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96% Correct Next Token Prediction, with No DNN, no Training, auto-distilled...
Over the last 12 months, I’ve built a model to predict the next token and to suggest synonyms or related queries to a user prompt, with 100% correct predictions on the training set in one shot, without...
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Invitation to Crack Codes Using AI
Could you use AI to crack a cypher? For instance, predict the next bits in bitstreams produced by a high-quality PRNG (pseudo-random generator). Or correctly guessing the next bit in sub-sequences of...
View ArticlexLLM: 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,...
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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...
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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...
View Article10 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....
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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...
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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...
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New Book: State of the Art in GenAI & LLMs — Creative Projects, with Solutions
With 23 top projects, 96 subprojects, and 6000 lines of Python code, this vendor-neutral coursebook is a goldmine for any analytic professional or AI/ML engineer interested in developing superior GenAI...
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New Book: Understanding Deep Learning
By Simon Prince, computer science Professor at the University of Alberta. To be published by MIT Press, Dec 2023. The author shares the associated Jupyter notebooks on his website, here. Very popular,...
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Massively Speed-Up your Learning Algorithm, with Stochastic Thinning
You have to see it to believe it! Imagine a technique where you randomly delete as many as 80% of your observations in the training set, without decreasing the predictive power (actually improving it...
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Data Synthetization: enhanced GANs vs Copulas
Using case studies, I compare generative adversarial networks (GANs) with copulas to synthesize tabular data. I discuss back-end and front-end improvements to help GANs better replicate the correlation...
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New Book: Intuitive Machine Learning and Explainable AI
Intuitive Machine Learning with focus on explainable AI, human-friendly intelligence, powerful visualizations and applications. By Vincent Granville Ph.D, published in September 2022. PDF format, 156...
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Fast Classification and Clustering via Image Convolution Filters
Subtitled “Alternative to Generative Mixture Models”, the full version in PDF format is accessible in the “Free Books and Articles” section, here. It is also described in details in my book “Stochastic...
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New Book: Efficient Deep Learning
Subtitled “Fast, smaller, and better models”. This book goes through algorithms and techniques used by researchers and engineers at Google Research, Facebook AI Research (FAIR), and other eminent AI...
View ArticleAmazing Neural Network Video Demonstration
I recently posted an article featuring a very deep neural network in action (250 layers), see here. Each frame in the video represented one layer, with the signal propagating from one layer to the...
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New Neural Network with 500 Billion Parameters
Google just published a research article about its Pathways Language Model (PaML), a neural network with 500 billion parameters. It is unclear to me how many layers and how many neurons (also called...
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Very Deep Neural Networks Explained in 40 Seconds
Very deep neural networks (VDNN) illustrated with data animation: a 40 second video, featuring supervised learning, layers, neurons, fuzzy classification, and convolution filters. Discussed in details...
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