May 2025

Discrete Diffusion: Continuous-Time Markov Chains

Discrete Diffusion: Continuous-Time Markov Chains

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This post, intended to be the first in a series related to discrete diffusion models, has been sitting in my drafts for months. I thought that Google’s release of Gemini Diffusion might be a good occasion to finally publish it. While discrete time Markov chains – sequences of random variables in which the past and future are independent given the present – are rather well known in machine learning, fewer people ever come across their continuous cousins. Given […]

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GenAI, AI Agents and Agentic AI what are the differences and best use cases part 2

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This 2nd episode on a 2 part series analyzes how GenAI has evolved to deliver automation through AI Agents and Agentic AI. It highlights the differences between both of them citing many sources from IBM, Anthropic McKinsey and Gartner amongst others as well as their best use cases and differences and also mentioning some of the risks. 1. Generative AI (GenAI) Generative AI refers to reactive systems that wait for user input, typically a prompt, to generate content1. […]

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GenAI, AI Agents and Agentic AI what are the differences and best use cases part 1

⋅

This first episode on a 2 part series analyzes how GenAI has evolved to deliver automation through AI Agents and Agentic AI. It highlights the differences between both of them citing many sources from IBM, Anthropic McKinsey and Gartner amongst others as well as their best use cases and differences and also mentioning some of the risks. 1. Generative AI (GenAI) Generative AI refers to reactive systems that wait for user input, typically a prompt, to generate content1. […]

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