I was talking to a friend recently, and i think i aligned with a similar definition.
I've seen people who talk nonstop about AI, and how it's changed everything, but then there's no quantifiable output that supports their claim.
On the other hand, I've had a friend start a business, and be able to create an app much much faster than what would have been possible in the past. He has real customers paying real money, which makes it easy to validate his claims.
I have literal quantifiable output that supports the claim when I make it. I've literally been building tools for a customer of mine since January, and while it started out kind of slow, it's now paying my bills entirely every month. I am so busy baby sitting the robots and adding new projects on that I don't really have any time to find new customers right now? But I'm thinking I should have most of the stuff they're going to need done here by the end of the year, so next up, I have to find more people and maintain their tooling...
I don't want to get into the nitty gritty, but I'm kind of at the nexus of tech and aviation with my experience in life. The result has been that I can build tools that directly apply to my customers' requirements and I know wtf I'm doing in the industry. I think if I was "just a dev" or "just a former pilot" I'd be kind of screwed because I wouldn't know what I was doing? But, the reality is that because I know how to do both I'm able to make money. I don't have to look up "what an IAP is" means or "what is the 1-4-1 rule and 2-2-1/2 rule" means or "what is an OpSpec?" frantically when I am figuring out what they need. That's quite helpful.
If you know what the hell you're doing, this is a game changer. Like, "oh, I need a custom CRM spooled up that covers things that aren't in typical CRM software" - if you're a developer you probably don't know what people actually want; if you're just an industry expert you don't know wtf sql is. But if you're kind of blend of both you can add real value.
Generalist > specialist right now. I doubt that holds for much more than about a dozen months or so.
No, my friend, if you are deeper than "just a pilot" and also capable of defining and building software (even with claude) that works and works well as extensions to industry tools like CRM, then you are not a generalist, you are an intersectional specialist of the kind Scott Adams used to talk about as "skill stacks" here:
I don't know, I was a good pilot, I'm a mediocre programmer compared to some Leet code heros or whatever, but I'm making money? And it's working? I literally see the evidence every day... that was why I responded.
I am so busy baby sitting the robots and adding new projects on that I don't really have any time to find new customers right now?
That statement seems to somewhat fly against the statement you have unparalleled productivity.
I feel like the way LLMs work involves them allowing you to do things you previously simply couldn't do but doing those tasks involves really a lot of effort at controlling the things. It's compressing "one kind of hard part" (actually writing code is another a hard part that's taken care but articulate/evaluate).
Which is to say, it seems like you're "working harder than you say"
I'd say that I am the main problem. If I was a bit cleverer, or better at time management, I'd be better at finding customers? I don't think that's an AI thing, that's a "me" thing.
Still, I'm making a living doing this, working less, and have way more control over my own life. My life kind of rules now compared to what it was a year ago.
I personally am doing some LLM work right now where, if successful, I will have accomplished what was years worth of effort in a couple of weeks.
But I feel "totally disorganized" in the way I'm doing it. I think that may be inevitable since becoming organized is a natural part of doing a project the slow, "old fashioned way" and just orienting oneself to the process can be a significant and inevitable part of the effort.
I agree that there are people who can see the potential of these tools, and are enthusiastic boosters, yet are still unable to realize the benefits for themselves for whatever reason. I feel like these people are somewhat rare, and labeling them has having a kind of psychosis strikes me as sneering elitism.
I don't think I elaborated on the type of person that I would consider having AI psychosis. It isn't just being enthusiastic. What I've seen (and it's not common, but I've seen it a few times), is this sort of arrogance around using AI, this "better than thou" attitude, and lack of consideration for things outside of AI, in their real life.
Back in the 2010s, the best, most efficient software engineers were characterized by 3 things
* end to end rough map of the entire space of compute in their head
* ability to search the internet for the right things
* ability to quickly experiment and try things to figure out how to do things
AI hasn't change that, it just made 2 and 3 into a very efficient thing.
The characterization of psychosis is best described by believing AI can do the first thing. No modern LLM can "reason" - otherwise you could give it a task like "make me money", it would ask you all the questions it needs about information that it doesn't know about and needs to know to make you money, then it would set whatever it needs to set up to make you money.
As such, you still need to know the domain entirely to be effective. When you do that, AI is fantastic at getting you to the right solution. Furthermore, its still in large part actually cheaper to higher a developer who then can use AI to build you the product that you need long term.
> No modern LLM can "reason" - otherwise you could give it a task like "make me money", it would ask you all the questions it needs about information that it doesn't know about and needs to know to make you money, then it would set whatever it needs to set up to make you money.
If that's your bar for reasoning, then most people can't reason either.
