What version of Gemini were you using? i.e. were you calling it locally via the API or thru their Gemini or AI Studio web apps?
Not every LLM app has access to web / news search capabilities turned on by default. This makes a huge difference in what kind of results you should expect. Of course, the AI should be aware that it doesn't have access to web / news search, and it should tell you as much rather than hallucinating fake links. If access to web search was turned on, and it still didn't properly search the web for you, that's a problem as well.
I had hardly written any code prior to ChatGPT other than teaching myself some VBA.
Since then, using Gen AI tools to learn + write code, I have deployed a functioning full stack application to the web. NextJS on Vercel, with a backend server also deployed running on Python, and a Supabase DB. Is it the best application ever making loads of money? Definitely not. Are there things wrong with it? Absolutely (although I promise I'm not exposing sensitive env vars and API keys to the web). Did the first versions look like absolute ass as I clumsily figured things out and made bad mistakes? You bet. But it's a functioning app that does some useful things and has real users.
I would never have imagined doing this in a million years prior to Gen AI.
Do some devs see mixed results depending on how they're using the tools? I'm sure. Is Gen AI overhyped broadly speaking? Probably so. But when I see people say it's a delusion, waste of resources, and everyone is wasting their time on it ... for me, it just doesn't line up.
> I have deployed a functioning full stack application to the web
Best hope ChatGPT plagiarized that code from people who properly sanitized user input, otherwise it might be vulnerable to SQL injection, XSS, etc. If such holes exist, it may be tough to resolve them without a professional.
> But when I see people say it's a delusion, waste of resources, and everyone is wasting their time on it ... for me, it just doesn't line up.
I don't think anyone would say LLMs are useless, but there are people out there comparing the birth of LLMs to the Industrial Revolution, and the advent of the Internet. Such claims are preposterous.
I think the widespread use of LLMs will ultimately be undone by a few factors:
1) Due to the way LLMs function, they will never be totally cured of 'hallucinations'. They are accurate a lot of the time, and apparently useful in those times. But you can never really trust its output. That is an exhausting problem, and will burn people out.
2) Prices for LLMs are artificially very low right now, these companies are burning investor money to keep going. The 'cost' is going to have to go way up for these LLM providers to be sustainable. I put cost in quotes because it will be some cost in subscription prices, but also cost in terms of ads that will be inserted everywhere, and other degrading forms of monetization.
3) Models are running out of good training data. They'll either hit a wall, or continue training on content that was itself LLM generated, which will go the way of Habsburg Jaw in a jiffy. Ensloppification is real.
I'm sure there will be niches for LLMs in the future, for those who can afford their true cost. But this cram-it-in-everything, available-everywhere frenzy will probably be looked back upon with deserved embarrassment.
Consider using a better AI IDE platform than Copilot ... cursor, windsurf, cline, all great options that do much better than what you're describing. The underlying LLM capabilities also have advanced quite a bit in the past year.
Well I do not really use it that much to actually care, and don't really depend on AI, thankfully. If they did not mess up the google search, we wouldnt even need that crap at all. But that's not the main point. Even if I switched to cursor or windsurf - aren't they all using one of the same LLMs? (ChatGPT,Claude, whatever..). The issue is that the underlying general approach will never be accurate enough. There is a reason most of successful technologies lift off quickly and those not successful also die very quickly. This is a tech propped up by a lot of VC money for now, but at some point, even the richest of the rich VCs will have trouble explaining spending 500B dollars in total, to get something like 15B revenue (not even profit). And don't even get me started on Altman's trillion-fantasies...
:) And you sound like one of the many people I've seen come and go in my career. Best of luck to you actually - if the GenAI bubble does not pop in the next few years (which it will) we'll only have so many open positions for "prompters" to use for building web app skeletons :)
You could easily test this for yourself right now, two different ways.
A) Go and ask ChatGPT the same question that Arve Hjalmar Holmen asked. (Make sure to turn off the 'Web Search' functionality, otherwise it will simply share what it finds on Google. We want to see what ChatGPT actually 'knows' in its 'internal data'.) After you do this, do you get the same answer, or something completely different?
B) Go and use ChatGPT and tell it the Answer to some Question about yourself that is not publicly known or recorded on any internet source. Then, tell one of your friends to ask that same Question to ChatGPT, and see what answer they receive. If ChatGPT is simply 'storing' information in its 'internal data' then surely your friend will receive the secret answer that you shared with ChatGPT - right?
Is there any evidence that ChatGPT is continuously making this false claim to multiple users? Can the false claim about this specific person be reproduced by anyone else or did it just appear randomly?
The article explains this, and the point of argument is whether what ChatGPT did to filter out wrong responses is sufficient vs. removing this underlying "internal data".
Shhh ... you're spoiling everybody's confirmation bias against LLMs. They are obviously terrible at coding, just as we have known all along, and everybody should laugh at them. Nothing to see here!
Since you are one of the cool kids in the know, can you share the road map to profitability and even better the expected/hyped ROI? Without extrpolations into science fiction, please.
Not every LLM app has access to web / news search capabilities turned on by default. This makes a huge difference in what kind of results you should expect. Of course, the AI should be aware that it doesn't have access to web / news search, and it should tell you as much rather than hallucinating fake links. If access to web search was turned on, and it still didn't properly search the web for you, that's a problem as well.