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Beyond Vector Search: Building a Deterministic 3-Tiered Graph-RAG System
3+ hour, 12+ min ago (924+ words) Making developers awesome at machine learning In this article, you will learn how to build a deterministic, multi-tier retrieval-augmented generation system using knowledge graphs and vector databases. Topics we will cover include: Beyond Vector Search: Building a Deterministic 3-Tiered Graph-RAG…...
Mukund Jha: Emergent democratizes software development for non-technical users, overcomes software testing bottlenecks, and redefines the second mover advantage | Y Combinator Startup Podcast
24+ min ago (287+ words) Mukund Jha is the CEO and Co-Founder of Emergent, an AI platform that enables anyone to build and ship production-ready software. He previously served as CTO of Dunzo, the Indian delivery startup that scaled to millions of users across multiple…...
Vishal Misra: Transformers learn correlations, not causations, the significance of in-context learning, and the role of Bayesian updating in AI | AI + a16z
46+ min ago (162+ words) Understanding transformers' limitations reveals the crucial shift needed from correlation to causation for true AI advancement. Pattern matching is not intelligence; LLMs learn correlation, not causation To get to AGI, we need the ability to keep learning after training Given…...
Microsoft Releases Azure Io T Operations 2603 for Industrial AI Deployments -
5+ hour, 10+ min ago (256+ words) Microsoft Releases Azure Io T Operations 2603 for Industrial AI Deployments'Redmondmag. com Microsoft Releases Azure Io T Operations 2603 for Industrial AI Deployments - Azure Io T Operations 2603 enables AI-driven edge computing for industrial Io T environments. - Update integrates data pipelines, Kubernetes, and…...
How Missions Work
6+ hour, 55+ min ago (709+ words) By Theo Luan - April 10, 2026 - 5 minute read - The architecture behind Missions: why agent context shapes every design decision, how separation of concerns and test-driven development at two levels produce reliable multi-day autonomous work, and how the system actually runs. Agent sessions…...
Fine-Tuning vs Prompt Engineering
4+ hour, 30+ min ago (168+ words) Hacker Noon < 100 M inferences/month: Prompt Engineering " Fixed cost infrastructure dominates 100 M - 1 B inferences/month: Hybrid " Fine-tuning cost per inference becomes significant 1 B inferences/month: Fine-Tuning " Unit economics favour optimised model Frequent changes needed: Prompt Engineering " Update latency matters more…...
Microsoft Doubles Down on In-House AI With MAI Voice, Transcription, and Image Models
9+ hour, 46+ min ago (551+ words) With advancing partnerships and increased interoperability, it's easy to see Microsoft as an enterprise AI gateway rather than a model developer. However, both statements are true, and Microsoft has been slowly building an arsenal of AI models that easily compete…...
A Coding Guide to Markerless 3 D Human Kinematics with Pose2 Sim, RTMPose, and Open Sim
4+ hour, 31+ min ago (1038+ words) In this tutorial, we build and run a complete Pose2 Sim pipeline on Colab to understand how markerless 3 D kinematics works in practice. We begin with environment setup, configure the project for Colab's headless runtime, and then walk through calibration, 2 D…...
What is RAG (Retrieval-Augmented Generation) and How It Works in Real AI Systems
5+ hour, 33+ min ago (337+ words) Large Language Models (LLMs) are powerful. They can write code, generate content, and even simulate reasoning. But they have a serious limitation: They don't actually know your data. Ask an LLM about something outside its training data, and you'll often…...
Incident response automation: from SOAR to agentic AI
1+ day, 2+ hour ago (819+ words) Was der Stryker-Vorfall "ber Handalas Vorgehensweise verr't. Zum Blog " Incident response automation is the practice of using rule-based logic, machine learning, and agentic AI to streamline or autonomously execute the detection, triage, enrichment, containment, and recovery steps of the incident…...
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