We're truly building walls everywhere.
Personally, I tried copilot when I got it for free as a student and it didnt make a difference. The reason I know is that I was coding on two devices, one which had copilot installed the other didnt, and I didnt care enough to install it on the latter through an entire semester.
Its just slightly better autocomplete, by a questionable standard of "better".
There’s literally nothing an llm can write or tell you that you can’t write yourself or find in a manual somewhere.
Also, local llms with an agentic tool can be a lot of fun to quickly prototype things. Quality can be hit or miss.
Hopefully the work trickles down to local models long-term.
Obviously, if the library or code using it weren't part of the training data, and you don't supply either in the context of your request, then it won't generate valid code for it. But that's not LLM's fault.
You can imagine the classic attention mechanism as a lookup table, actually.
Transformers are layers and layers and layers of lookup tables.
That's like saying, there's literally nothing a service business can do for you that you can't do yourself. It's only true in a theoretical sense, if neither time nor resources are a constraint.
In such hypothetical universe, you don't need a dentist - you only need to spend 5+ years in medical school + whatever extra it takes to become proficient with tools dentists use + whatever money it takes to buy that equipment. You also don't need accountants, lawyers, hairdressers, or construction companies. You can always learn this stuff and do it yourself better!
Truth is, time and attention is finite. Meanwhile, SOTA LLMs are cheap as dirt, they can do pretty much anything that involves text, and do it at the level of a mediocre specialist - i.e. they're literally better than you at anything except the few things you happen to be experienced in. Not perfect, by no means error-free - just better than you. I feel this still hasn't sunk in for most people.
Like speaking english and coding?
Don’t be so hard on yourself.
Chatgpt (and other LLMs) are awful at creative prose.
As are most humans.
Don't get me wrong, what I've seen from even the better LLMs have a certain voice and tropes and sacherine worldview that isn't dark enough where it needs to be for the story to work; but on the other hand, what I see on some fiction writing subreddits… the AI is often a genuine improvement over amateur writers, even in cases where the AI contradicts itself about plot elements.
Which is frustrating, because I have the feeling the novel I've been trying to finish writing for the last decade may be usurped by AI before I get my final draft.
What point are you trying to make here? That amateur writers are amateurs? That AI is only "often" an improvement over an amateur?
> Which is frustrating, because I have the feeling the novel I've been trying to finish writing for the last decade may be usurped by AI before I get my final draft.
This statement shows such a warped attitude towards art and the creative process. What do you mean "usurped?" Do you actually believe that LLMs will overtake humans when it comes to creative works?
If so, you don't really understand what is compelling about the written word or what makes for good writing and reading and it's no wonder you feel as though your own writing is so substandard.
I highly doubt your writing is that bad. Especially if you've been working on it for a decade.
I'm not sure if the following statement will help your confusion, but most who judge the quality of a story do so without being able to write that story. Critiquing and writing are different skills.
(This is why I believe LLM performance is best judged against human inner voice/system 1 reasoning, not the entirety of human thinking. When thinking with system 1, people don't really have an idea what they're doing either - they're just doing stuff that feels right.)
Also note that "sounds right to a human" is literally the loss function on which LLMs are trained, so between heaps of training inputs and subsequent extensive RLHF, the process is by its very construction aiming optimizing for above-human-average performance across the board.
No, it’s not. You’re making my statement abstract for the sake of arguing.
I’m not a cook, doctor, or a lawyer. I can’t prepare meals for a party of more than 2.
I can’t perform surgery.
I can’t effectively defend myself in a court of law.
I (and I assume OP) have programming expertise.
I can write exactly all code an llm could write.
For simple scripts, demos and other easily Googleable tasks, LLMs will be faster, but it’s nothing out of reach for me.
These tools won’t force you to pay a subscription to code. You don’t need them if you already have experience.
> I’m not a cook, doctor, or a lawyer. I can’t prepare meals for a party of more than 2.
They are demonstrating how over-broad your own statement was with an *equivalent* statement to show how it only passes on an unhelpful technicality.
Immediately after your quotation is this:
> you only need to spend 5+ years in medical school + whatever extra it takes to become proficient
LLMs pass the bar exam and the medical exam. These are things which I assume I would be able to do myself if only I were willing to dedicate 5 years of my life to each.
> I can write exactly all code an llm could write.
