… You can get away with this in cloud AI because it’s been trained to make assumptions and fill in the blanks - even search engines are better at handling vague queries thanks to their sophisticated algorithms. …
… The runner honestly matters less than the model you load into it - a capable model with a large and diverse training set is what will actually determine how useful the setup is for research. …
… A Notion B Evernote C Obsidian D Roam Research Correct! Obsidian stores all notes as plain markdown files on your local device, making it ideal for pairing with self-hosted LLMs. …
… But now you can use @gmail to search through your inbox. And after using it briefly, I turned it back off. It found things that I forgot were in there, in emails from a decade or more ago. Things that don't even show up when you use the search box in the Gmail interface. …
… There's two main ways you'll actually use it. The Gemini app is just the standalone chatbot, the one you'd open for the usual AI tasks. AI Mode lives inside Google Search itself, where it gives you a conversational layer built into the regular search results. …
… But the real issue is much more insidious: it’s data training. Every time you paste text into a standard cloud chatbot, that data is potentially absorbed to train the next generation of models . …
… It was quicker to set up than I expected, and it makes a real difference in the way my local LLM responds… The Brave Search MCP Letting local LLMs access real-time web results Brave Search MCP is like a bridge between your local LLM or whichever AI you set it up with and the Brave Search engine. …
… Every model made the same mistakes Training data biases were too strong There's a pattern that runs through all five models, regardless of size or architecture, and it's down to training data. …
… It is a privacy-focused metasearch engine that I run locally using Docker. This means I can search the web without ads, tracking, or personalized results influencing what I see. I use SearXNG when my AI needs fresh information that isn’t part of its training data. …
… Claude doesn't use your data for training by default, and deleted conversations clear within 30 days - but if you opted into model improvement at any point, retention stretches to five years. …