AI/ML Techniques

5 Lessons Learned Building RAG Systems

Retrieval augmented generation (RAG) is one of 2025's hot topics in the AI landscape.

1 week ago

Understanding RAG Part X: RAG Pipelines in Production

Be sure to check out the previous articles in this series: •

1 week ago

Defending against Prompt Injection with Structured Queries (StruQ) and Preference Optimization (SecAlign)

Recent advances in Large Language Models (LLMs) enable exciting LLM-integrated applications. However, as LLMs have improved, so have the attacks…

2 weeks ago

Understanding RAG Part IX: Fine-Tuning LLMs for RAG

Be sure to check out the previous articles in this series: •

2 weeks ago

How to Perform Scikit-learn Hyperparameter Optimization with Optuna

Optuna is a machine learning framework specifically designed for automating hyperparameter optimization , that is, finding an externally fixed setting…

2 weeks ago

5 Reasons Why Traditional Machine Learning is Alive and Well in the Age of LLMs

Nowadays, everyone across AI and related communities talks about generative AI models, particularly the large language models (LLMs) behind widespread…

2 weeks ago

Repurposing Protein Folding Models for Generation with Latent Diffusion

PLAID is a multimodal generative model that simultaneously generates protein 1D sequence and 3D structure, by learning the latent space…

2 weeks ago

Example Applications of Text Embedding

This post is divided into five parts; they are: • Recommendation Systems • Cross-Lingual Applications • Text Classification • Zero-Shot…

2 weeks ago

Using Auto Classes in the Transformers Library

This post is divided into three parts; they are: • What Is Auto Classes • How to Use Auto Classes…

2 weeks ago

Text Embedding Generation with Transformers

This post is divided into three parts; they are: • Understanding Text Embeddings • Other Techniques to Generate Embedding •…

3 weeks ago