From the source
The post argues that machine learning is too hard to use because of a lack of good tools and abstractions, drawing parallels to the early days of web development before frameworks like Ruby on Rails and platforms like Heroku.
It highlights the shift from academic ML to open-source experimentation, exemplified by Stable Diffusion, and calls for a new tooling stack for 'Software 2.0'.
