Technology

It's just in European. it's an entirely reasonable assumption that people in this continent with even a passing interest in the world will know what an NGO is (that's not even European-specific) as well as what the GDPR is. Your argument suggests that people from the US, for instance, should be forbidden from talking about IRAs and the IRS and their 401(k)s and the DMV because those terms mean very little to nothing over here.

💀 noyb is the name of an organization and GDPR is a law. NGO is the only thing you could even remotely begin to describe as unnecessary jargon but that's still a stretch.

Don't you realize everyone exists to serve me?

People can’t seem to understand that it’s a tool in the early stages of development. If you are treating it as a source of truth, you are missing the point of it entirely. If it tells you something about a person, that is not to be trusted as fact.

Every bit of information you get from it should be researched and verified. It just gives you a good jumping off point and direction to look based on your prompting. You can drastically improve your results on any subject with good direction, especially something you don’t know a lot about and are starting out in your research. If you are asking it about specific facts you want it to regurgitate, you are going to get bad information.

If you are claiming damages from something you know gives false information, maybe you should learn how to use the tool before you get your feelings invested, so you can start using it more effectively in your own applications. If you want it to specifically say something that can grab a headline, you can make it do that, it’s just disingenuous and not actually benefiting the conversation, the technology, or the future.

They have a long way to go to solve AGI, but the benefits to society along the way outpace current tools. At maturity, it has the potential to change major socio-economic structures, but it never gets there if people want to treat it like it has intuition and is trying to hurt them as the technology starts getting stood up.

excruciatingly painful

is the perfect description

You can literally run large language models with a single exe download: https://github.com/Mozilla-Ocho/llamafile

It doesn't get much simpler than that.

Thanks!

You cannot in all seriousness use a LLM as a research tool. That is explicitly not what it is useful for. A LLM's latent space is like a person's memory : sure there is some accurate data in there, but also a lot of "misremembered" or "misinterpreted" facts, and some bullshit.

Think of it like a reasoning engine. Provide it some data which you have researched yourself, and ask it to aggregate it, or summarize it, you'll get some great results. But asking it to "do the research for you" is plain stupid. If you're going to query a probabilistic machine for accurate information, you'd be better off rolling dice.

Someone doesn’t know how to use ChatGPT

This question betrays either your non-use or misuse of the products available. You're either just reading the headlines of the screw-ups or you're just bad at using the tool.

To directly answer your question:

• Quick scripts in a variety of languages. Tested before being used on real data/systems.
• Creating visual graphs of data in python and Jupyter notebooks with no prior knowledge of python itself or the tools it's running. In this case, I was able to update the way I wanted it to look in natural language, have it suggest code changes, and immediately try them in the notebook with great results.
• Improving the sentiment of correspondence. Proofread before sending. It has better grammar and flow than a surprising number of correspondences I've come across at work. Sure, English may be their second language but it doesn't change the fact.
• Quickly finding documentation pertaining to the query which, yes, you need to go read to verify any answers any LLM provides. Anyone using it regularly should know this by now.
• Quick "do this in command line. What options are required" which is then immediately tested.
• In one case, a news story was referenced in passing in a podcast I listen to. It stuck with me days later and I wanted to find actual articles written about it. I was able to describe what I was looking for in natural language and included as many details as I could remember and asked it to find articles for me. I found exactly what I was after.

But were you actually looking for a real response to your question?

I don't really query, but it's good enough at code generation to be occasionally useful. If it can spit out 100 lines of code that is generally reasonable, it's faster to adjust the generated code than to write it all from scratch. More generally, it's good for generating responses whose content and structure are easy to verify (like a question you already know the answer to), with the value being in the time saved rather than the content itself.

Without blatant privacy and copyright violations AI wouldn't work. I mean it doesn't really work anyway but it would work even less.