Is this data confidential or something you are willing to send to anyone? If the former, you probably shouldn't be sending it to an AI company that retains the data for its own purposes.
You don't want to know how many companies still get paper bills scan them and add them to their system half manually.
And normal people without scripting experience never had the tools to just do a little bit of text analysis without tools like chargpt.
https://news.ycombinator.com/newsguidelines.html
> questioning the value of a chatbot
Original commenter was questioning the value of the entire field.
> hasn’t had a real job”
This is different than “haven't worked in a 'real' business”.
If you really had wanted to get into the "HN rules" game, you could at least have cited "don't be snarky"
But yes, also snarky.
That wasn't even remotely my goal and I'm disappointed that my choice of words made it seem like it was. I purposefully added quotes to the word 'real' in my comment since any business is a real business and made it clear it was an assumption, not a fact.
It's just that many tech workers often haven't worked outside of tech and therefore are blind to issues outside of the tech world, like manual data entry, because they assume that must all be automated. It's exactly the same the other way around, people in what I called 'real' businesses are blind to what tech can to to improve business processes because they have no clue about what's available and possible.
Translation: “Real” businesses sort of make their own gravity.
The real win long term remains killing off manual entry any time it’s possible, but GPT offers a nice patch.
I'm going to guess (assume) you probably haven't worked in a 'real' business. A place where elbow grease still does the majority of the work and where Windows 8 was only just phased out.
The killer app (to me) in case of GPT is GPT itself, not ChatGPT. ChatGPT just allows me to easily test use cases for GPT. There are many interesting use cases for those elbow grease businesses for GPT. For example:
Data entry. There's still a lot of data entry being done from unstructured text. Where specifics like names and addresses need to be extracted from letters and emails and contracts and other stuff. I've worked on these challenges before using different strategies and GPT blows my mind with what it can do just by asking to grab this data and format it as JSON. Is it 100% correct? Nope. You still need people to review the data (depending on the use case), but that already saves tons of work.
Categorization. Some companies still get tons of emails that need to be forwarded to specific departments. This is another thing that GPT does surprisingly well out of the box.
And that's just GPT. There are many other legacy business processes that can be automated (partially) by other models that are coming out right now. Even just 'segment anything' that Meta just released is incredibly useful for many use cases I've seen in my daily work.
Killer apps are always a combination of a technology to solve a real world problem. If you don't venture into the real world and only stay part of the tech world, seeing the killer app is very difficult and ends up leading to Juicero-like products.