a cybernetic machine can nail the task and completely miss the job. coding makes this very very easy to see because the tasks are so legible (and verifiable!): write the function, migrate the API, fix the tests.
What's proven is if you properly architect it and have co- cloud code go into certain sub segments or have cloud help you build the architecture, you modify, refine it, lock it in and say just work on these few things
Trials serve two distinct functions: validation — confirming whether a drug works and is safe — and learning, or generating biological data to refine our understanding of a disease, a compound, and the relationship between the two.
Then you need a metag game, which for Duolingo is kind of like the path, but it's also the leaderboard, achievements, kind of long-term things that you're going to strive to such that you have like long-term, I guess, motivation uh to continue doing the thing. And then the profile is also critical because you build up a profile over time. It's a reflection of your investment inside the product experience. And so when you nail those three things, you can end up with a long-term learning journey that can be quite successful.
It's a nice, short, and moving memoir by the comedian and actor Steve Martin. The book details his early working days at shops and clubs, his relationships, and eventually his rise to fame. He shared his struggles, his failures, long hours of practice, his reflections to refine his craft, and his efforts to find his own unique voice as a comedian. Any memoir that only talks about successes and never discusses struggles, rejections, or weaknesses is suspect. This one is not. What I like about his writing is that it feels candid and, at times, funny.
So that's a lot of what I think we need to nail for the creators, and that's why that one is actually a much harder problem, I think, than starting with new characters that you're creating from scratch.
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