LLM News and Articles

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Sunday, 2025-09-28
17:54From Heat to Language: The Fourier Lineage
16:48Top 5 Essential Python Scripts for Data Analytics
16:38ChatGPT told me I should quit my job
16:31LangChain to Lite Chains
16:12Understanding Linear Attention
16:05Veo 3’s Visual Reasoning: A GPT-3 Moment or Old Wine in a New Bottle?
16:01Beyond ChatGPT: 8 AI Model Types That Are Shaping 2025
16:00Let’s Look at RAG Again
15:51LLM responds filtering
15:50Bots in the Basement: How AI Could Break the Incel Spiral
15:45Demystifying AI Jargon: LLMs, Gen AI, and Agentic AI Explained for Curious Beginners
15:42LLM agents need sites to respect 'Accept: text/plain'
15:36Claude Code Context Management: If You’re Not Managing Context, You’re Losing Output Quality
15:35Wow!!! Analog In-Memory Computing: 100× Faster, 10,000× More Efficient LLMs (Nature Computational…
15:31Exploring research paper on Financial Knowledge Large Language Model
15:29Asynchronous LLM computations specifications with LLM:Graph
15:05Seven Counterintuitive Observations About AI Writing
15:01The Complete Open-Source AI Agent Stack: From Zero to Production
14:37Small Language Models (SLMs): A Complete Guide
14:31Why Gated Residual Networks Matter in Modern LLMs
14:01The 3-Level Prompting System That Transforms AI Into Your Ultimate Thinking Partner
13:49Doğru Kullanım: AI Modelleri ile Proje Geliştirme
13:23Multimodalities in LLMs: When AI Sees, Listens, and Speaks
12:53LLM Training Pipeline: From Foundation to Chatbot
12:43Deep Learning: How Machines Learn Like Our Brain (Part 2/2)
12:31RAG — The Knowledge Layer That Makes LLMs Truly Useful
12:265 Techniques to Prevent Hallucinations in Your RAG Question Answering
12:02Beyond Vector Search: Testing Whether Knowledge Graphs Are RAG’s Missing Piece”
10:55The ADK Prompting Pattern: Static vs. Turn Instructions
10:51ChromaDB Vector Embeddings RAG Based Smart Search
10:40İnsanlığın Son Sınavı — Büyük Dil Modellerinin Başarım Oranlarının Ölçülmesi & Derin Araştırma
10:37SGMem: The Sentence-Graph Memory that Makes Long-Term Chatbots Actually Remember
10:37SGMem: The Sentence-Graph Memory that Makes Long-Term Chatbots Actually Remember
10:17How to use AI in Google Sheets
10:168 FastAPI Tricks for Low-Latency LLM Backends
10:06A Year Ago And Now. Progress of Llama.cpp on Mainframes (s390x)
10:06Model Context Protocol (MCP) as a Strategic AI Service Layer for your business
09:51RAG vs Fine-Tuning vs Foundation Models: What Works Best for OTT User Personalization?
09:38Richard Sutton, Father of RL, Thinks LLMs Are a Dead End
09:22LLMs: Dead End? AI Pioneer Says ‘Maybe’
09:20The LLM is Just the Brain: Meet the Components That Give It Memory and a Body
09:17From YouTube Caption Frustration to My First AI App: A 90-Day Live Build
09:10LLMs in Recommender Systems: Are They the Next Big Leap for OTT Platforms?
08:22Persistence-First Emergence of Relational Benevolence — an LLM-friendly guide
08:08How Hierarchical Reasoning Models Are Redefining AI: Can a Tiny Model Really Outsmart the Giants?
07:59The great wall of Deep Research: Tongyi Deep Research
07:42I Turned Any REST API into an AI-Powered Chatbot (Without Writing a Backend Twice)
07:26Large Language Model Providers and Exploring LLM and SLM
06:58Day(9/100) Search-R1: How GRPO Trains LLMs to Search and Reason
06:21Top 10 Local LLMs (2025): Context Windows, VRAM Targets, and Licenses Compared
06:18Post-Training Large Language Models
06:07Why Task-Based Evaluations Matter
06:0020 AI Concepts Every Beginner Should Know.
