As for exercise: shot some hoops. Running is a rough proposition with the still-bruised-rib, so bringing the bike for cardio down in LA.

Driving down to LA today, with a return on this Friday. The weather is flawless, not not looking forward to it. annnd got a flat, will head down tomorrow morning

Zipped around Baku a bit more in F1'22. Still clipping my wing when I lock, but I actually feel like I’m improving with the new setup. Starting to adjust the differential as the tires wear which helps keep the car from snap turning on throttle.

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Taking off for LA tomorrow, so packing up tonight.

Raced a bit with EBJ, practice and quali around Baku. We both got off to front-wing breaking poor starts, but started to get into the flow by the time we got into quali – I ended up P14 with the AI@55. Setting up the car to oversteer on acceleration feels helpful to avoid understeering into the wall. Also, adjusted brake linearity up to 50 so I can lean more on the breaks / have greater sensitivity in the earlier range.

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Not sure why, but tired as hell today. The bruised rib does not play well with bench press, so only worked on triceps today. At this point, just one week since the impact, so likely another month till healed up. Push-ups are a less painful alternative, will try for some sets today.

Sim Racing: ACC 1.9

Tried out the Porsche 992 and the updated physics for ACC 1.9. Super fun to catch slides and hammer kerbs. I’d like to compete in online matchmaking / LFM so working my SA up on the steam install – currently ~50 after some 20min practice races at Laguna Seca.

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Guix: Adding Packages / Applying Diffs

My guix home upgrade has been blocked by one of the dependent package’s builds being broken (python-lazr-restfulclient). The patch to fix has already been submitted, but not accepted into the guix mainline. If I could cherry-pick these changes into my own “cutting edge” branch I can keep my build working.

Guix has published three videos showing the process, which feels foundational to figuring out my own guix fork:

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LLM

Some more reading. Still behind the curve, but seeing how the foundation can be put together to run locally on the tools we have today:

• Vicuna is a LLaMa derivative fine-tuned as a chatbot by GPT-4. It provides near GPT-3 quality (90% whatever that means) and the 13B model can be run on local commodity hardware, e.g. an Apple M1 chip with 32GB of ram has no problem running the model. The fine-tuning only cost ~$500 for the 65B param model
• Alpaca-LoRA opens the door for instruction-tuning on local hardware. The sauce is Low Ranked Adaptation [LoRA], which freezes the pre-trained model while training a lower-ranked layer, a much cheaper process than training the whole high-ranked model.
• Found my way to the LLM wikipedia article, always good to read.

Exercise

Slight regression from last week, the ribs still hurt from Friday and I don’t want to push it. Similar story with grip strength – left middle finger tendons have been strained for like the last two weeks.

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