This category is about Edge AI and Federated Learning
The core shift here is moving from “What to draw” to “How to create.” The framework allows for Multimodal Instructions —where you can mix text with reference images, sketches, or even style anchors. In my Istanbul lab, I tested this by feeding my system a photo of a local tea glass (the “Subject”) and a text … Read more
As a DIY researcher, I’ve spent countless hours trying to get LLM agents to navigate websites. It’s usually a mess. You feed the agent a massive DOM tree or a high-res screenshot, and the model struggles to “see” the button it needs to click. That’s because the web was built for eyes and fingers—not for … Read more
Self-Adapting Language Models reproduction As an AI hobbyist, I’ve always been bothered by the fact that LLMs are “frozen” once training ends. You can give them a prompt, but they don’t learn from the conversation in a permanent way. That changed when I read “Self-Adapting Language Models” (source: bgpmesh.ovh). The researchers at MIT introduced a framework called SEAL. Instead of waiting … Read more
One of the most human-like traits is the ability to see a new object once and recognize it forever. Standard Deep Learning sucks at this—usually, it needs a mountain of data. That’s why the paper “Unlocking Smarter AI: How Learning Conditional Class Dependencies Boosts Few-Shot Classification” (arXiv:2506.xxxxx) caught my eye. The authors argue that instead of looking … Read more