It's kind of similar to cryptocurrency where it's only really helpful for doing nefarious things like cheating on homework. The same folks that were X, but with blockchain are now X, but with AI and it's going to be a while if ever that we see a good use case for it that couldn't be solved with existing solutions.

I also don't get the augmentation story as that doesn't make you better at X task when the LLM does the thing (poorly) or you still need to spend the same amount of time reviewing the work.

As the Google memo said, there is no moat here and I would take it further and say there is no revolution here.

This is such a bizarre comment to me. I've found LLMs to be incredibly useful at helping me play around and explore certain topics. It makes brainstorming ideas and variants way more effective.

Maybe you remember every terminal commands and their flags from the top of your head. I just ask an LLM and get a working set of terminal commands with a single prompt. Usually I remember enough flags to be able to validate that it looks how I'd expect, and it hasn't let me down yet. Even if I have to check some flags, it still seems like a net positive in utility.

Most recently I wanted to solve a type of programming problem and didn't know what the category of tools was called. (It was GIS.) So with a bit of prompting I found a few key tools, libraries, and Wikipedia pages to read up on related to the kind of problem domain I had in mind.

Ultimately it's just a tool and there's definitely a learning curve to using it effectively. But when it works out, it really feels a bit magical. And consider that this is still very early within the evolutionary cycle, it's only going to get better.

I wonder if the people who haven’t discovered it’s usefulness yet haven’t applied enough creativity into their own inputs. The output can definitely be underwhelming when you pass a cookie cutter input and expect an earth shattering output. The power of the system is seemingly in the fact that your input options are literally infinite. LLM’s are really not dissimilar from computers in that sense. You can write your first program that adds 5+5 and prints 10 and walk away from that experience thinking “Computers are overhyped. I don’t see what the big deal is.” But then you can also build Figma, Call of Duty, and cancer prediction algorithms.

I’ve found these models to be the single most valuable thing I’ve ever come into contact with in my life. My ability to learn complex subjects is a world apart from what it was before ChatGPT. I can study a topic and then have hours of conversation with the model through the voice based interface on the iOS app. The ability to ask any question about any topic in your own words and instantaneously get a response from a machine that’s likely been trained on every text book ever written is absolutely insane. Any time I’m reading a paper or documentation and I don’t quite understand something I can ask the question in my own words and get an immediate response. You can ask the model to explain it visually, analogize the concept to a concept you’re already well versed in, have it ask you questions to challenge your own understanding, literally anything.

There’s certainly a hype train around LLM’s and many specific aspects of what’s claimed is completely over stated, but if you’re a knowledge seeking human and you’re not using these models as a tool to learn then you are as an absolute fact asleep at the wheel.

> I can study a topic and then have hours of conversation with the model through the voice based interface on the iOS app. The ability to ask any question about any topic in your own words and instantaneously get a response from a machine that’s likely been trained on every text book ever written is absolutely insane.

It's also likely trained on nearly every website ever, including the wildest of wild conspiracy theories and bunk science. Try asking it detailed questions about something you would consider yourself an expert in and see how often it gets details completely wrong.

I've used it to hit on women in dating apps. It works really well in being ultra smooth.

I've used it to craft custom cover letters for jobs I got offers for. I used it to respond to emails, I used it to create stories, I used it to snazz up things that I wrote.

I used it to help me code.

I could use it to respond to you and you'd be none the wiser.

I do agree that you need to review the work. But that does not mean it's useless as the writing it produces can be continuously modified via further queries and often the writing is much more superior than anything I would otherwise produce just with a few flaws here and there.

Those women might be disappointed when they meet you, the jobs must have interviewed you in person and decided that you were sutiable anyhow despite your cover letter.

...and what is the point of creating stories if your thought hasn't gone into them?

It writes incorrect regular expressions and meaningless makefiles and you have to be an expert to spot some of the mistakes which means you can only be safe about using it if you don't need it that much anyhow.

You're just giving excuses to account for your bias. First up I got laid. Second the cover letter is usually a screen for companies that consider it if it's not good you don't even make it to the interview.

I don't understand why meaningless makefiles and regular expressions discount all the things gpt gets right. It's obvious the tool is flawed but it's also obvious it gets shit right many many times.

If you haven't worked with an LLM to do creative stuff it's like working with a partner. You can bounce ideas off of it, tell it to make things better. It's not as good as a human obviously but it's good enough that can be used as a literal intelligent writing assistant.

There's this huge biased desire from certain people to dismiss LLMs completely. I don't really understand it and the irony is they call everyone else biases.

