Machine Learning Basics [ML 2.c] Needle in the Haystack: Embedding Training and Context Rot You’ve probably experienced this: you paste a 50-page document into ChatGPT or Claude, ask a specific question…
Privacy Tech [PET 1.a] Privacy Enhancing Technologies (PETs) — Part 1 How Your Data Gets Protected Every time you browse a website, click an ad, or make a purchase, data flows through…
Machine Learning Basics [ML 1] AI Paradigm Shift: From Rules to Patterns Every piece of software you’ve ever shipped works the same way. A developer thinks through the logic and writes…
Privacy Tech [PET 1] Privacy Enhancing Technologies – Introduction Every time you browse a website, click an ad, make a purchase, or train an ML model, data flows through systems.…
Encryption [EN 1.a] Breaking the “Unbreakable” Encryption – 1 If you’ve spent any time in tech, you’ve heard of AES, RSA, and Diffie-Hellman. We treat them like digital…
Machine Learning Basics [ML 2.b] Measuring Meaning: Cosine Similarity In the previous posts, we established that embeddings turn everything into points in space and that Word2Vec showed how…
How Smart Vector Search Works By Archit Sharma 4 Min Read In the ever-evolving world, the art of forging genuine connections remains timeless. Whether it’s with colleagues, clients, or partners, establishing a genuine rapport paves the way for collaborative success. Read More