic Data

Checking for Randomness: Replacing Test Batteries with a Single Test

In cybersecurity applications where replicability is critical, or when building pseudo-random number generators, it is typical to perform a large number of various tests to check if a sequence of bits is random enough for practical purposes. This is also true in scientific research, to assess whether or not the digits of π or other […]

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Cybersecurity Use Case: AI Agent for Anomaly Detection – Part 2

In the first part of this series, here, I feature a click fraud case that we are working on, litigated by one of the largest law firms in the US.  The input data comes from an Excel repository, automatically processed by an AI agent part of our BondingAI enterprise solutions. It comes with insights generation […]

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Deep Learning Explainable AI Featured Posts Generative AI Natural Language Processing Python

xLLM: 30 Articles Shaping the Future of Enterprise AI in 2026

Over several decades, I unlearned everything that I learned in college classes, and built a new discipline from scratch, as much different from traditional AI than it is from standard machine learning, statistics and computer science. Outside academia with a focus on practical applications. Item #2 in the list below is the culmination of this […]

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New Book: No-Blackbox, Secure, Efficient AI and xLLM Solutions

Large language models and modern AI is often presented as technology that needs deep neural networks (DNNs) with billions of Blackbox parameters, expensive and time consuming training, along with GPU farms, yet prone to hallucinations. This book presents alternatives that rely on explainable AI, featuring new algorithms based on radically different technology with trustworthy, auditable, […]

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Explainable AI Featured Posts Machine Learning Python Statistical Science Time Series

Cybersecurity Use Case: AI Agent for Anomaly Detection – Part 1

The case discussed here concerns fraudulent paid clicks to defraud a Google advertiser. The sophisticated click fraud scheme involving clicking viruses, data centers and other means, is undetected by Google. I worked with the law firm involved in the litigation, to build an agent able to pinpoint the sources of fraudulent traffic. The agent processes […]

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Explainable AI Featured Posts Generative AI Python Synthetic Data

How to Build and Optimize High-Performance Deep Neural Networks from Scratch

With explainable AI, intuitive parameters easy to fine-tune, versatile, robust, fast to train, without any library other than Numpy. In short, you have full control over all components, allowing for deep customization, and much fewer parameters than in standard architectures. Introduction I explore deep neural networks (DNNs) starting from the foundations, introducing a new type […]

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Explainable AI Featured Posts Generative AI Natural Language Processing

Differences between transformer-based AI and the new generation of AI models

I frequently refer to OpenAI and the likes as LLM 1.0, by contrast to our xLLM architecture that I present as LLM 2.0. Over time, I received a lot of questions. Here I address the main differentiators. First, xLLM is a no-Blackbox, secure, auditable, double-distilled agentic LLM/RAG for trustworthy Enterprise AI, using 10,000 fewer (multi-)tokens, […]

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