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…
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 [C1] What Machines Actually Do (And What They Don’t) Every time you use Google Maps at 5:30 PM, something remarkable happens — and it has nothing to do with intelligence.…
Machine Learning Basics [ML 2.a] Word2Vec: Start of Dense Embeddings When you type a search query into Google or ask Spotify to find “chill acoustic covers,” the system…
Privacy Tech [PET 1.b] Privacy Enhancing Technologies (PETs) — Part 2 Secure Collaboration Without Sharing Raw Data In Part 1, we covered how individual organizations protect data…
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…
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