NIH syndrome? I am guilty of it too. I love implementing things from scratch, you learn a lot by doing so and you get to own the codebase end-to-end, so no surprises and fighting around othersโ choices. It can get exhausting too though, in the end I succumb to using off-the-shelf components because my primary goals move at a higher level.
Any conversation
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.
โฆ
Is this true? Sometimes, AI allows for socratic thinking, this is, the conversation with the machine allows the thinker to go further as the AI thorws ideas to the conversation. Many times, the AI reasoning is not good enough, but like a friend that says a funny think that sparks an idea, the AI can help our brain to see other possible paths.
The AI doesn't need to be right to be helpful



