Meet Turbovec: A Rust Vector Index with Python Bindings, and Built on Google’s TurboQuant Algorithm
Source: MarkTechPost Vector search underpins most retrieval-augmented generation (RAG) pipelines. At scale, it gets expensive. Storing 10 million...
How to Build Knowledge Graph Generation Pipelines From Text With kg-gen, NetworkX Analytics, and Interactive Visualizations
Source: MarkTechPost In this tutorial, we will generate knowledge graphs from plain text, conversations, and multiple source documents...
NVIDIA AI Releases Nemotron-Labs-Diffusion: A Tri-Mode Language Model with 6× Tokens Per Forward Over Qwen3-8B
Source: MarkTechPost NVIDIA researchers have released Nemotron-Labs-Diffusion, a language model family that unifies three decoding modes in one...
Meet MemPrivacy: An Edge-Cloud Framework that Uses Local Reversible Pseudonymization to Protect User Data Without Breaking Memory Utility
Source: MarkTechPost As LLM-powered agents move from research to production, one design tension is becoming harder to ignore:...
Stochastic Gradient Descent (SGD’s) Frequency Bias and How Adam Fixes It
Source: MarkTechPost Modern language models are trained on data with extremely uneven token distributions. A small number of...
NVIDIA Introduces a 4-Bit Pretraining Methodology Using NVFP4, Validated on a 12B Hybrid Mamba-Transformer at 10T Token Horizon
Source: MarkTechPost Pretraining frontier-scale LLMs in FP8 is now standard practice, but moving to 4-bit floating point has...
A Coding Implementation to Compress and Benchmark Instruction-Tuned LLMs with FP8, GPTQ, and SmoothQuant Quantization using llmcompressor
Source: MarkTechPost In this tutorial, we explore how to apply post-training quantization to an instruction-tuned language model using...
Vercel Labs Introduces Zero, a Systems Programming Language Designed So AI Agents Can Read, Repair, and Ship Native Programs
Source: MarkTechPost Most programming languages were designed for humans who read error messages, interpret warnings, and manually trace...
A Coding Guide Implementing SHAP Explainability Workflows with Explainer Comparisons, Maskers, Interactions, Drift, and Black-Box Models
Source: MarkTechPost In this tutorial, we implement SHAP workflows as a practical framework for interpreting machine learning models...
Nous Research Proposes Lighthouse Attention: A Training-Only Selection-Based Hierarchical Attention That Delivers 1.4–1.7× Pretraining Speedup at Long Context
Source: MarkTechPost Training large language models on long sequences has a well-known problem: attention is expensive. The scaled...