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> It's entirely clear that every last human will be beaten on code design in the upcoming years Citation needed. In fact, I think this pretty clearly hits the
by DanHulton 1y ago
> It's entirely clear that every last human will be beaten on code design in the upcoming years
Citation needed. In fact, I think this pretty clearly hits the "extraordinary claims require extraordinary evidence" bar.
- pinoy420 1y ago[dead]
- coffeemug 1y agoAlphaGo.
- giovannibonetti 1y agoA board game has a much narrower scope than programming in general.
- kaliqt 1y agoTrends would dictate that this will keep scaling and surpass each goalpost year by year.
- sweezyjeezy 1y agoI would argue that what LLMs are capable of doing right now is already pretty extraordinary, and would fulfil your extraordinary evidence request. To turn it on its head - given the rather astonishing success of the recent LLM training approaches, what evidence do you have that these models are going to plateau short of your own abilities?
- sigmaisaletter 1y agoWhat they do is extraordinary, but it's not just a claim, they actually do, their doing so is evidence. Here someone just claimed that it is "entirely clear" LLMs will become super-human, without any evidence. https://en.wikipedia.org/wiki/Extraordinary_claims_require_extraordinary_evidence https://en.wikipedia.org/wiki/Extraordinary_claims_require_e...
- sweezyjeezy 1y agoAgain - I'd argue that the extraordinary success of LLMs, in a relatively short amount of time, using a fairly unsophisticated training approach, is strong evidence that coding models are going to get a lot better than they are right now. Will it definitely surpass every human? I don't know, but I wouldn't say we're lacking extraordinary evidence for that claim either. The way you've framed it seems like the only evidence you will accept is after it's actually happened.
- sigmaisaletter 1y agoWell, predicting the future is always hard. But if someone claims some extraordinary future event is going to happen, you at least ask for their reasons for claiming so, don't you. In my mind, at this point we either need (a) some previously "hidden" super-massive source of training data, or (b) another architectural breakthrough. Without either, this is a game of optimization, and the scaling curves are going to plateau really fast.
- sweezyjeezy 1y agoA couple of comments a) it hasn't even been a year since the last big breakthrough, the reasoning models like o3 only came out in September, and we don't know how far those will go yet. I'd wait a second before assuming the low-hanging fruit is done. b) I think coding is a really good environment for agents / reinforcement learning. Rather than requiring a continual supply of new training data, we give the model coding tasks to execute (writing / maintaining / modifying) and then test its code for correctness. We could for example take the entire history of a code-base and just give the model its changing unit + integration tests to implement. My hunch (with no extraordinary evidence) is that this is how coding agents start to nail some of the higher-level abilities.
- mark_l_watson 1y agoI recently asked o4-mini-high for a system design of something moderately complicated and provided only about 4 paragraphs of prompt for what I wanted. I thought the design was very good, as was the Common Lisp code it wrote when I asked it to implement the design; one caveat though: it did a much better job implementing the design in Python than Common Lisp (where I had to correct the generated code). My friend, we are living in a world of exponential increase of AI capability, at least for the last few years - who knows what the future will bring!
- gtirloni 1y agoThat's your extraordinary evidence?
- mark_l_watson 1y agoNope, just my opinion, derived from watching monthly and weekly exponential improvement over a few year period. I worked through at least two,AI winters since 1982, so current progress is good to see.
- namaria 1y agoExponential over which metric exactly? Training dataset size, compute required yeah these have grown exponentially. But has any measure capability? Because exponentially growing costs with linear or not measurable improvements is not a great trajectory.
- mark_l_watson 1y agoExponential in how useful LLM APIs and LLM based products like Google AI Lab, ChatGPT, etc. are to me personally. I am the data point I care about. I have a pet programming problem that every few months I try to solve with the current tools of the day. I admit this is anecdotal, just my personal experiences. Metrics like training data set size are less interesting now given the utility of smaller synthetic data sets. Once AI tech is more diffused to factory automation, robotics, educational systems, scientific discovery tools, etc., then we could measure efficiency gains. My personal metric for the next 5 to 10 years: the US national debt and interest payments are perhaps increasing exponentially and since nothing will change politically to change this, exponential AI capability growth will either juice-up productivity enough to save us economically, or it won’t.
- ArthurStacks 1y agoBeating humans isnt really what matters. Its enabling developers to design who cant. Last month I had a staff member design and build a distributed system that would be far beyond their capabilities without AI assistance. As a business owner this allows me to reduce the dependency and power of the senior devs.
- auggierose 1y agoHehe, have fun with that distributed system down the line.
- ArthurStacks 1y agoWhy? We fully checked the design, what he built, and it was fully tested over weeks for security and stability. Don't parrot what you read online that these systems are unable do this stuff. It's from the clueless or devs coping. Not only are they capable but theyre improving by the month.
- goatlover 1y agoI can't tell on this site who has genuinely experienced radical changes in software development from dedicated LLM usage, and who is trying to sell something. But given previous hype cycles with all exciting new tech at the time, including past iterations of AI, I tend to believe it's more in the trying to sell something camp.
- ArthurStacks 1y agoWell, youre right to be skeptical because the majority of "AI" going on is hype designed for the purposes of either a scam, getting easy investment funds or inflating company valuations. But.. the capabilities (and rate of progression) of these top tier LLMs isn't hype.
- auggierose 1y agoOh, they are definitely capable, I am using them every day, and build my own MCP servers. But you cannot test a distributed system "fully". The only test I believe in is understanding every single line of code myself, or knowing that somebody else does. At this point, I don't trust the AI for anything, although it makes a very valuable assistant. Very soon our AI built software systems will break down in spectacular and never before seen ways, and I'll have the product to help with that.
- numpad0 1y agoWe were all crazy hyped when NVIDIA demoed end-to-end self driving, weren't we? First order derivatives of a hype cycle curve at lower X values is always extremely large but it's not so useful. At large X it's obviously obvious. It's always had been that way.
- aposm 1y agoI had a coworker making very similar claims recently - one of the more AI-positive engineers on my team (a big part of my department's job is assessing new/novel tech for real-world value vs just hype). I was stunned when I actually saw the output of this process, which was a multi-page report describing the architecture of an internal system that arguably needed an overhaul. I try to keep an open mind, but this report was full of factual mistakes, misunderstandings, and when it did manage to accurately describe aspects of this system's design/architecture, it made only the most surface-level comments about boilerplate code and common idioms, without displaying any understanding of the actual architecture or implications of the decisions being made. Not only this coworker but several other more junior engineers on my team proclaimed this to be an example of the amazing advancement of AI ... which made me realize that the people claiming that LLMs have some superhuman ability to understand and design computer systems are those who have never really understood it themselves. In many cases these are people who have built their careers on copying and pasting code snippets from stack overflow, etc., and now find LLMs impressive because they're a quicker and easier way to do the same.