Something that I've found worth pointing out to other builders is that you don't need to build an AI product outright to sell to consumers (re: your comment about your ideas being gobbled up by big tech). Building internal AI/ML tools to solve your own business/workflow/whatever problems is often the better route for folks to leverage the advances in that technology. The best AI you build is likely the one your users don't even know exists.
This also has a beneficial side effect of showing you first-hand just how bad this tooling is currently and how far away it is from replacing builders wholesale. And to be clear, I'm not just talking about leveraging closed proprietary APIs for these efforts, I'm actually more referring to building your own training and inference stacks from scratch. The pedagogical impact alone can make up most of the ROI for your time spent.
> The best AI you build is likely the one your users don't even know exists
AI has a lot of use cases that are "transparent" and not necessarily "in your face" and still present a lot of opportunities for builders.
I work at a startup that leaned into AI and a use case is simply detecting mis-classified products (happens all the time at large retailers).
On my own side projects, I'm using it in a travel app transparently to help extract places from travel blogs. Imagine you're trying to plan a trip and you find a blog that has a great itinerary. Using AI, it's trivial now to pull out all of the place names for your and organize just the days and destinations without the fluff.
I have another side project where I use AI to generate a customized daily newsletter based off of a feed from the FDA. The AI allows the recipient to ask whatever questions they might have against clinical trials registered with the FDA and automatically answers those questions and sends it along with a summary of the trial.
If anything, I think AI has opened up a vast field of new possibilities.
> I work at a startup that leaned into AI and a use case is simply detecting mis-classified products (happens all the time at large retailers).
This tracks with my own experience for the last decade or so. I stopped being surprised at how many business problems can be, in part or in whole, reduced to classification issues.
This also has a beneficial side effect of showing you first-hand just how bad this tooling is currently and how far away it is from replacing builders wholesale. And to be clear, I'm not just talking about leveraging closed proprietary APIs for these efforts, I'm actually more referring to building your own training and inference stacks from scratch. The pedagogical impact alone can make up most of the ROI for your time spent.