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How to Build an Advanced Agentic Retrieval-Augmented Generation (RAG) System with Dynamic Strategy and Smart Retrieval? Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In this tutorial, we walk through the implementation of an Agentic Retrieval-Augmented Generation (RAG) system. We design it so that the agent does more than just retrieve documents; it actively decides when retrieval is needed, selects the best retrieval strategy, and synthesizes responses with… Read More »How to Build an Advanced Agentic Retrieval-Augmented Generation (RAG) System with Dynamic Strategy and Smart Retrieval? Asif Razzaq Artificial Intelligence Category – MarkTechPost

Compute-Optimal Quantization-Aware Training Apple Machine Learning Research

​[[{“value”:”Quantization-aware training (QAT) is a leading technique for improving the accuracy of quantized neural networks. Previ- ous work has shown that decomposing training into a full-precision (FP) phase followed by a QAT phase yields superior accuracy compared to QAT alone. However, the optimal allocation of… Read More »Compute-Optimal Quantization-Aware Training Apple Machine Learning Research

Zhipu AI Releases GLM-4.6: Achieving Enhancements in Real-World Coding, Long-Context Processing, Reasoning, Searching and Agentic AI Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Zhipu AI has released GLM-4.6, a major update to its GLM series focused on agentic workflows, long-context reasoning, and practical coding tasks. The model raises the input window to 200K tokens with a 128K max output, targets lower token consumption in applied tasks, and… Read More »Zhipu AI Releases GLM-4.6: Achieving Enhancements in Real-World Coding, Long-Context Processing, Reasoning, Searching and Agentic AI Asif Razzaq Artificial Intelligence Category – MarkTechPost

Modernize fraud prevention: GraphStorm v0.5 for real-time inference Jian Zhang Artificial Intelligence

​[[{“value”:” Fraud continues to cause significant financial damage globally, with U.S. consumers alone losing $12.5 billion in 2024—a 25% increase from the previous year according to the Federal Trade Commission. This surge stems not from more frequent attacks, but from fraudsters’ increasing sophistication. As fraudulent activities… Read More »Modernize fraud prevention: GraphStorm v0.5 for real-time inference Jian Zhang Artificial Intelligence

OpenAI Launches Sora 2 and a Consent-Gated Sora iOS App Michal Sutter Artificial Intelligence Category – MarkTechPost

​[[{“value”:” OpenAI released Sora 2, a text-to-video-and-audio model focused on physical plausibility, multi-shot controllability, and synchronized dialogue/SFX. The OpenAI team has also launched a new invite-only Sora iOS app (U.S. and Canada first) that enables social creation, remixing, and consent-controlled “cameos” for inserting a verified… Read More »OpenAI Launches Sora 2 and a Consent-Gated Sora iOS App Michal Sutter Artificial Intelligence Category – MarkTechPost

DeepSeek V3.2-Exp Cuts Long-Context Costs with DeepSeek Sparse Attention (DSA) While Maintaining Benchmark Parity Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Table of contents FP8 index → top-k selection → sparse core attention Lets Talk about it’s efficiency and accuracy Summary FAQs DeepSeek released DeepSeek-V3.2-Exp, an “intermediate” update to V3.1 that adds DeepSeek Sparse Attention (DSA)—a trainable sparsification path aimed at long-context efficiency. DeepSeek also… Read More »DeepSeek V3.2-Exp Cuts Long-Context Costs with DeepSeek Sparse Attention (DSA) While Maintaining Benchmark Parity Asif Razzaq Artificial Intelligence Category – MarkTechPost

Meet oLLM: A Lightweight Python Library that brings 100K-Context LLM Inference to 8 GB Consumer GPUs via SSD Offload—No Quantization Required Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” oLLM is a lightweight Python library built on top of Huggingface Transformers and PyTorch and runs large-context Transformers on NVIDIA GPUs by aggressively offloading weights and KV-cache to fast local SSDs. The project targets offline, single-GPU workloads and explicitly avoids quantization, using FP16/BF16 weights… Read More »Meet oLLM: A Lightweight Python Library that brings 100K-Context LLM Inference to 8 GB Consumer GPUs via SSD Offload—No Quantization Required Asif Razzaq Artificial Intelligence Category – MarkTechPost

7 Python Decorator Tricks to Write Cleaner Code Iván Palomares Carrascosa MachineLearningMastery.com

​Usually shrouded in mystery at first glance, Python decorators are, at their core, functions wrapped around other functions to provide extra functionality without altering the key logic in the function being “decorated”. Usually shrouded in mystery at first glance, Python decorators are, at their core, functions… Read More »7 Python Decorator Tricks to Write Cleaner Code Iván Palomares Carrascosa MachineLearningMastery.com