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In a chat bot coding world, how do we ever progress to new technologies? The AI has been trained on numerous people's previous work. If there is no prior art, f
by pacman128 6mo ago
In a chat bot coding world, how do we ever progress to new technologies? The AI has been trained on numerous people's previous work. If there is no prior art, for say a new language or framework, the AI models will struggle. How will the vast amounts of new training data they require ever be generated if there is not a critical mass of developers?
- kstrauser 6mo agoThat’s factually untrue. I’m using models to work on frameworks with nearly zero preexisting examples to train on, doing things no one’s ever done with them, and I know this because I ecosystem around these young frameworks. Models can RTFM (and code) and do novel things, demonstrably so.
- allthetime 6mo agoYeah. I work with bleeding edge zig. If you just ask Claude to write you a working tcp server with the new Io api, it doesn’t have any idea what it’s doing and the code doesn’t compile. But if you give it some minimal code examples, point it to the recent blog posts about it, and paste in relevant points from std it does incredibly well and produce code that it has not been trained on.
- SV_BubbleTime 6mo agoIt’s always been about context, then being able to communicate it. Manager people or managing a hyper-knowledgeable intern (LLM). If you know what you need, actually want what you want (super difficult), and have the ability to provide context to someone else… management has always been easier for you than others. I find one of the more interesting things about the current “AI debate” is that many programmers are autistic or at least close one side of an empathetic spectrum that they’ve always had trouble communicating what is needed for a task and why. So it’s hard for me to take the opinions going around.
- qweiopqweiop 6mo agoIt also needs a validation loop. Give it the compiler output and I bet it would fix that code even without examples/a blog post.
- coldtea 6mo ago>I’m using models to work on frameworks with nearly zero preexisting examples to train on Zero preexisting examples of your particular frameworks. Huge number of examples of similar existing frameworks and code patterns in their training set though. Still not a novel thing in any meaningful way, not any more than someone who has coded in dozens of established web frameworks, can write against an unfamiliar to them framework homegrown at his new employer.
- thunky 6mo ago> Still not a novel thing in any meaningful way Right. What you're saying is that barely anyone is doing truly novel work. 100% agree.
- coldtea 6mo agoAlmost no e.g. web or app or enterprise or even game developer is doing any novel work, does that come as a surprise? And is that fact supposed to be an argument in favor of how LLMs can do novel work and move the state of the art (which is what we're arguing about). I mean, "LLMs can do novel work because: barely anyone is doing truly novel work" doesn't really compute as an argument.
- thunky 6mo agoWhat I'm saying is that LLMs don't have to do truly novel work in order to be useful. They are useful because the lion's share of all work is a variation on an existing theme (even if the creator may not realize it).
- kstrauser 6mo agoI'm not talking about web frameworks. I'm talking about other frontiers with darn near zero preexisting examples, and no code samples to borrow from in any language or in any similar framework (because there is no such thing). "LLMs can only emit things they've been trained on" is wholly obsolete.
- 6mo ago
- danielbln 6mo agoInject the prior art into the (ever increasing) context window, let in-context-learning to its thing and go?
- justonceokay 6mo agoMost art forms do not have a wildly changing landscape of materials and mediums. In software we are seeing things slow down in terms of tooling changes because the value provided by computers is becoming more clear and less reliant on specific technologies. I figure that all this AI coding might free us from NIH syndrome and reinventing relational databases for the 10th time, etc.
- realusername 6mo agoThe bar to create the new X framework has just been lowered so I expect the opposite, even more churn.
- justonceokay 6mo agoYes but no AI will know how to use your new framework so it will not get adopted
- marcus_holmes 6mo agoAll frameworks make some assumptions and therefore have some constraints. There was always a well-understood trade-off when using frameworks of speeding up early development but slowing down later development as the system encountered the constraints. LLMs remove the time problem (to an extent) and have more problems around understanding the constraints imposed by the framework. The trade-off is less worth it now. I have stopped using frameworks completely when writing systems with an LLM. I always tell it to use the base language with as few dependencies as possible.
- LtWorf 6mo agoIf you are doing js, that makes sense since all the frameworks are a mess anyway.
- sd9 6mo agoLLMs are very much NIH machines
- jedberg 6mo agoPeople are doing this now. It's basically what skills.sh and its ilk are for -- to teach AIs how to do new things. For example, my company makes a new framework, and we have a skill we can point an agent at. Using that skill, it can one-shot fairly complicated code using our framework. The skill itself is pretty much just the documentation and some code examples.
- NewJazz 6mo agoA framework is different than a paradigm shift or new language.
- jedberg 6mo agoYes and no. How does a human learn a new language? They use their previous experience and the documentation to learn it. Oftentimes they way someone learns a new language is they take something in an old language and rewrite it. LLMs are really good at doing that. Arguably better than humans at RTFM and then applying what's there.
- NewJazz 6mo agoAnd LLMs will get retrained eventually. So writing one good spec and a great harness (or multiple) might be enough, eventually.
- andrei_says_ 6mo agoThe question is, who made the new framework? Was it vibe coded by someone who does not understand its code?
- jedberg 6mo agoNo, it was created by our team of engineers over the last three years based on years of previous PhD research.
