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2/ I am doing course.fast.ai again. I did part 1 in 2018 but binged the first 4 lessons fri-sun. Jeremy was kind enough to invite me to the 2022 version on going. Wait a few weeks before pursuing this which will show you new tools and a few new concepts.
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4/ I’ve been messing around with prompts again in OpenAI playground with DALL-E and GPT-3 to experiment. Made some album art for a song I plan to release next month and prototyped a new feature for I hope we’ll ship later. Just keeping up the momentum/motivation.
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6/ I was somewhat surprised how complicated getting a dev env was today. Lots of choices but it's all kind of expensive, running weird versions of pkgs, bespoke notebook UIs. I mostly just wanna use a local jupyter environment and connect to a GPU/macOS/not pay $1K/mo
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7/ Trying Paperspace but their remote kernel environment in VS Code doesn't work. Might give up and just use the funky jupyter lab thing and get to work.
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paperspace is the best provider i found (i was able to get vscode remote ssh plug-in working - their jupiter lab hack is jank though). i ended up just buying my own machine and setting up a local environment in the end since paperspace startup time was painful.
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Idk why but when I add the remote url, vs code doesn't do anything or show anything. It doesn't seem like it connects even though it shows a last connection date. It kills me a little to have the janky setup. I move so slowly.
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Bummer :/ might be a bug with the plugin If you're serious about investing the time in ML learning, you could probably justify just buying a gaming rig and installing linux - nothing beats to the simplicity of connecting to a local machine you can remote into from a laptop.
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