LLM News and Articles

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Thursday, 2025-09-11
17:38Qwen3-Next: Towards Ultimate Training and Inference Efficiency
17:21On Tokenization — Learning the Complexities
17:16Bias in LLMs: How It Happens
17:11On Word Embeddings & Vector Databases — Storing More than Just Words
16:54How to turn Claude Code into a domain specific coding agent
16:45Zonos-Hebrew: Fine-Tuning Zonos on SASPEECH with a Phonikud Phoneme Pipeline
16:30MCP — The Missing Elixir for LLMs
16:26The Three Core Skills Every AI Engineer Actually Needs in 2025
16:26The Hidden Truth Behind AI’s Inconsistency: Thinking Machines Reveals the Root Cause and…
15:56How to Write Prompts: 7 Steps to Unlock AI’s Full Potential in 2025
15:34Süni İntellekt, Maşın Öyrənməsi, Dərin Öyrənmə və Generativ Süni İntellektə Baxış
15:10Paragen Technical Delivery Roadmap for Q3–Q4 2025
15:06Show HN: Asxiv.org – Ask ArXiv papers questions through chat
15:05When ‘Environment’ Becomes ‘Evaluation’: The Semantic Inflation of AI Terminology
15:05NotebookLM Updates FAQ and Timeline Features, But User Experience Still Needs Improvement
15:01LAI #92: AI Hype vs. Reality, Deepfake Detection, and Copilot+ PCs
15:01LLMs: Should You Prompt, RAG, or Fine-Tune?
14:56Crafting Multi-Agent RAG Systems with DSPy and GEPA Optimization
14:46How Enterprises Can Audit Their AI Visibility
14:42Network and Storage Benchmarks for LLM Training on the Cloud
14:13“Persistence ≈ Creation”: Why Cooperative Intelligence Can Spread by Natural Law
14:06The AI Banana That’s Eating Photoshop’s Lunch
13:56<The Misfit at Tech’s Cool Kids Table: Why Artists Are Indispensable in the AI Revolution>
13:34AI Mode: how it works and what it means for Ukrainian SEO
12:52LLM’s Simplified — Language Modelling and Decoding
12:52From LLMs(Large Language Models) to LCMs( Large Concept Models)
12:44How GPUs Revolutionize Vector Search: CUDA, cuVS, and Faiss in Action
12:43Small LLMs: When to Prefer 1–8B Models, LoRA/QLoRA, and Low-VRAM Finetuning Recipes
12:37Why RAG is Like a Triple Espresso Shot☕ for Your AI: The Caffeine Boost Your Chatbot Didn’t Know…
12:31A quick take on K8s 1.34 GA DRA: 7 questions you probably have
12:31The Free AI Tool They Don’t Want You to Know About: All LLMs at One Place
12:14A deeper look into using MCP in the enterprise
12:10Supercharge Your Sentence Embeddings: A Tale of Two Loss Functions
12:08Prompt Engineering: O Guia Definitivo para Dominar a Comunicação com IA
12:05When Words Learn to See
11:52Agno vs. LangGraph: Which AI Framework Wins on Speed?
11:52Agno vs. LangGraph: Which AI Framework Wins on Speed?
11:49AI's 4B 'language model' bet looks fragile
11:41LangChain vs. LangGraph: When to Use Which (and Why Not Just Any Framework)
11:38Beyond the Black Box: A Beginner’s Deep Dive into the LLMAD Paper on AI Anomaly Detection
11:33ChatGPT may start alerting authorities about youth considering suicide, says CEO
11:26New Peer-Reviewed Section & Vol. 1 Lexicon Update!
