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2 weeks ago | 
datasciencecentral.com | Vincent Granville
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. 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.
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1 month ago | 
flipboard.com | Vincent Granville
New Book: 0 and 1 - From Elemental Math to Quantum AI - DataScienceCentral.comThis book opens up new research areas in theoretical and computational number theory, numerical approximation, dynamical systems, quantum dynamics, …
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1 month ago | 
datasciencecentral.com | Vincent Granville
This book opens up new research areas in theoretical and computational number theory, numerical approximation, dynamical systems, quantum dynamics, and the physics of numbers.
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1 month ago | 
datasciencecentral.com | Vincent Granville
Standard LLMs rely on prompt engineering to fix problems (hallucinations, poor response, missing information) that come from issues in the backend architecture. If the backend (corpus processing) is properly built from the ground up, it is possible to offer a full, comprehensive answer to a meaningful prompt, without the need for multiple prompts, rewording your query, having to go through a chat session, or prompt engineering.
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2 months ago | 
datasciencecentral.com | Jelani Harper |Vincent Granville |Dan Wilson
The quantum leap forward in natural language technologies attributed to foundation models, LLMs, and modern vocal applications of AI is due in no small part to the mastery of the concept of attention. When training and deploying the aforementioned models, attention mechanisms account for several things. One of the most valuable is allowing models to look back at different parts of a conversation or text and determine how that context relates to present inputs (or lines of text).
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2 months ago | 
flipboard.com | Vincent Granville
14 hours agoLast week, OpenAI released Images for ChatGPT which led to an explosion of interest thanks to its ability, in part, to generate Studio Ghibli inspired AI art. It looks like the virality has paid off — CEO Sam Altman posted that the company has added one million users in the last hour alone (he’s …
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2 months ago | 
datasciencecentral.com | Vincent Granville |Dan Wilson
In this article, I discuss the main problems of standard LLMs (OpenAI and the likes), and how the new generation of LLMs addresses these issues. The focus is on Enterprise LLMs. Most of the LLMs still fall in that category. The first ones (ChatGPT) appeared around 2022, though Bert is an early precursor.
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Mar 6, 2025 | 
datasciencecentral.com | Eric Ethridge |Dan Wilson |Bill Schmarzo |Vincent Granville
The rapid development and adoption of artificial intelligence (AI) has been incredible. When it comes to generative AI alone (GenAI), 65% of respondents in a recent McKinsey Global Survey said their companies regularly use the technology, doubling findings from just 10 months earlier. Moreover, three-quarters anticipate that in the years ahead, AI will bring significant or disruptive change to their industries. Without question, AI is rapidly revolutionizing areas of business operations.
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Mar 2, 2025 | 
datasciencecentral.com | Bill Schmarzo |Dan Wilson |Vincent Granville
Growing up, I was fascinated by the Strat-O-Matic baseball game. This strategy-driven baseball simulation board game used dice rolls and individual player statistics (captured on individual playing cards) to recreate realistic game outcomes based on statistical probabilities. And yes, I still have my original game board (what a nerd…).
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Feb 23, 2025 | 
datasciencecentral.com | Bill Schmarzo |Vincent Granville |Dan Wilson
Generative AI (GenAI) has revolutionized content generation, information processing, and decision-making. However, as AI tools like ChatGPT and Bard integrate into daily workflows, a crucial question emerges: How is GenAI affecting critical thinking? A recent research paper published by Microsoft, The Impact of Generative AI on Critical Thinking, explored this issue by surveying 319 knowledge workers and analyzing 936 first-hand examples of AI-assisted tasks.
