Twitter, recommendation engine approach

Twitter, as any social media environment has a mechanism to decide what content recommends you. Right now, if you are using Twitter and are under “For you” tab, the content shown is recommended by an engine. In the original map I have from Twitter this capability is shown here: The recommendation code will be opened … Read more

Fully Homomorphic Encryption

This post is a summary of this video titled: Privacy Preserving Machine Learning with Fully Homomorphic Encryption, done by Jordan Fréry. Abstract In today’s digital age, protecting privacy has become increasingly difficult. However, new developments such as Fully Homomorphic Encryption (FHE) provide a means of safeguarding sensitive client information. We are excited to present Concrete-ML, … Read more

OpenAI’s Foundry

This post is a second version of the map drawn on the post Microsoft, Google, Chat GPT, Bard and other things. The pricing table Last week a pricing deck of OpenAI models have been leaked, and it’s an interesting information to understand what is potentially coming on the prompt industry. So in a nutshell: How … Read more

Olympic games

Background This is a series of Wardley Maps trying to explore outside the competitive landscape. Using the Olympic Game as example. Starting in 1988 (it’s what I remember). Purpose: Show my view about how a country pride event turned into a commercial event. I don’t like to do maps alone, so feedback is welcomed. Seoul … Read more

The limits of Wardley Maps doctrines

Wardley Map doctrines are very useful and to work on them. It’s a good basis to work on the right environment. Saying it, in my opinion, the doctrines have some aspects that the person using it needs to take into consideration: To be completed