Synthetic Data – NextGen AI Technology

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 […]

Deep Learning Explainable AI Featured Posts Generative AI Python Synthetic Data

Watermarking and Forensics for AI Models, Data, and Deep Neural Networks

In my previous paper posted here, I explained how I built a new class of non-standard deep neural networks, with various case studies based on synthetic data and open-source code, covering problems such as noise filtering, high-dimensional curve fitting, and predictive analytics. One of the models featured a promising universal function able to represent any […]

Experimental Math Featured Posts Generative AI Python Synthetic Data

How Synthetic Primes Reveal the Quantum States in the Riemann Hypothesis

This research paper showcases spectacular discoveries across multiple disciplines. The main question — yet unanswered — is how the mathematical engineering behind the scenes could be applied to modern AI, deep neural networks (DNNs) and LLMs in particular, to dramatically accelerate the convergence of some slow algorithms. Most notoriously, the laborious and expensive training attached […]

Deep Learning Explainable AI Featured Posts Generative AI Python Synthetic Data

10 Tips to Boost Performance of your AI Models

These model enhancements techniques apply to deep neural networks (DNNs) used in AI. The focus is on the core engine that powers all DNNs: gradient descent, layering and loss function. Reparameterization — Typically, in DNNs, many different parameter sets lead to the same optimum: loss minimization. DNN models are non-identifiable. This redundancy is a strength that […]

Data Sets Deep Learning Explainable AI Featured Posts Generative AI Python Synthetic Data

A New Type of Non-Standard High Performance DNN with Remarkable Stability

I explore deep neural networks (DNNs) starting from the foundations, introducing a new type of architecture, as much different from machine learning than it is from traditional AI. The original adaptive loss function introduced here for the first time, leads to spectacular performance improvements via a mechanism called equalization. To accurately approximate any response, rather […]

Books Experimental Math Featured Posts Python Stochastic Systems Synthetic Data Visualization

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’ […]

Explainable AI Featured Posts Natural Language Processing Synthetic Data

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 […]

Books Courses Data Sets Explainable AI Featured Posts Generative AI Natural Language Processing Python Synthetic Data

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 […]

Data Sets Experimental Math Featured Posts Python Synthetic Data

Universal Dataset to Test, Enhance and Benchmark AI Algorithms

This scientific research has three components. First, my most recent advances towards solving one of the most famous, multi-century old conjectures in number theory. One that kids in elementary school can understand, yet incredibly hard to prove. At the very core, it is about the spectacular quantum dynamics of the digit sum function. Then, I […]

Data Sets Deep Learning Featured Posts Synthetic Data Time Series

Synthesizing Multi-Table Databases: Model Evaluation & Vendor Comparison

Synthesizing multi-table tabular data presents its own challenges, compared to single-table. When the database contains date columns such as transaction or admission date, a frequent occurrence in real-world datasets, generating high quality synthetizations and model evaluation are even more complicated. In this article, we focus on this type of problems, comparing generated observations produced by […]

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