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.
Right, questioning the value of a chatbot is a good indication someone hasn't had real job. Totally legit characterization that doesn't make the whole thing sound like a confidence game.
Ironic given yours and others emphasis on my choosing "chatbot" to summarise llms as a reason to dismiss my comment, along with the rest of the pedantry. The upstream post dismissed / insulted the person for questioning value, which was what I called out.
If you really had wanted to get into the "HN rules" game, you could at least have cited "don't be 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.
They weren't questioning the value if the chat bot, they were questioning the value of the models based on only the high profile use cases such as a now (in)famous chat bot. That, to me, showed that they have a narrow view of the problems that this stuff could solve when applied outside of those high profile use cases. So I made an (explicit) assumption that they mostly worked in tech and not outside of tech, which limits the view of the world outside of tech.
I don't think donkeyd was trying to insult the person he was replying to, but he definitely could have worded that better. I think he's using "real job" in a derogatory sense directed at businesses, how most of them are so inefficient and rote that they'd stand to gain from the roteness of something like GPT, and that the person he's replying to, perhaps fortunately, hasn't experienced that type of business.
Data entry is a really interesting one to me. We’ve been replacing a legacy (read > 1 MLoC with no tests), system on and off for a few years. The original system had a ton of double entry or manual data entry and the human error rate is noticeable. If GPT could have automated this with a similar or reduced error rate then we would have considered it a win.
The real win long term remains killing off manual entry any time it’s possible, but GPT offers a nice patch.
> 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 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.
This is very confidential data, which is why the current implementation is run on-premise and of course I'm definitely not using production data to test GPT capabilities.
Well, in the organization I was doing this, they had similar issues before I started, with external consultants doing stupid stuff. Luckily, my team wasn't as stupid as these people and integrity was also very high. Which was very, very necessary considering the data we were working with.
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.