Artificial intelligence large models are currently in a rapid development phase, with technical challenges including algorithm optimization, data privacy, model interpretability, computational resource demands, and ethical issues
Hey everyone, Since Notion released its AI tool, I've become addicted to using it. However, I find inputting text on my phone frustrating because the screen is too small for editing. Moreover, its input mechanism is not very user-friendly for mobile users. Do you have the same trouble as me? How do you deal with it?
Let me share our journey of making AI short films starting in 2023. This is not the dark history of PopShort.AI, but how it came to be. Feedback is welcome.
https://x.com/PopshortAI/status/...
I'm an old school developer but have been building my first AI platform. Most of the development is familiar (i.e. basic systems architecture work hasn't changed much) but I ve run into some counter-intuitive (for me) stuff
Too much instruction gives the model more ways to fail; too little leaves it without guidance for your use case, so it s a careful ongoing curation process.
There's a tension between what seems most helpful to the user and what is economically sustainable for the product.
Every free user plays into your business model and conversion rate calculations, dictating how robust your freemium model can be.
I m now seeing token management as a core part of UX. There s an article about the tradeoffs on my profile if anyone wants to join me down this rabbit hole, but
How are other builders thinking about this? Have you had to make tough choices about gating features or using multi-model architectures to make the numbers work?
