5 ms·

when I started coding at the age of 11 in machine code and assembly on the C64, the dream was to create software that creates software. Nowadays it's almost rea

by darqis 1y ago

when I started coding at the age of 11 in machine code and assembly on the C64, the dream was to create software that creates software. Nowadays it's almost reality, almost because the devil is always in the details. When you're used to write code, writing code is relatively fast. You need this knowledge to debug issues with generated code. However you're now telling AI to fix the bugs in the generated code. I see it kind of like machine code becomes overlaid with asm which becomes overlaid with C or whatever higher level language, which then uses dogma/methodology like MVC and such and on top of that there's now the AI input and generation layer. But it's not widely available. Affording more than 1 computer is a luxury. Many households are even struggling to get by. When you see those what 5 7 Mac Minis, which normal average Joe can afford that or does even have to knowledge to construct an LLM at home? I don't. This is a toy for rich people. Just like with public clouds like AWS, GCP I left out, because the cost is too high and running my own is also too expensive and there are cheaper alternatives that not only cost less but also have way less overhead. What would be interesting to see is what those kids produced with their vibe coding.

diggan 1y ago
> those kids produced with their vibe coding No one, including Karpathy in this video, is advocating for "vibe coding". If nothing more, LLMs paired with configurable tool-usage, is basically a highly advanced and contextual search engine you can ask questions. Are you not using a search engine today? Even without LLMs being able to produce code or act as agents they'd be useful, because of that. But it sucks we cannot run competitive models locally, I agree, it is somewhat of a "rich people" tool today. Going by the talk and theme, I'd agree it's a phase, like computing itself had phases. But you're gonna have to actually watch and listen to the talk itself, right now you're basically agreeing with the video yet wrote your comment like you disagree.
dist-epoch 1y ago
> This is a toy for rich people GitHub copilot has a free tier. Google gives you thousands of free LLM API calls per day. There are other free providers too.
- guappa 1y ago
  1st dose is free
  - infecto 1y ago
    LLM APIs are pretty darn cheap for most of the developed worlds income levels.
    - guappa 1y ago
      Yeah, because they're bleeding money like crazy now. You should consider how much it actually costs, not how much they charge. How do people fail to consider this?
      - bdangubic 1y ago
        how much does it cost?
      - infecto 1y ago
        >You should consider how much it actually costs, not how much they charge. How do people fail to consider this? Sure, nobody can predict the long-term economics with certainty but companies like OpenAI already have compelling business fundamentals today. This isn’t some scooter startup praying for margins to appear; it’s a platform with real, scaled revenue and enterprise traction. But yeah, tell me more about how my $200/mo plan is bankrupting them.
      - NitpickLawyer 1y ago
        No, there are 3rd party providers that run open-weights models and they are (most likely) not bleeding money. Their prices are kind of similar, and make sense in a napkin-math kind of way (we looked into this when ordering hardware). You are correct that some providers might reduce prices for market capture, but the alternatives are still cheap, and some are close to being competitive in quality to the API providers.
        1y ago
infecto 1y ago
This is most definitely not toys for rich people. Now perhaps depending on your country it may be considered rich but I would comfortably say that for most of the developed world, the costs for these tools are absolutely attainable, there is a reason ChatGPT has such a large subscriber base. Also the disconnect for me here is I think back on the cost of electronics, prices for the level of compute have generally gone down significantly over time. The c64 launched around the $5-600 price level, not adjusted for inflation. You can go and buy a Mac mini for that price today.
- bawana 1y ago
  I suspect that economies of scale are different for software and hardware. With hardware, iteration results in optimization of the supply chain, volume discount as the marginal cost is so much less than the fixed cost, and lower prices in time. The purpose of the device remains fixed. With software, the software becomes ever more complex with technical debt - featuritis, patches, bugs, vulnerabilities, and evolution of purpose to try and capture more disparate functions under one environment in an attempt to capture and lock in users. Price tends to increase in time. (This trajectory incidentally is the opposite of the unix philosophy - having multiple small fast independent tools than can be concatenated to achieve a purpose.) This results in ever increasing profits for software and decreasing profits for hardware at equilibrium. In the development of AI we are already seeing this-first we had gpt, then chatbots, then agents, now integration with existing software architectures.Not only is each model ever larger and more complex (RNN->transformer->multihead-> add fine tuning/LoRA-> add MCP), but the bean counters will find ways to make you pay for each added feature. And bugs will multiply. Already prompt injection attacks are a concern so now another layer is needed to mitigate those. For the general public, these increasing costs will besubsidized by advertising. I cant wait for ads to start appearring in chatGPT- it will be very insidious as the advertising will be comingled with the output so there will be no way to avoid it.
  - infecto 1y ago
    I’m struggling to follow your argument, it feels more speculative than evidence-based. Runtime costs have consistently fallen. As for advertising, it’s possible, but with so many competitors and few defensible moats, there’s real pressure to stay ad-free. These tools are also positioned to command pricing power in a way search never was, given search has been free for decades. The hardware vs. software angle seems like a distraction. My original point was in response to the claim that LLMs are “toys for the rich.” The C64 was a rich kid’s toy too—and far less capable.
kordlessagain 1y ago
Kids? Think about all the domain experts, entrepreneurs, researchers, designers, and creative people who have incredible ideas but have been locked out of software development because they couldn't invest 5-10 years learning to code. A 50-year-old doctor who wants to build a specialized medical tool, a teacher who sees exactly what educational software should look like, a small business owner who knows their industry's pain points better than any developer. These people have been sitting on the sidelines because the barrier to entry was so high. The "vibe coding" revolution isn't really about kids (though that's cute) - it's about unleashing all the pent-up innovation from people who understand problems deeply but couldn't translate that understanding into software. It's like the web democratized publishing, or smartphones democratized photography. Suddenly expertise in the domain matters more than expertise in the tools.
- nevertoolate 1y ago
  It sounds too good to be true. Why do you think llm is better in coding then in how education software should be designed?
- pphysch 1y ago
  > These people have been sitting on the sidelines because the barrier to entry was so high. This comment is wildly out of touch. The SMB owner can now generate some Python code. Great. Where do they deploy it? How do they deploy it? How do they update it? How do they handle disaster recovery? And so on and so forth. LLMs accelerate only the easiest part of software engineering, writing greenfield code. The remaining 80% is left as an exercise to the reader.
  - bongodongobob 1y ago
    All the devs I work with would have to go through me to touch the infra anyway, so I'm not sure I see the issue here. No one is saying they need to deploy fully through the stack. It's a great start for them and I can help them along the way just like I would with anyone else deploying anything.
    - 1y ago
kapildev 1y ago
>What would be interesting to see is what those kids produced with their vibe coding. I think you are referring to what those kids in the vibe coding event produced. Wasn't their output available in the video itself?