> I've seen people who talk nonstop about ________, and how it's changed everything, but then there's no quantifiable output that supports their claim.
How would you feel about applying the same rule to artists?
I've seen people who work on art nonstop and think their art is really meaningful, get really into it, but there's little output that anyone cares about or that changes the world or that anyone would pay for.
On the other hand I've had friends who created some art, and have real customers paying real money, ....so it's easy to tell their art project is meaningful. (is that the conclusion?)
Maybe something (AI, code, an AI-coded project) doesn't need to have value to others or be worth money for it to be meaningful to the person who created it.
I think a lot of artists want to have psychosis because it would improve their art ahaha.
On a more serious note - real art is not validated by making money. If you want to be a full time artist, then you also have to run a business. But if all you care about is the art, then money has no relevance.
Business on the other hand, is all about making money.
I'm not sure if there is actually any evidence of this? Criminals do very well without crypto. If you look at percent of the economy that is fraudulent, it is quite large. If you look at percentage of crypto economy that is fraudulent, it is surprisingly similar
Plenty, search for cases of ransomware for example, you will find hundreds of instances where they demand payment by cryptocurrency, at least 1B per year.
Sometimes Opus 5 (high/xhigh) feels like I'm dealing with the programmer equivalent of Zeno of Elea.
Every time, without fail, it would get me 90% of the way there and then leave a small note, exception, or deferral. When instructed to address that, Opus would somehow take nearly the same amount of time as the first 90%. And then it would finish with yet another deferral. Repeat ad infinitum.
You can sometimes get around it using the `goal` directive provided you are not subject to the constraints of mortality.
They got that from Anime seasons. Every prompt has yet another cliffhanger to keep you hooked. But the Season II story arc where Claude-chan fights the NsPasteboard boss battle on the journey to the UIViewMainController, I thought that was pretty intense. I guess I just gotta keep watching my terminal to see what happens to the main character input - rooting for him to survive the next season, but you know they always kill off the good input characters early.
Yes and the last bit is always mysterious and inscrutable. I have to think way too hard to figure out what the actual problem is. I’ve noticed it does a lot of explaining the mechanics of the problem it found, but almost never explains why it’s important until I ask.
And the worst part is that this little problem will keep sneaking into the context of future sessions, unless you spend the time to fix it. Even if it isn’t important, I’ll sometimes have Claude fix it so it will shut the F up about it going forward.
i think they took a huge bet that speaking like a ted talk was going to be a vast popular differentiator in their offering, i don't think they anticipated that people were going to make fun of it, that it could become a meme..that it could get in the way of getting stuff done and result in cancellations.
it's downright exhausting to read claude, the language style was a regression imo.
I wonder if I can make a tool for it to write messages back to me, say that it can only speak to the user through tool use, and then put a hook on that tool to prevent any of the Claude-isms
Me too. And it does it so often, that I've added a stop hook that detects "honest*" in its response and forces it to regenerate without the banned word.
On the topic of translation/ language learning, I still find Google Translate better for when I need to type emails in Russian (my older family who only speak it) as far as grammar is concerned than what LLMs spit out.
I'd be surprised if Google Translate isn't powered by a specialized, Transformer-powered model we would now recognize as a "small" language model heavily constrained to a specific task.
The transformer was invented as a machine-translation algorithm, later adapted to create LLMs. I think it's a reasonable hypothesis that a ML system designed for translation will always beat an LLM role-playing a translation system (assuming equal computing power and engineer effort).
We're going to see is a lot of stuff people use LLMs for moving back to using bespoke algorithms solving the one specific issue. LLMs are just machine learning unlocked for the masses, where you can ask it "translate this for me", "what's the sentiment of this text", and it just does it. Any of these were already achievable before LLMs, they just needed a machine learning engineer to implement.
I myself started an LLM driven project to classify and sort all the photos I've got. I just ask an LLM to poop out tags for an image. Using a proper algorithm for this is possible, but I'd need to put in some effort to actually get it set up. LLMs do make it easier since they can directly, instructively help you that set up, and provide an easy stream of training data to distill out a model perfectly fit to your usecase.
I think majority of work currently going through LLMs is such inefficient tasks that can be solved quicker and better with a limited algorithm.
Having an app means exactly nothing. How good your language skills will be after N years of learning is the actual measure of whether it's worth anything.
> ai code dev has enabled people to make tools for themselves that they didn't have before.
...that sounds pretty worthless tbh. The promise of AI wasn't that you can bang out your own little half baked duolingo clone. It was that every engineer was supposed to become hundreds or thousands of percent more productive. The assumption being that things generally would therefore get noticeably better.
