Small on-device vision models and what they let you build
Small vision models, fine-tuned for specific jobs, can now run on a phone with accuracy that used to need a server. Here is what that changes for image-driven apps.
Tag: ai-and-automation
· securityClaude Mythos Found Flaws Under Millions of Laravel Sites. A Wake-Up Call, Not a Disaster
Anthropic's Mythos model just found 19 confirmed vulnerabilities in Symfony, the framework behind millions of Laravel sites. It sounds alarming, and it is worth taking seriously. But what actually decides whether your application is exposed is more reassuring than the headline.
How to choose between prompting, RAG, and fine-tuning
Three ways to make an AI feature work, three very different price tags. Here is the decision framework we use to pick the right one, written for the person signing off on the budget.
Expert in the loop: rethinking AI oversight
Human in the loop made sense when AI errors were obvious. The failures we see now look like working software, and only an expert can tell the difference.
How to Prepare Your Company's Data for AI Automation (Without Creating a Security Nightmare)
Before your company can use AI, your data has to be clean and secure. Here is how we help businesses organise their messy databases and API silos so they can safely deploy AI agents without accidentally exposing confidential data.
Google's Gemma 4 is Apache 2.0, and That Changes the Local Model Conversation
Gemma 4 ships under Apache 2.0 with native audio, vision, reasoning, and function calling. Here is what it means for teams running local models and building AI-powered products.