by darqis 1y ago

diggan 1y ago

> those kids produced with their vibe coding No one, including Karpathy in this video, is advocating for "vibe coding". If nothing more, LLMs paired with configurable tool-usage, is basically a highly advanced and contextual search engine you can ask questions. Are you not using a search engine today? Even without LLMs being able to produce code or act as agents they'd be useful, because of that. But it sucks we cannot run competitive models locally, I agree, it is somewhat of a "rich people" tool today. Going by the talk and theme, I'd agree it's a phase, like computing itself had phases. But you're gonna have to actually watch and listen to the talk itself, right now you're basically agreeing with the video yet wrote your comment like you disagree.

dist-epoch 1y ago

> This is a toy for rich people GitHub copilot has a free tier. Google gives you thousands of free LLM API calls per day. There are other free providers too.

guappa 1y ago
1st dose is free
- infecto 1y ago
  LLM APIs are pretty darn cheap for most of the developed worlds income levels.
  - guappa 1y ago
    Yeah, because they're bleeding money like crazy now. You should consider how much it actually costs, not how much they charge. How do people fail to consider this?
    - bdangubic 1y ago
      how much does it cost?
    - infecto 1y ago
      >You should consider how much it actually costs, not how much they charge. How do people fail to consider this? Sure, nobody can predict the long-term economics with certainty but companies like OpenAI already have compelling business fundamentals today. This isn’t some scooter startup praying for margins to appear; it’s a platform with real, scaled revenue and enterprise traction. But yeah, tell me more about how my $200/mo plan is bankrupting them.
    - NitpickLawyer 1y ago
      No, there are 3rd party providers that run open-weights models and they are (most likely) not bleeding money. Their prices are kind of similar, and make sense in a napkin-math kind of way (we looked into this when ordering hardware). You are correct that some providers might reduce prices for market capture, but the alternatives are still cheap, and some are close to being competitive in quality to the API providers.
      - 1y ago

