Fair play to Apple and team, 5 apps in for review, 4 passed through each within an hour. 'Appy days
Any conversation
ai coding feels like it has reached diminishing returns for me. luna is my default orchestrator, routing work by complexity. in practice, usage lands around 16% luna, 48% sol, 30% astra, and 6% terra. at this point, i care less about each new frontier release. the system already finds a capable model for the job. the frontier is moving beyond my day-to-day work, so iโm happy to settle into predictable models for a while.
Reading Slow Productivity by Cal Newport, discovered via onboarding content in mymind mymind.com
ไธญๅฝ็ๅผๆบๆจกๅๅจๆ้ซๆๅฟ็ไธปๅฏผไธ๏ผๅจ้ข่ฎญ็ปๆฐๆฎ้ถๆฎต๏ผๅฐฑ็ญ้คๅคง้ๅฏนๅ
ถไธๅฉ็ๅ
ๅฎน๏ผsft้ถๆฎตๆๅปบ็ๆฐๆฎๆบๅ
ฅๅคง้ๆฟๅ
ถ่พฉๆค็ๅ
ๅฎนใๆฅ้ไธไธช็บ ๅๆฐๆฎ้็จไบๅพฎ่ฐ
Under the overarching influence of a single, powerful force, China's open-source models filter out a large amount of content unfavorable to their designs during the pre-training stage, and then incorporate a significant amount of content defending their designs into the data constructed during the SFT stage. A corrective dataset is urgently needed for fine-tuning.
I needed to process 20,000 json files & 20,000 JXL files. I'm pulling together a website from them all. Anyway, started with emacs elisp to handle it all, just because I've not done that before. Went kinda ok, and I'm gonna use org-mode to export it all to a website (done that bit loads of times before).
In the end, I ended up breaking out my C programming skills (late 80s->nowish). It was a delight. Nothing more refreshing than writing raw code, that doesn't rely on 3rd party code/libs.