- majormajor 6mo agoIsn't the "skill" just stuff that gets put into the context? Usually with a level of indirection like "look at this file in this situation"? How long can you keep adding novel things into the start of every session's context and get good performance, before it loses track of which parts of that context are relevant to what tasks? IMO for working on large codebases sticking to "what the out of the box training does" is going to scale better for larger amounts of business logic than creating ever-more not-in-model-training context that has to be bootstrapped on every task. Every "here's an example to think about" is taking away from space that could be used by "here is the specific code I want modified." The sort of framework you mention in a different reply - "No, it was created by our team of engineers over the last three years based on years of previous PhD research." - is likely a bit special, if you gain a lot of expressibility for the up-front cost, but this is very much not the common situation for in-house framework development, and could likely get even more rare over time with current trends.
- pklausler 6mo agoThis would also mean that we should design new programming languages out of sight of LLMs in case we need to hide code from them.
- CamperBob2 6mo agoIn a chat bot coding world, how do we ever progress to new technologies? Funny, I'd say the same thing about traditional programming. Someone from K&R's group at Bell Labs, straight out of 1972, would have no problem recognizing my day-to-day workflow. I fire up a text editor, edit some C code, compile it, and run it. Lather, rinse, repeat, all by hand. That's not OK. That's not the way this industry was ever supposed to evolve, doing the same old things the same old way for 50+ years. It's time for a real paradigm shift, and that's what we're seeing now. All of the code that will ever need to be written already has been. It just needs to be refactored, reorganized, and repurposed, and that's a robot's job if there ever was one.
- rustystump 6mo agoWhile i dont disagree with the larger point here i do disagree that all the code we ever need has been written. There are still soooooo many new things to uncover in that domain.
- CamperBob2 6mo agoLike what?
- cgh 6mo agoNew cryptography algorithms, particularly post-quantum cryptography New zero-knowledge proofs Video compression And so forth.
- atomic_reed 6mo ago[dead]
- CamperBob2 6mo agoThose are all instances of reuse of existing techniques in new contexts. And when genuinely-new algorithms do arise from genuinely-new areas of study, it's easy enough to teach LLMs how to apply and deploy them.
- derrak 6mo agoMaybe you’re right about modern LLMs. But you seem to be making an unstated assumption: “there is something special about humans that allow them to create new things and computers don’t have this thing.” Maybe you can’t teach current LLM backed systems new tricks. But do we have reason to believe that no AI system can synthesize novel technologies. What reason do you have to believe humans are special in this regard?
- adamiscool8 6mo agoAfter thousands of years of research we still don’t fully understand how humans do it, so what reason (besides a sort of naked techno-optimism) is there to believe we will ever be able to replicate the behavior in machines?
- derrak 6mo agoThe Church-Turing thesis comes to mind. It would at least suggest that humans aren’t capable of doing anything computationally beyond what can be instantiated in software and hardware. But sure, instantiating these capabilities in hardware and software are beyond our current abilities. It seems likely that it is possible though, even if we don’t know how to do it yet.
- sophrosyne42 6mo agoThe church turing thesis is about following well-defined rules. It is not about the system that creates or decides to follow or not follow such rules. Such a system (the human mind) must exist for rules to be followed, yet that system must be outside mere rule-following since it embodies a function which does not exist in rule-following itself, e.g., the faculty of deciding what rules are to be followed.
- derrak 6mo agoWe can keep our discussion about church turing here if you want. I will argue that the following capacities: 1. creating rules and 2. deciding to follow rules (or not) are themselves controlled by rules.
- charcircuit 6mo agoYou can just have AI generate its own synthetic data to train AI with. If you want knowledge about how to use it to be in the a model itself.
- lifis 6mo agoYou can have the LLM itself generate it based on the documentation, just like a human early adopter would
- fritzo 6mo agoThe same could be asked about people. The answer is social intelligence.
- storus 6mo agoThere is even a bigger problem; if AI didn't see your framework, you don't exist. Soon AI companies will be asking for money from devs to include their frameworks in the training dataset. Worse than Google's SEO that could at least be gamed somewhat.
- thinkindie 6mo agoI don't think people discovered frameworks with Google, nor they are going to do so with LLMs. It might be a different topic for libraries.
- storus 6mo agoIf no coding agent offers your framework as a choice for code generation, your framework might not even exist, you'd get the same outcome.
- nurettin 6mo agoI still research efficient algorithms. You can describe these to LLMs and they do it without any prior art. They just took away the stomach churners. In fact, we probably started a communist revolution in software with anthropic/openai streaming your solutions to lesser coders.
- imtringued 6mo agoYou're actually better off using the LLM to consult textbooks from the 70s, because most likely someone already came up with a better algorithm that hasn't seen adoption yet.
- nurettin 6mo agoRude!
- Schlagbohrer 6mo agoAccording to the nobel prize winner Geoffrey Hinton, these LLMs will be able to talk to each other and self-train in the same way that AlphaGo started playing games against itself to be able to surpass all human experts, on who's games it had originally been trained and therefore originally been restricted to their ability. This is how LLMs will surpass human knowledge rather than being limited to a statistical average from human generated training data.
- MattGrommes 6mo agoLook at the history of art. Lots of people used the same paint that had always been used and the same brushes, and came up with wildly different uses for those tools. Until there are literally no people involved, we'll always be using the tools in new ways.