infecto 1y ago

This is most definitely not toys for rich people. Now perhaps depending on your country it may be considered rich but I would comfortably say that for most of the developed world, the costs for these tools are absolutely attainable, there is a reason ChatGPT has such a large subscriber base. Also the disconnect for me here is I think back on the cost of electronics, prices for the level of compute have generally gone down significantly over time. The c64 launched around the $5-600 price level, not adjusted for inflation. You can go and buy a Mac mini for that price today.

bawana 1y ago
I suspect that economies of scale are different for software and hardware. With hardware, iteration results in optimization of the supply chain, volume discount as the marginal cost is so much less than the fixed cost, and lower prices in time. The purpose of the device remains fixed. With software, the software becomes ever more complex with technical debt - featuritis, patches, bugs, vulnerabilities, and evolution of purpose to try and capture more disparate functions under one environment in an attempt to capture and lock in users. Price tends to increase in time. (This trajectory incidentally is the opposite of the unix philosophy - having multiple small fast independent tools than can be concatenated to achieve a purpose.) This results in ever increasing profits for software and decreasing profits for hardware at equilibrium. In the development of AI we are already seeing this-first we had gpt, then chatbots, then agents, now integration with existing software architectures.Not only is each model ever larger and more complex (RNN->transformer->multihead-> add fine tuning/LoRA-> add MCP), but the bean counters will find ways to make you pay for each added feature. And bugs will multiply. Already prompt injection attacks are a concern so now another layer is needed to mitigate those. For the general public, these increasing costs will besubsidized by advertising. I cant wait for ads to start appearring in chatGPT- it will be very insidious as the advertising will be comingled with the output so there will be no way to avoid it.
- infecto 1y ago
  I’m struggling to follow your argument, it feels more speculative than evidence-based. Runtime costs have consistently fallen. As for advertising, it’s possible, but with so many competitors and few defensible moats, there’s real pressure to stay ad-free. These tools are also positioned to command pricing power in a way search never was, given search has been free for decades. The hardware vs. software angle seems like a distraction. My original point was in response to the claim that LLMs are “toys for the rich.” The C64 was a rich kid’s toy too—and far less capable.

kordlessagain 1y ago

Kids? Think about all the domain experts, entrepreneurs, researchers, designers, and creative people who have incredible ideas but have been locked out of software development because they couldn't invest 5-10 years learning to code. A 50-year-old doctor who wants to build a specialized medical tool, a teacher who sees exactly what educational software should look like, a small business owner who knows their industry's pain points better than any developer. These people have been sitting on the sidelines because the barrier to entry was so high. The "vibe coding" revolution isn't really about kids (though that's cute) - it's about unleashing all the pent-up innovation from people who understand problems deeply but couldn't translate that understanding into software. It's like the web democratized publishing, or smartphones democratized photography. Suddenly expertise in the domain matters more than expertise in the tools.

nevertoolate 1y ago
It sounds too good to be true. Why do you think llm is better in coding then in how education software should be designed?
pphysch 1y ago
> These people have been sitting on the sidelines because the barrier to entry was so high. This comment is wildly out of touch. The SMB owner can now generate some Python code. Great. Where do they deploy it? How do they deploy it? How do they update it? How do they handle disaster recovery? And so on and so forth. LLMs accelerate only the easiest part of software engineering, writing greenfield code. The remaining 80% is left as an exercise to the reader.
- bongodongobob 1y ago
  All the devs I work with would have to go through me to touch the infra anyway, so I'm not sure I see the issue here. No one is saying they need to deploy fully through the stack. It's a great start for them and I can help them along the way just like I would with anyone else deploying anything.
  - 1y ago

kapildev 1y ago

>What would be interesting to see is what those kids produced with their vibe coding. I think you are referring to what those kids in the vibe coding event produced. Wasn't their output available in the video itself?