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…
InTowards AIbyMustafa Genc·Apr 15Running a 35B Model Locally with TurboQuant — What’s Actually Possible Right NowBefore diving in, one important distinction: TurboQuant does not quantize model weights. It compresses the KV cache at inference time. This…A response icon7A response icon7
DhanushKumar·Apr 5TurboQuant : Near-Optimal Vector Quantization Without CodebooksModern machine learning systems especially large language models (LLMs), retrieval systems, and vector databases operate on massive volumes…
Sarvesh Koli·Mar 28Unpacking TurboQuant: The Math Behind Near-Optimal Vector QuantizationVector quantization (VQ) is the backbone of modern AI deployment. Whether you are serving a massive Large Language Model (LLM) or querying…
Tahir·Mar 27TurboQuant vs Traditional Quantization Eliminating Memory Overhead in LLMsTLDR:TurboQuant enables lossless 3-bit KV cache compression with 8x faster attention. Zero memory overhead, no fine-tuning.A response icon1A response icon1
ABV — Applied AI Reviews·Feb 28ConceptLM and the End of Token WorshipA review of ConceptLM, the architecture that teaches language models to plan in discrete semantic chunks before they generate text token by…