We're seeing hundreds of percent more commits. We're not seeing that translate to any real world improvement of anything. That's the problem.
Call me "ignorant" if you want, but back it up by showing what all this "AI productivity" has actually accomplished in real economic terms. Not vaporware.
Out of curiosity, what real economic terms would you have to see to be convinced?
Do you mean more earnings per share for corporations or real utility impacts on social systems (e.g., more new drugs)
When I ask Claude about the AI ROI, it seems to cite that ~95% of AI PoC's are negative ROI but the 5% that do have ROI tend to have decent return -- my guess is mostly back office clean up to reduce expenses and increase revenue/profit.
IIRC Uber claim their 1.5k/mo budget lead to no new value creation.
FWIW, I look at the situation with similar skepticism. One argument you could make was what Marc Andreesen said with the hypothesis that "all the big companies get nuked", so no new valued gets created but the large market cap companies get eaten by thousands of little pirañas. Obviously, so far, that doesn't seem to be the case.
> Do you mean more earnings per share for corporations or real utility impacts on social systems (e.g., more new drugs)
I mean real utility impacts. More reliable and efficient software, better features, etc. So far we've seen none of that. In fact, it seems like the opposite--more volume but a much lower quality product.
Hang on! What's the proposed causal chain from AI to famine here? Inference -> energy prices -> fertilizer/food prices? Or are you referring to the war?
Most people would prefer an excellent language learning app to simply be available and ready for them to use, rather than having to come up with how such an app could best work, and to get an AI to implement it by themselves, and having to iterate on that. Just like most people simply want to buy nice clothes, and don’t want to become fashion designers and managers of a clothing factory. So far it doesn’t look like AI is making the former (readily available excellent apps) more widespread.
As someone also building a language-learning app for myself, it's not too hard to create an excellent app right now, but the "readily available" part of your requirements is now 10x harder than a few years ago. Users are getting bombarded by new apps, so marketing an app, which was already hard before AI, is now much, much harder.
I could try to market this app, but I tried that 2 years ago, and it was already essentially a failure. So I'm probably going to keep it for myself or just try to find a few users who like it and will use it for free.
I think I agree. But it's nice to have the option. Furthermore, i think it's too early to see the results of this, as technology takes a while to diffuse. Since there are so many people trying to take advantage of the hype to make a quick buck, it takes time to figure out what is actually useful and what is not
You probably can't build such a model without unlimited access to YouTube and Google has been tightening the screws on that over the years pretty systematically.
to be fair, all it's doing is sampling the frames and maybe doing transcription, if I'm not mistaken. So you can do it with the other models too, you just need to sample the frames yourself and do the transcript yourself
it does this at a variable rate of frames which you can set - not sure if it is transcribing or natively understanding audio, but I think it's the latter since it is much faster than most transcription models I am aware of
Regardless you are right - I can roll my own.... but why
Yes, was going to say I use it exclusively for video and audio. The ability to give it a YouTube link through the API and ask questions about it is awesome
I've built some tools using AI. A custom GUI that has "copy context" and "copy image" buttons, to make prompting easy, and the camera position is persisted to disk on each change so that the agent can run a command to get a screenshot of it.
I'm thinking about inlining an AI chat window directly - I guess I might fire off a prompt to do that right now.
Personally both, i use openscad with opencode, and paste images but it is pretty often the modell decides by itself it wants to see a render and uses the render shell commands to get a image to look at.
I also agree with this. LLMs are a great companion when reading a book to clarify things and dive into specific topics.
I'd imagine an application that uses LLMs will be created that better manages learning. It's just not clear what that UX is yet- it's obviously not just a chatbot
I've seen a few that have been shared - I'll link them here if I can find them.
I think right now most people here and on twitter have no taste, and post slop that were just sort of one shotted.
But there are people using these tools in a sort of hybrid way, which I think has incredible potential. You can use it to do CGI on existing footage, in a way that's orders of magnitudes faster and cheaper than current CGI methods.
I also think that the most viable models will be video-to-video, and audio-to-audio.
If you've read A Young Lady's Illustrated Primer, I think you might get what I'm saying. But essentially, you can capture a lot of emotion, expression, etc, using a cheap camera and a single actor, and then use AI to "stylize" it in a really cheap effective way, while keeping the emotion/expression. Adding lighting for example, upscaling the quality, changing the voice timbre while keeping the pacing, etc.
I've seen people who talk nonstop about AI, and how it's changed everything, but then there's no quantifiable output that supports their claim.
On the other hand, I've had a friend start a business, and be able to create an app much much faster than what would have been possible in the past. He has real customers paying real money, which makes it easy to validate his claims.
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