Category: AI
Large Language Models & Vector Stores, it takes two to tango
Large Language Models (LLMs) need to compare and search text based on meaning. Thus, they must transform the text in units that allow processing and storing efficiently. Furthermore, since the processing is heavy, there are many parameters, and the amount of data to process is large, LLMs need a storage solution, vector store, that optimises…
Artificial Intelligence in Speculative Fiction
Review of a few Speculative Fiction stories that show a concern about our obsession with Artificial Intelligence and other digital technologies. They unveil the dark side of those machines that interfere in our life and thoughts, and which may become an additive technology. They also expose the fantasies about absolute power that may raise in…
Takeaways from a Microsoft engineer about ML on Azure
Takeaways on how to run ML projects on Azure from a Microsoft engineer – author of the Azure Data Scientist Associate Certification Guide.
Andreas Botsikas – Microsoft engineer, author of the Azure Data Scientist Guide
“ML models are in fashion, such as customer churn predictions. However, it’s not easy to define what a churned customer is unless you have a multi subscription system like Netflix, where you can quickly identify the customers who stopped paying. E.g., what does churn mean for a supermarket?”
Lessons learnt with a Google engineer to leverage data for business
Leverage data and Machine Learning for business. Lessons learnt with a Google Engineer about real-world implementations.
Héctor Parra – A Google Engineer and the exciting realities of ML
“The COVID pandemic has spoiled many forecasting models. We can’t use historical data to predict a scenario that has never happened before. Many companies have not included data from 2021 to train their models because it’s biased”.
