itโs time! yโall!
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Any conversation
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.
mandelbrot
for y in range(10):
s=''
for x in range(25):
a=[]
for q in range(2):
z=c=x/25*3-2+1j*((y*2+q)/10-1);n=40
while n and abs(z)<2:z=z*z+c;n-=1
a+=[n<5]
s+=" โโโ"[a[0]+2*a[1]]
print(s)
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โโI notice that language models are much better at programming than at writing. This is largely because, in programming, they have a closed feedback loop that allows them to find errors. Writing is much more complicated because the feedback is much more diffuse and delayed over time. In fact, it is often not well-defined.
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.