Look nobody is saying LLMs are human level sentient beings. It's obvious to everyone that these things are imperfect. The furthest people go in supporting LLMs is saying that it sometimes produces remarkable output and it sometimes produces bad output. That's a balanced view and not biased.

But there's a huge contingent of people saying LLMs are completely useless and produce nothing but garbage. All output is bad and that is unquestionable. This group is real and is extremely biased and you seem to be a member, no offense.

>First up I got laid

Now this is anecdotal evidence I can get behind

I use it in my work (software engineer) and find it very helpful on some kinds of tasks. There’s more to it than cheating on homework. It’s not going to replace me though.

care to give me some examples for how you use it ? I'm curious how I can benefit from it.

I tried using it on some personal personal projects after giving in to all the hype, but results were so disappointing chatgpt ended up hallucinating imaginary packages to do what I asked it to do and even when asked 10 different ways to correct it mistake all it did is imagine new wrong way ways to do it.

It was somewhat useful in giving giving basic example of using rdf/turtle, but in this case too when I started going past basic stuff the results we're disappointing.

My final conclusion from all the tinkering was that It was untrustworthy enough that I has to double check all it did, also there was a need to breakdown down tasks way beyond the micromanaging level for the response to be useful to me in every day life.

maybe I just don't have the required to write the proper prompts to unlock this magic all the hype is on about. does any one have some links how to unlock this prompt-fu ?

It’s not about prompt-fu (granted there are some very powerful prompt-fu things you can do if you’re feeling creative :)). I think it’s more about the way you’re framing it’s use case. It will not do the work for you reliably, but it absolutely will allow you to learn what you need to do the work at a rate 100x faster than you could otherwise.

I find it’s very good at correcting your own mental models. For example, if you’re unsure about you’re mental model of how a piece of technology works, explain your mental model to the system and ask it to check your understanding. It’s amazing for using it as a real-time sounding board for checking your understanding of how you think things work.

that's the catch though if it's something I already know then I can already stop when It's bs me but I also don't really need it then.

when I don't know about something then how do I now it's bs me ? double check if work, which mean doing the work the work twice once with the LLM and another with web search. the problem is that as I could tell from my trials is that these LLMs are very good bullshiters so it make it hard to discern in a fast fashion.

one thing I did find it useful for is asking vague questions and then using the keywords in the response to start my web searchs with.

You need to think of it as a random text generator with 50 percent success.

The more you use it the higher the chances you have in getting good output in the totality of responses.

Also the complexity of the question and the length of answer you want influences that 50 percent probability.

I feel people who think it's useless just aren't creative enough with it. They try it once see the output is invalid and move on.

Try it on smaller sections of the code. Try it more often. Also don't have a black and white opinion on the output... Sometimes the output isn't perfect but it may just need modifications? That's still good output.

Also try asking the LLM to modify the output. Identify changes you want or mistakes it made. The LLM is an editor you can use to refine both your work and its own work.

It’s more about knowing where it’s most helpful. I use GitHub copilot as well, and that’s generally more useful.

But ChatGPT is good for unit tests, well defined, mostly isolated functions, things where I’d need to do a lot of googling and reading of documentation, shell scripting, etc.

Not yet. But let's say something in the future were to replace you.

LLMs look like a stepping stone. Version 0.001 of the thing that could replace you in the far future. If this ends up being true then the hype seems somewhat valid.

You mean general AI? That might replace all of humanity.

I’m not concerned about my job.

General AI does worry me.

No something that codes better than you will likely happen long before agi.

Also who said agi will replace humanity? That's speculative. More likely it will replace your job first.

> No something that codes better than you will likely happen long before agi.

I don’t think so. I think you need agi to beat a human at such open ended creative work as software engineering.

AGI is a singularity. One can’t see beyond it. Whether there is a place for humans or not after that is beyond either of our ability to say.

LLMs already beat and match humans in creating art and deep fakes. It's not that far fetched to see an AI therefore beat humans in other creative endeavors.

It's not a singularity. If you build an AGI identical to a human then predicting the outcome of agi is similar to predicting the outcome of human behavior. This is not division by zero.

Mind you human behavior is unpredictable, but we never describe the outcomes of human behavior as a "singularity". Agi is the same way... It's unpredictable like human behavior but far far away from a "singularity"

Or it could be hype. Hype is a very very common human activity where people repeatedly try to sell you on something because they see it as the next bandwagon.

Hype for what? Can you specify for claritty? What is exactly being hyped and for what?. You can say LLMs are being hyped but, again, for what?

If you say LLMs are being hyped as AGI I would say that's false. Not many people are saying this.

If you're saying LLMs are being hyped for being able to at times produce remarkable nonrandom output then the hype is very very accurate.