05:40My Journey to Build an AI Meeting Summarizer
05:37Tech Behind MegaLLMs #2: A Simple Guide to the Attention Mechanism
05:32“Next-Gen Smart DB Query Builder: Robust, Accurate, and Typo-Free with Multi-Condition Handling”
05:32The rise of large language models
04:49Do people really make fun of accents? I’m feeling self-conscious after a presentation.
04:25The Truth About Multi-Agent Debate: Majority Voting Is the Key
04:25Query Spelling Correction Overview
04:25Tencent Hunyuan Open-Sources HunyuanImage 3.0: An 80-Billion-Parameter Text-to-Image Model
03:57Putting ChatGPT on the Couch
03:31Adaptive Model Routing, Low Latency
03:31Meta’s AI Reasoning Revolution: Teaching Models to ‘Remember How to Think’
03:21From Chaos to Control: The Architecture of a Scalable AI Agent Framework built using LangGraph
03:18Cloud vs. Local GPU for LLMs
03:07DeepEval: A Simple Way to Test and Evaluate Your LLM Applications
02:44When Silicon Valley Elites Start Researching ‘How Not to Work’
02:44Multi-Agent Large Models: Is Voting More Effective Than Debate?
02:31Fine-Tuning Without Regret
02:17Claude Prompt Trees: My Secret to Contextual Depth
02:04Can you make your Agents to remember things? — State machines for rescue.
02:01Notes, Thoughts, & Synthesis: Your Brain on ChatGPT
01:55Demystifying LangChain, LangGraph, LangSmith & LangFlow: Choosing the Right LLM Tool in 2025
01:31Invoice Extraction — Evaluation — Part 5
01:24️ Why LLMs Need MCP: From Smart Text to Real Assistants
Saturday, 2025-09-27
23:46From RNNs to Attention: Teaching AI to Remember and Focus
23:19LLM reading
22:07AI Challenge #1: Teaching an LLM to Play Chess (Part I)
21:59Comparing Chunking Strategies for RAG: From Naive Splits to Striding Windows
21:21Beyond Checkboxes: Using Large Language Models to Discover Hidden Insights in Open-Text Surveys
21:20QualiAI- Automating Data Validation with LLM
21:15Hands-On LLM Alignment: Coding GRPO from Scratch, Step by Step
21:14Speed vs. Thought: Why o3’s Slower Answers Felt Smarter than Gemini 2.5 Pro
21:06Shrinking AI: How Quantization Makes Neural Networks Faster and Leaner
20:26Pydantic AI — The Secret Weapon for Smarter Python Agents
19:42Jailbreak Arena Part 3: Tools, Agents, and Evaluation — Building LLMs that can act and judge
19:31Using LLMs in Trading
19:10Living the Transition: Memory, Movement, and the Model We Need
18:59The AI Wake-Up Call We All Need: OpenAI Discovers AI Models Can Deliberately Deceive Users
18:57Understanding Multimodal LLMs: The Next Evolution of AI
18:56LLM Observability in the Wild – Why OpenTelemetry Should Be the Standard
18:34Série 16 Técnicas de RAG — Parte 1
18:30Bellekteki Hafiflik: Quantization Nedir ve Bize Ne Kazandırır?
18:27A Dual Perspective — Prompting in Large Language Models
18:13MCP Fundamentals: A Beginner’s Guide to the Future of AI Integration
18:01Context Engineering for LLMs: Build Reliable, Production-Ready RAG Systems
17:51Master Guide to LLM Prompting Techniques: From Zero-Shot to Advanced Chain-of-Thought
17:17The Future of AI Is Small, Specialized, and Efficient
16:51What Are Guardrails for LLMs?
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124