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Real-Time Sync: The Missing Piece in Cross-Platform LLM Chat Apps
While LLM chat apps now support Android, iOS, macOS, and Windows, they're still struggling with synchronisation - conversations of...
I Reverse-engineered How 23 'AI-first' Companies Actually Build Their Products
So I spend way too much time looking at how companies claiming to be "AI-powered" or "built with AI" actually implement their tech...
The Simple Document Everyone Should Read to Understand Artificial Intelligence
Large Language Models (LLMs), like ChatGPT, translate words into numerical vectors so they can process them and produce intelligen...
The Hidden Flaw in Automated Content Generation
LLM-powered automated newsletters often generate repetitive content because Retrieval-Augmented Generation (RAG) systems stop sear...
The Problem With Persistent AI Memory: It Doesn’t Forget Context
A response length selector (Short/Medium/Long) could eliminate frustrating back-and-forth iterations and save time. Simple UX cont...
From Cloud to Desk: 3 Signs the AI Revolution is Going Local
The DGX Spark is a true supercomputer with a "smaller than a smartphone footprint" It's powerful enough to fine-tune models with u...
Context Engineering for Coding Agents
Coding agents are getting pretty good, but they're inconsistent. The same prompt can work one time and break the next. To get reli...
4 Counter-Intuitive Truths About Building Smarter AI Agents
Next great leap in artificial intelligence is the creation of “agentic LLMs”; AI that can perform complex, open-ended tasks withou...
Beyond the Prompt: Five Lessons from Anthropic on AI's Most Valuable Resource
"Prompt engineering" is becoming less about finding the right words and phrases for your prompts, and more about answering the bro...
How to Run a RAG Powered Language Model on Android With the Help of MediaPipe
Learn how to implement and fine tune a RAG powered AI model in your Android Apps!
Exploiting Vision-LLM Vulnerability: Enhancing Typographic Attacks with Instruct...
This article proposes a linguistic augmentation scheme for typographic attacks using explicit instructional directives.
Methodology for Adversarial Attack Generation: Using Directives to Mislead Visio...
This article details the multi-step typographic attack pipeline, including Attack Auto-Generation and Attack Augmentation.
