I’m writing a book on Retrieval Augmented Generation (RAG) for Wiley Publishing, and vector databases are an inescapable part of building a performant RAG system. I selected Qdrant as the vector…
Traditional correlation coefficients such as Pearson ρ, Spearman, or Kendall’s τ are limited to finding linear or monotonic relationships and struggle to identify more complex association structures…
Nvidia’s stock price has skyrocketed because of its GPU’s dominance in the AI hardware market. However, at the same time, TPUs, well-known AI hardware from Google, are not for sale. You can only rent…
Principal components analysis is a variance decomposition technique that is frequently used for dimensionality reduction. A thorough guide to PCA is available here. In essence, each principal…
When using Gradio for the first time, you’ll likely end up using the Interface method to display your GUI. The reason for this is the simplicity it offers and if your page layouts are uncomplicated…
In the first part of this series, we've discussed the basic ideas of computer simulations and how you can leverage them to answer "what-if" questions. It's impossible to talk about simulations…
The transformer neural architecture is state-of-the-art. It scales very well, i.e., the larger models learn better, and is efficient to train thanks to the parallel computation of the attention.
Business stakeholders are starting to recognise the value machine learning models bring to their operations, gaining a deeper understanding of their benefits and drawbacks. Simultaneously, there’s a…
Our focus this week was on real-world testing and fine-tuning of LLama-3 and Phi-3, as well as some exciting progress in medical AI. We have been monitoring resounding positive feedback on LLama-3…
Enhancing Direct Answer Accuracy in RAG Setup with Self-Retrieval Mechanisms. Leveraging the power of LLMs to significantly enhance the quality of document context retrieved for direct answer generation in your RAG….