I can often see many errors in the code that ChatGPT produces. Within my domain, it's just a speed-up, a first draft I have to fix. Outside my domain, it knows what I *can't* Google because I've never heard the keyword that would allow me to.
On legal questions, ChatGPT (despite passing the bar exam) seems to make up cases. I belive this because I can google the cases and fail to find them. Is this because they don't exist, or because they're not indexed on Google? I don't have the legal background necessary to know — and it would take me years to get the knowledge necessary to differentiate "it's worse than first glance" from "it's better than second glance".
LLMs only started to because they could follow the questions.
But even that aside, it doesn't matter why LLMs can do what they can do or what else can also do that, what matters is that it would take most humans several years to get to the level of current LLMs in a subject that human isn't already familiar with.
If your job is to write software, then you're the accountant or lawyer or doctor. Otherwise, what do we even bring to the table?
I use that with avante.vim for tedious refactors. All local.
I think you are approaching this with the wrong mindset. I see it as I'm paying somebody to type and document for me. If you treat LLMs like a power tool, it is very easy to do a cost benefit analysis.
So we're going back to the last century, but given we are in a different computing context, only the stuff that can be gated via digital stores, or Web Services, gets to have a way to force people to pay.
But I am glad we now have more paid options available. Tooling is important and people that do good work should be able to charge for high quality tools.
I would be much happier in a world full of tools licensed like Sublime Text, where I can purchase a license and just run it without the need to constantly phone home though.
Nothing stopping you to build the world you want really.
There's no moat, all the clever prompting tricks Cursor et al. are just that - there is no secret sauce besides the model at the other end.
Complexity isn't an issue either, have the model write the interface to itself.
I'm not understanding what it is about a private company launching a product that changes that?
You can do it without IDEs, nothing is stopping you. I don't think this is a new phenomenon though.
You are free to coding without spend a dime, these AI dev tool cost money because these LLM cost money to run
You can get the same experience with open source tools that you can run your own model on your pc
I mean you don't need to if you don't want to. I am gainfully employed as a software developer and what I do everyday is literally just fire up Emacs on my Linux machine and write code. To this day I haven't figured out what llms are supposed to do that a bunch of yasnippets don't.
Just like five years ago most of my day is reading and debugging code, I'm not limited by how fast I can type.
It is kind of terrifying that I probably would stop coding for the day if those subscriptions end. (I get far too much convenience out of them)
I have tried to rationalize it by the fact that I do pay for internet, and version control, and my peripherals etc
The problem is that coding was a passion, but turned out to be very lucrative profession so loads of people who can't do it want to do it.
This is why we have languages like Go, and AI tools: allow people who don't want to learn how to be developers, to get a job as developers.
Also 20$ per month is way less than what it costs them to run it. Eventually they will need to charge way more to cover their costs, and the people who can't code without an AI assistant will need to pony up :)
That only applies to regular ChatGPT use.
And developers actively using AI for coding can easily spend more than $20/mo for the API.
There are people spending $10-15/day in OpenAI API usage working through Cline.
If you’re not running the model locally, you’re sending your code to them for analysis. Now ByteDance has it.
The issue would be based on the terms of employment and the software license. There’s likely a provision that just says “don’t share” regardless of what the other party will use it for.
To OP’s point, if your company is paying for the sub, then sending the codebase data would be an approved use of the codebase as part of your job.
I hope your current and future employers never find this side of your personality :D
If it benefits you more than 1%, then you're in profit.
Of course, if you're in a job that doesn't actually care about performance, and performing won't lead to better salary at some point, then it may not matter.
I get making economic/stats based analysis like this, but is your boss going to notice that 1% to give you a raise they otherwise wouldn’t? Probably not…
Your company culture can be performance-minded and this still be true.
The real problem however is, I cannot simply share my employer's repos to be absorbed by any LLM out there. So I use only the tools that my employer provides and approves of. Currently that is Microsoft Copilot chat/RAG via my work account. It takes some copy/paste and adaptations of problems/solutions but it is much more efficient than using SO. It is also a great teacher that never gets tired of my plenty why/how questions.
In my view, the future is that LLMs can train on entire private code repos until it understands its ins and outs. Currently it would need to fit in the context window, hence you need to babyspoon it, as I understand things.
In this case it tricks you because it assumes that the LLMs increase productivity and launders that into the calculation. For me, and many people, LLM usage decreases my productivity.