Aayushi Patel·Jul 8ANN Algorithms in Vector Search — HNSW, Inverted File Index, and PQ ExplainedModern AI systems rely heavily on vector search to find semantically similar items across large datasets. Whether you’re building semantic…
Alex·May 24TurboQuant: Near-Optimal Vector QuantizationHow a random rotation and a Beta distribution unlock information-theoretically tight quantization for KV caches and nearest-neighbor…
InData Reply IT | DataTechbyGregorio Nicora·May 20TurboQuant: Near-Optimal Vector Quantization for LLM Inference EfficiencyA deep dive into Google’s new vector quantization method that challenges the information-theoretic limits of compressing high-dimensional…
Kaushik Gandhi·Apr 24Sound Meets Sense: How Split RVQ Lets AI Hear Both “What” and “How”As we move toward a world of “native” voice AI, the biggest challenge is how to feed high-bandwidth, continuous audio into Large Language…
Sundar Ram Subramanian·Apr 23Decoding EnCodec for MusicGenIn my previous articles, I explained how LoRA helps us adapt large pretrained models efficiently, without retraining everything from…
