As I said, there are some self-hostable alternatives, but nothing even remotely enterprise ready yet. I’m keeping a pretty close eye on this because my boss wants to train a support chatbot on company data and run it on our own hardware. (And an alternative to copilot would be great too, as that’s banned for internal use.) There are some great tools to tinker around with, but I haven’t found anything that I would call production ready.

if you want to write a mediocre story, anyway

agreed otherwise

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I’m gonna vehemently disagree with you. As a knowledge worker, ChatGPT allows me to offload low level thinking and writing tasks so I can focus on bigger picture creative aspects.

GPT speeds up my quality work output by around half. Those who refuse to incorporate it into their work flow will find they fall behind compared to those who have successfully integrated it.

Then you don’t have much faith for your co-workers competence in wielding any given tool to its greatest utility. Using an LLM like ChatGPT to access data hardly automatically means you’re also a brain-dead search result copy-paster.

Yes, its a new interface for existing data, the same way digital files are to data on paper. Only ever using the latter is really inefficient, and stupid in a world where the digital files exist. Not that the hardcopies cant be to their own utility, or be used as corroborating data.

It’s a really good interface, if you know how to use it. This is like banning search engines because you expect your workers to be expert at everything, so they shouldn’t need support tools to sleuth for data.

Better stop using xerox machines to make copies and write everything out by hand

Frankly, if ChatGPT isn’t increasing your performance significantly, you’re already falling behind the curve unless you’re doing manual labor.

You could argue the same thing about using google. Yet you use google.

On this I agree entirely. The potential for corporate espionage because of unwitting employees using an LLM through unofficial means is huge.

At the very least, the corporation itself would have to be the customer, so that watertight terms might be negotiated, not the employee.

We’re talking about very specialized engineering work,

We’re not though. This isn’t a policy preventing them from disclosing them from talking about specific company IP (which is almost certainly covered by existing NDAs already). This prevents them from using it internally at all.

I use ChatGPT at work all the time, usually for getting very specific information about products I have to integrate with, quickly parsing new API documentation, and learning about unfamiliar processes at a conceptual level before I have to dive deeper for a project. It’s more the context around which I’ll be building the specialized IP. It’s the sort of stuff I can learn via Googling (or sometimes Stack Exchange), but can learn it faster in a more targeted manner by asking detailed questions to the chatbot.

This is true, but if you understand that queries don’t necessarily need to also become training data, what you tell it could absolutely be kept secret, provided the necessary agreements and changes were to be made. Nothing about an LLM means you can’t make it forget things you’ve told it. What you can’t make it forget, without re-training it from the ground up with that piece of information omitted, is what you told it in the training data.

But queries, do not suffer this limitation.