Companies love to show how they care about privacy and security of their data yet the amount of data breaches are higher than ever before. What an irony
ChatGPT Enterprise
381–390 of 532 posts
Re: ChatGPT Enterprise
#382Explicitly calling out that they are not going to train on enterprise's data and SOC2 compliance is going to put a lot of the enterprises at ease and embrace ChatGPT in their business processes. From our discussions with enterprises (trying to sell our LLM apps platform), we quickly learned how sensitive enterprises are when it comes to sharing their data. In many of these organizations, employees are already pasting…
My company (Fortune 500 with 80,000 full time employees) has a policy that forbids the use of any AI or LLM tool. The big concern listed in the policy is that we may inadvertently use someone else’s IP from training data. So, our data going into the tool is one concern, but the other is our using something we are not authorized to use because the tool has it already in its data. How do you prove that that could never…
> How do you prove that that could never occur?
Realistically you can prove that just as well as you can prove that employees aren't using ChatGPT via their cellphones.
There are also organizations that forbid the use of Stack overflow. As long as employees don't feel like you're holding back their career and skills by prohibiting them from using modern tools, and keep working there, hey. As long as you pay them enough to stay, people will put up with a lot, even if it hurts them.
Re: ChatGPT Enterprise
#383The ChatGPT model has violated pretty much all open source licenses (including MIT license which needs attribution. Show me one single OSS project's license attribution before arguing please.) and is standing still. With the backing of microsoft, I am confused. What will happen if they violate their promise and train data selectively from competitors or potential small companies?
What is actually stopping them? Most companies won't have the fire power to go against microsoft backed openai. How can we ensure that they can't violate this? How can they be practically held accountable?
This as far as I am concerned is "Trust me bro!". How is it not otherwise?
Re: ChatGPT Enterprise
#384Explicitly calling out that they are not going to train on enterprise's data and SOC2 compliance is going to put a lot of the enterprises at ease and embrace ChatGPT in their business processes. From our discussions with enterprises (trying to sell our LLM apps platform), we quickly learned how sensitive enterprises are when it comes to sharing their data. In many of these organizations, employees are already pasting…
Azures ridiculous agreement likely put a lot of orgs off. They also shouldn't have tried to "improve" upon OpenAI's APIs. OpenAI's APIs are a little under thought (particularly fine tuning) but so what?
Re: ChatGPT Enterprise
#385Earlier quoted context omitted.
I saw it, but it only mentions "applications" (whatever that means) and not bare documents. Does this mean companies might be able to upload, say, PDFs, and fine-tune the model on that?
Pretty unlikely. Generally you don't use fine-tuning for bare documents. You use retrieval augmented generation, which usually involves vector similarity search. Fine-tuning isn't great at learning knowledge. It's good at adopting tone or format. For example, a chirpy helper bot, or a bot that outputs specifically formatted JSON. I also doubt they're going to have a great system for fine-tuning. Successful fine-tunin…
Totally agree. retrieval augmented generation is still the preferred way to give the LLM more knowledge. Fine-tuning is mostly useful for adapting the base model for another task. I wrote about this in a recent blog post: https://vectara.com/fine-tuning-vs-grounded-generation/.
Anyone knows how this new capability works in terms of where the model inference be done? Would it still be at the OpenAI side or is this going to be at the customer side?
Re: ChatGPT Enterprise
#386Has there been some resolution to the copyright issues that I’m no aware of? In my conversations with execs that’s been a serious concern — basically that generated output from AI systems can’t be reliably protected. I refer to the concept that output could be deemed free of copyright because they are not created by a human author, or that derivative works can be potential liabilities because they resemble works that…
If you are concerned somebody will steal your IP or infringe your copyright, they first have to be 100% sure that some text was indeed written by an AI, and only an AI. In practice, if you suspect something was written by an AI and are considering copying it, you would be safer to just ask an AI to write you one as well.
There have been a few things that have been in the back of my mind that have been painfully bothering me for quite while regarding this subject.
Are people really that different from an AI model when it comes to generating works?
Isn't the underlying and overarching concept and process similar when it comes to this? (Optimizing for a certain select scenario or outcome by iteratively going through ideas and generating more over time.)
What happens when both the model and human converge and it becomes truly indecipherable when it comes to telling the difference?
Shower thoughts. I guess.
Re: ChatGPT Enterprise
#387Earlier quoted context omitted.
My company (Fortune 500 with 80,000 full time employees) has a policy that forbids the use of any AI or LLM tool. The big concern listed in the policy is that we may inadvertently use someone else’s IP from training data. So, our data going into the tool is one concern, but the other is our using something we are not authorized to use because the tool has it already in its data. How do you prove that that could never…
> How do you prove that that could never occur? Realistically you can prove that just as well as you can prove that employees aren't using ChatGPT via their cellphones. There are also organizations that forbid the use of Stack overflow. As long as employees don't feel like you're holding back their career and skills by prohibiting them from using modern tools, and keep working there, hey. As long as you pay them enou…
Using chatgpt to code is not a skill. It’s a crutch. Any employees that feel held back by not being able to access it aren’t great in the first place.
Re: ChatGPT Enterprise
#388Earlier quoted context omitted.
This sounds a bit like word salad, and your argument is worse than an LLM output. You even contradict yourself at the end. Also I think you need to better understand how much hallucination has been driven down recently and its clear path going forward.
“This isn’t fixable,” said Emily Bender, a linguistics professor and director of the University of Washington’s Computational Linguistics Laboratory. “It’s inherent in the mismatch between the technology and the proposed use cases.” https://apnews.com/article/artificial-intelligence-hallucina...
Bender also recently said in some podcast that there's basically no useful case for LLMs. I think she's a good candidate for some soundbite to add to "a global market of maybe five computers", "nobody needs more than 640k", etc (but she is probably not notable enough even for that).
Re: ChatGPT Enterprise
#389I used to be super hyped about ChatGPT and the productivity they could deliver. However the large amount of persistent bugs in their interface has convinced me otherwise.
Bugs in the interface?
Yes. If you re-open a chat from a while ago, typing a new message will typically result in an error causing me to having to start a new conversation. Happens both in the browser and on mobile for months now. Because no one else has it then it’s probably because I disabled history. It’s still a bug.
Another bug that I‘m having for weeks now is that pressing Stop Responding will indeed stop the stream but it will also cause a block on any new messages for about a minute. This one used to work just fine but started to fail a few weeks ago.
Re: ChatGPT Enterprise
#390Earlier quoted context omitted.
When I first started working with GPT I was disappointed in this. I thought like the previous commentor that I could fine tune by adding documents and it would add it to the "knowledge" of GPT. Instead I had to do what you suggest is vector similarity search, and add the relevant text to the prompt. I do think an open line of research is some way for users to just add arbitrary docs in an easy way to the LLM.
Yes, this would definitely be a game changer for almost all companies. Considering how huge the market is, I guess it's pretty difficult to do, or it would be done already. I certainly don't expect a nice drag-and-drop interface to put my Office files and then ask questions about it coming in 2023. Maybe 2024?
I believe latest version of Elastic offers this