It’s certainly still improving in many areas - like coding assist, for sure. I think video generation is still improving but it takes a shit ton of resources, so it’s a bit slower. Maybe image generation has plateaued, but that could certainly be temporary. There are lots of more niche applications that are still progressing at a slower pace like I just read an article on using image processing AI in fertility clinics to better predict viability of embryos for implantation. Cool stuff that could actually improve people’s lives.
It’s certainly still improving in many areas - like coding assist, for sure. I think video generation is still improving but it takes a shit ton of resources, so it’s a bit slower. Maybe image generation has plateaued, but that could certainly be temporary. There are lots of more niche applications that are still progressing at a slower pace like I just read an article on using image processing AI in fertility clinics to better predict viability of embryos for implantation. Cool stuff that could actually improve people’s lives.
medical applications of machine learning are a pretty far cry from llms/genai
Many medical applications of ML do use transformer architectures, so it’s fundamentally the same technology.