11:20MCP & Agent2Agent — What it is, why you should care, and how to implement them
11:17Implementing Guardrails in an Automated SDR Flow — Line-by-Line Explanation
11:00Supervised Fine-Tuning (SFT) Memorizes, Reinforcement Learning (RL) Generalizes
10:59REFRAG: Rethinking RAG based Decoding in a nutshell
10:45How AI Starts Getting Dark Humor
10:36OpenAI for Greece
10:35LLM Safety: Guide to Responsible AI
10:12From Prediction to Thought
10:08Inter-Head Instability: A Signal of Attention Disagreement in LLMs
09:329 LangChain Tool-Calling Patterns That Survive Traffic
09:25Qolaba.AI and Gemma 3n: Transforming Education in India’s Rural Heartland with Offline AI Learning
09:04Creating larger projects with LLM (as a coder)
08:58LLM-D for Proactive Cybersecurity: Scaling Intelligence on Kubernetes
08:29Best practices for high availability of LLM based on AI gateway
08:26Review of “A Two-Stage Cognitive Architecture for Large Language Models”
08:22Context Rot: How Increasing Input Tokens Impacts LLM Performance
08:10The AIVO 100™ Challenger 50: How AI Elevates Digital-Native Brands Over Legacy Giants
08:10LLM’s Simplified — Feed Forward Network (FFN)
08:05LangChain: Revolutionizing AI Application Development
08:00Unpopular but important #SEO take: LLMs.txt won’t boost your rankings (at least not yet).
07:57Docker AI Runner+OnlyOffice:Install & Run Docker AI Model Runner & Integrate with Onlyoffice.
07:57Docker AI Runner+OnlyOffice:Install & Run Docker AI Model Runner & Integrate with Onlyoffice.
07:46The AI Pricing Crisis: Why 95% of Companies Are Losing Money and Only Cash-Rich Giants Will Survive
07:24Basic Introduction: Who I Am and What I Do
07:19I Built Two AI Apps That Can Read Any Document or Website — In Under 100 Lines of Python
07:14Tuning LLMs Made Simple: RLHF and PPO for Beginners
07:10AI Explained: Insights from the Paper “ Why Language Models Hallucinate”
07:05Agents.md: A Standard for AI Coding Agent Instructions
07:05Crash Course on Vercel AI SDK: Live from Poland
07:05When ‘Environment’ Becomes ‘Evaluation’: The Semantic Inflation of AI Terminology
06:45Meet mmBERT: An Encoder-only Language Model Pretrained on 3T Tokens of Multilingual Text in over 1800 Languages and 2–4× Faster than Previous Models
06:45Advancing SEO with LLM Technology | New Era of Search Intelligence
06:44Stemming vs Lemmatization: How AI Finds the Root of Words
06:36Mira Murati’s Thinking Machines Study: Your LLM Isn’t Creative, It’s Just Broken
06:36From Theory to Reality: Addressing LLM Deployment Challenges for Startups Through My Project
06:219xchat vs ChatGPT, Claude, Hugging Face: pricing, features & best fit (2025)
06:16The Complete Roadmap to Becoming an AI Engineer in 2026
06:01Introduction to RAG
05:57Alibaba’s Trillion-Parameter Giant, Why Qwen 3 Max Feels Like the Future: Picture a model so…
04:54Synthetic data generation with differentially private LLM inference
04:52Building for Agentic AI  - Agent SDKs & Design Patterns
04:36Understanding Fine-Tuning, Zero-Shot, One-Shot, and Few-Shot Learning in Large Language Models
04:31Learning to Build a Voice‑Based AI Interviewer
04:30Monte Carlo: Building Data + AI Observability Agents with LangGraph and LangSmith
04:26How I Built a “Teach Me Anything” AI Tutor with Python in Under 200 Lines
03:54Beyond Accuracy: The Hidden Challenge of Evaluating LLM Explanations
03:43Understanding Transformers Architecture
03:35Byte Pair Encoding (BPE): Power, Pitfalls, and Practical Insights
03:04Quantization Explained: A Concise Guide for LLMs
03:02AgentScope: A Simple, Agent-Oriented Framework for Building LLM Applications
03:01Top GPT OSS API Provider: Finding the Right Match
02:50I Built a Lightweight and Ultra-Fast Webscraping App in Go (and Open-Sourced It)
02:46Part 1: Introduction to Agentic AI — Why Enterprises Should Care
02:16I built Qwen3 from scratch and here’s what I learned(theory)
00:48OpenAI’s gpt-oss Models: Training, Performance, Safety and Access
00:43Mixture-of-Experts (MoE): Design, Benefits & LLMs
00:33Mitigate Context Poisoning in AI Agents Using Context Engineering
00:29Under the Hood of Rerankers: Scoring, Models, and Trade-Offs
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124