Comment by auxiliarymoose
3 days ago
Some off the top of my head...
- Instead of trying to get LLMs to answer user questions, write better FAQs informed by reviewing tickets submitted by customers
- Instead of RAG for anything involving business data, have some DBA write a bunch of reports that answer specific business questions
- Instead of putting some copilot chat into tools and telling users to ask it to e.g. "explain recent sales trends", make task-focused wizards and visualizations so users can answer these with hard numbers
- Instead of generating code with LLMs, write more expressive frameworks and libraries that don't require so much plumbing and boilerplate
Of course, maybe there is something I am missing, but these are just my personal observations!
I agree, however, I've seen first hand how the AI fever and mandate from the top has finally busted enough information silos that previously 'have some DBA write a bunch of reports that answer specific business questions' just wasn't feasible in the first place, and now is.
Yeah, I will say it provides a good excuse to leadership & external stakeholders for fixing technical debt and working cross-functionally! Making infrastructure "AI-ready" and all that.
I imagine more of the benefit of AI will come from companies prioritizing infrastructure and effective organization than from the technology itself.
With all due respect, all of those examples are the examples of "yesterday" ... that's how we have been bringing money to businesses for decades, no? Today we have AI models that can already do as good, almost as good, or even better than the average human in many many tasks, including the ones you mentioned.
Businesses are incentivized to be more productive and cost-effective since they are solely profit-driven so they naturally see this as an opportunity to make more money by hiring less people while keeping the amount of work done roughly the same or even more.
So "classical" approach to many of the problems is I think the thing of a past already.
> Today we have AI models that can already do as good, almost as good, or even better than the average human in many many tasks, including the ones you mentioned.
We really don't. There are demos that look cool onstage, but there is a big difference between "in store good" and "at home good" in the sense that products aren't living up to their marketing during actual use.
IMO there is a lot of room to grow within the traditional approaches of "yesterday" - The problem is that large orgs get bogged down in legacy + bureaucracy, and most startups don't understand the business problems well enough to make a better solution. And I don't think that there is any technical silver bullet that can solve either of these problems (AI or otherwise)
I am wondering how often do you use AI models? Because I do it on a daily basis, and as much as they have limitations, I find them to be performing incredibly well. It's far very far from being a demo - last time it was a demo that looked "cool" was around 2020/21 when they were cool for spitting out the haiku poetry, and perhaps 2022 when capabilities were not as good. But today? Completely mind-blowing.
If you're not convinced, I suggest you to search for the law firms, hospitals, and laboratories ... all of which are using AI models as of today to do both the research and boiler-plate work. Creative industries are being literally erased by the generative AI as we are speaking. What will happen with the Photoshop and other similar tools when I can create whatever I want using the free AI model in literally 2 seconds without prior knowledge? What will happen with majority of movie effect makers when single guy will be able to do the work of 5 people at the same time? Or interior designers? The heck, what will happen with the Google search - I anticipate nobody will be using it in a year or two. I already don't because it's a massive sink of time compared to what I can do with perplexity for example.
There's many many examples. You just need to have your mind open to see it.
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