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🤖 Added summaries and the Jina AI API to a few projects #research
🖥 ordered a 32GB Mac Mini Pro so I can do more AI work and have a dedicated machine at home again #mylife
🤖 I built a robot to help generate and maintain some Django/Python code using [cog](nedbatchelder.com/code/cog/in…). This will speed up my prototyping by a lot #myconf
🖥 threw some parts together to get a Windows box together so I can run pyautogui on it and build a few things #mylife
🤖 more AI writing project
🤖 checking out Amazon's Astro robot video demo 👀
🤖 sat down and had ChatGPT write some GPT4(ish) code for me
Ordered two Nvidia GPUs to implement some ✨ magic into #2markdown.
🤖 setup my new Raspberry Pi Zero 2 W tonight so that I can run Python on it and connect from anywhere via Tailscale. Time for some hardware projects.
get new notebook for dev work
🤖 Finally remembered the jina.ai address (been looking for weeks) and made a quick Agent to pull in remote pages. #research
Working on a distribution strategy for the latest product review on hackernoon: hackernoon.com/i-spent-a-week…
Finished home AI server build: 2 x 2697v2, 128 GB ram, 2 x Nvidia Tesla P40 24 GB gpus. #2markdown
🤖 got sweep running on my Mac Studio and spent $0.73 letting it write five pull requests to try it out. Not bad.
Over the past three days and a half, I've dedicated all my time to developing a new product that leverages locally running Llama 3.1 for real-time AI responses.
It's now available on Macs with M series chips – completely free, local, and incredibly fast.
Get it: Snapbox.app #snapbox
🤖 more robot work, but figured out how to get better results limiting num_predict for git commit messages #research
Have a GPTini with OpenAI #life