And these people you mention are trying to stop you from using ChatGPT or you can proceed only based on their opinion?

I think you've missed the point I'm trying to make. I'm not entertaining their opinions. I'm annoyed that they don't see the utility at all and think it's such a gimmick. It's incredibly helpful to me day to day.

They act like it's literally useless except for plagiarism.

Exactly. An electric drill is useless for me in a daily basis, but it doesn't mean it's useless for a carpenter.

Electric drill companies aren't being attributed deity-like capabilities and unicorn valuations on $0 revenue.

That's not a new phenomenon and it's not the tool's fault.

It's the fault of the manufacturer, but that is a distinction without a difference. OpenAI has marketed it as an "everything" tool, whereas McMaster-Carr have been more conservative about the capabilities of theirs.

An electric drill's capabilities are known, in the way AI's is not. There's no drill bit coming in Q4 that will let you drill into steel for example. But there will be a GPT 4.5 or something that will add new capabilities.

I'm not sure I buy that.

After so many disappointments in the tech universe (and with some AI winter in the past) people in the industry should not be naive to the point of thinking that OpenAI would solve all the industry's problems.

>> OpenAI has marketed it as an "everything" tool

That's what all companies do all the time. Should we blame capitalism?

A tool every person uses daily can be worth anything from hundreds of millions to trillions of dollars. The issue, as always with AI, is overselling it. Pre-Revenue startups raising at billion dollar valuations is certainly not going to end well. Hence anything that looks like it will prick the bubble is worth talking about to a certain segment.

On the other hand, the finances of AI are only loosely correlated with it's utility to individuals. If OpenAI went from being worth 10 Billion to 500 MM, it wouldn't make too much difference to people who use OpenAI products.

Can you share a transcript where it saved you an hour? I’m trying to better understand how I might apply it to my work.

So far it’s only been useful to me when working with a tool I don’t really know. But most of my work I know the tools fairly well.

So lately I've been using it to build things against APIs I've never worked with. I needed to write something that would check circleci (ci/cd system) for jobs in ANOTHER repo running and hold off starting a job in a DIFFERENT repo if there was one running in the first. Basically something to check every 30s-1min and succeed and move on to the next job if that repo wasn't running a workflow. Instead of having to dig through circles API docs or stackoverflow for examples I just typed in something like "How can I use ruby, go, bash or python to check a different circleci repo for running workflows before starting a workflow in a different repo?"

I had to go through several iterations and I bounced from wanting to write it in go to I think eventually just doing it in bash, just simplicities sake, but it absolutely saved me days of research. I definitely had to fix a lot of things and tailor it to my needs and it lead me astray quite a few times but it really was more like asking a professor the question vs googling it and hoping that SOMEONE out there has done something similar. Or combing API docs.. It was such an ancillary thing that I didn't want to get hung up on it for more than 1-3 days and it literally got me going in maybe 3-6 hours.

I also write a ton of very advanced terraform and cdk with it. I already know both very well but it absolutely speeds me up if I haven't used a specific function or what not in awhile, or it's newer to me.

It's great at leading me to the water, sometimes I have to still teach myself to fish but it will give me ideas and get me going if not even more.

Totally agreed.

For me ChatGPT (v4) is very useful as it is and for my line of work is a God sent, and I give one simple real world example.

Earlier this month we have some encouraging results on earthquakes early detection based on IoT and Big Data. Our earthquake expert is not replying emails for several weeks and we had to send the research summary immediately to ask the journal editor for the suitability of potential publication based on the proposed paper's title and abstract. But since we are not the earthquake domain experts, we are not sure what's the correct word to use for the early detection of earthquake in our particular results, and the prime candidates are forecasting or prediction. Voila, upon consulting ChatGPT it's obvious that for our results, prediction is the correct word to be used.

Before Internet people used to go to library for looking up something, but then Google arrived. Similarly, before ChatGPT people used to these so called experts for consultations, but then ChatGPT arrived. But somehow, people seems to be in denial of the useful of the GPT in helping us to write better reports, papers, articles, etc.