Why Your Local LLM Setup Is Costing More Than You Think — And What Happens When It Breaks
You're three hours into debugging a model quantization issue. The GPU utilization is sitting at 12%. Your M2 Max is running hot, the fans sound like a…
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Linear Ensembles Can Erase LLM Watermarks
Watermarking schemes that embed distributional perturbations into LLM outputs are effectively broken by linear ensembles of a few independently traine…
The Agent Gets the API Key. You Get the Guinea Pig Seat.
A friend texted me this week, and within a year someone you know is going to send you the same message. He had seen that you can now connect an AI dir…
DiffusionGemma: How Google's New Open LLM Hits 1,000 Tokens/sec and Changes Inference Economics
TL;DR: Google released DiffusionGemma, an open Apache 2.0 diffusion-based LLM that generates text up to 4x faster than autoregressive models, hitting …
Every Step Was Allowed. The Sequence Was the Attack. (AI Memory Judgment, CLAIM-30)
Earlier this week I published CLAIM-29: permission is not purpose. An instruction can be fully authorized, fresh, and clean in shape, and still ask th…
Rag Vs Fine-Tuning For Document Qa 2024
RAG vs Fine‑Tuning for Document Q&A in 2024: What You Need to Know Hey Build Log listeners, it’s Nick. If you’ve ever stared at an invoice for a c…
Fine-Tuning Transformers Vs Lora Vs Qlora 2024
Fine‑Tuning Transformers vs LoRA vs QLoRA 2024 – What You Need to Know Hey folks, Nick Creighton here. If you’ve been listening to the latest Bui…
Local Ai Deployment Cost Analysis 2024
Local AI Deployment Cost Analysis 2024 – How I Cut My Inference Bill to Under $50/Month Hey, it’s Nick. If you caught the latest episode of Build Log …
The AI Paper That Quietly Changes How Enterprises Scale
Most enterprises are chasing “AI at scale,” but many are stuck in the same loop: flashy demos, fragile POCs, and a long list of reasons why nothing is…
Physical AI just got its platform layer. Nvidia is the only candidate. Here's what you missed this week.
NEURA closed a $1.4B record round, robots grew hands that can feel, and someone is racing to own the Physical AI ecosystem. Value Description $1.4BN N…
Because in a Life-Threatening Situation, Every Millisecond Counts
Removing expf() from a fire detector: one header, 1.95x faster, zero accuracy loss A smoke detector is not a demo project. When it fires, someone eith…
Sampling strategies compared: temperature, top-p, top-k, min-p, and what actually works in production
Sampling strategies compared: temperature, top-p, top-k, min-p, and what actually works in production You deployed a chatbot, picked temperature 0.7 b…
I trained a neural network to break my own encrypted search. It learned nothing.
A few months ago I built a way to search documents by meaning while keeping the embeddings hidden — even from the server doing the search. I called it…
How I Built an AI-Powered Adult (Porn) Content Scanner for Windows (And the Engineering Challenges I Didn't Expect)
Building an AI-Powered Content Scanner for Windows: Performance, Multithreading and GPU Acceleration in .NET Building software always looks straightfo…
We put confidence intervals on our LLM-judge scores. The error bars ate three weeks of "trend"
We track weekly agreement between an LLM judge and human labels (Cohen's kappa) on a sample of production traces. For three weeks the point estimates …
I Thought One AI Agent Was Enough. I Ended Up Building Six
Our first architecture was embarrassingly simple. A user sent a message. The persona replied. User Message ↓ Persona LLM ↓ Response That was it. No pr…
An AI Module Smaller Than a Smartphone Photo. Are We Underestimating the Computer We Carry Every Day?
The Idea and the Main Engineering Challenges Recently, I released a new offline AI feature for my Android application as a separate module. The entire…
Prompt Engineering for AI Image Generation — A Developer's Practical Guide
Most developers treat AI image prompts like search queries. Type a few words, hope for the best, get disappointed. After generating a few thousand ima…
MTP Isn't Always a Win: 1.95x on My 3090, but Speculative Decoding Is Hardware-Dependent
In my MTP post , speculative decoding roughly doubled Qwen3.6-27B generation on a 3090. It's tempting to read that as "turn on MTP, go faster." So I m…
We Invented an Oil Company (On Purpose)
We invented an oil company. It doesn't exist. No rigs. No wells. No employees. Just five fields, forty wells, five hundred people, ten rigs, a hundred…
Build Your RAG System Right the First Time: 6 Decisions That Make or Break It
After debugging 20+ broken RAG systems, I've identified the 6 decisions that determine whether yours works. Here's how to get each one right. The RAG …
AI Weekly — 2026-06-05 to 2026-11 | OpenAI Files S-1: What the IPO Actually Means
OpenAI has filed its S-1 confidentially. Meanwhile the Microsoft partnership is fraying at the seams, Anthropic shipped two models in 48 hours, and Vi…
# I Thought High Current Always Meant a Fault Until I Came Across Transformer Inrush Current
For a long time, I had a simple rule in my mind: high current means fault . If a transformer suddenly drew 5 times or 10 times its rated current, I wo…
I built a distributed compute grid where your idle laptop runs ML jobs — the orchestrator behind it
I built a distributed compute grid where your idle laptop runs ML jobs — the orchestrator behind it The pitch: a single FastAPI hub takes compute jobs…
Gemma 4 QAT on 10GB Laptop: Local AI with 6.7GB VRAM
This stack uses Ollama with Gemma 4 QAT to run a 12B model on a 10GB VRAM laptop GPU. The latest Gemma 4 QAT checkpoints reduce memory usage and enabl…
Mixture of Experts (MoE) Explained Simply: How Modern AI Models Get Bigger Without Getting Slower
Hello, I'm Shrijith Venkatramana. I'm building git-lrc, an AI code reviewer that runs on every commit. Star Us to help devs discover the project. Do g…
Stop Whispering to the Model, Start Furnishing Its Brain
Hello, I'm Maneshwar. I'm building git-lrc, a Micro AI code reviewer that runs on every commit. It is free and source-available on Github. Star git-lr…
How I fixed silent Ollama failures in my local AI Assistant
How I fixed silent Ollama failures in my local AI assistant Neo-AI is an offline assistant with episodic memory, running entirely on-device using Olla…
Agent-Harness Scaling Law: Feedback Quality Predicts Success, Not Raw Compute: Effective Feedback Compute (EFC)
What: A new agent-harness scaling-law paper introduces Effective Feedback Compute (EFC) — a single quantity that predicts whether an agent finishes a …
Как я сделал Smart Select для Krita: локальное AI-выделение объектов по лассо
Я недавно начал пользоваться Krita, и после Фотошопа основной болью для меня было отсутствие удобного инструмента для умного выделения объектов выделе…