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Cake day: July 30th, 2023

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  • No, you define what you want in project planning and briefs, coding is the interpretation of your definition. It is quickly becoming far easier and definitely faster for a machine to interpret what we define than for us to translate our definition into what a machine can interpret.

    LLMs aren’t “in their infancy”. They’re tapped out.

    And 64k oughta be enough for everyone.

    You switch to LLM’s at your convenience but you tripped over the term “AI”. We’ve been over this a few times already and I hate repeating myself.

    We can boil the issue down to a very simple question, do you think in time AI will play a significant role in how we generate code?

    If the answer is no, then I’ll see you in ten years, if the answer is yes, then you should admit that GitHub choosing that term is not out of place and it is only self evident that they use what is currently the best approach to produce code/assistance while putting it under the “AI” banner for their long term vision and because it wants and needs to ride the hype train.

    All the arguments I hear are largely pedantry and contrarianism. You see this every time something new and exciting pops up, people will huff and puff about small issues while losing track of the larger picture. The way you choose your words makes it obvious that this is just another case of that. No nuance, no, just “this is trash”, as if completely oblivious to the fact that in the time it took you to type those 3 words, a million people received an answer from an LLM that would otherwise take them 5 minutes to Google.

    You can’t decouple quality and productivity, because code that isn’t of sufficient quality is not useful, and the debt of bad code costs many, many more times more work than doing code correctly. Low quality code isn’t “doing the job”.

    But you have no idea whether the code generated is of such low quality that it offsets the time it took to produce it. That is just another assertion. For someone who is so adamant about the precision of code, you sure do throw around a lot of unfounded beliefs.

    the debt of bad code costs many, many more times more work than doing code correctly

    Like this gem for instance. Not only do you build on the unfounded premise that AI generates bad code, it also assumes a coder does not. On top of that, how much bad code? How many more times? Shouldn’t there be some quantification in all this rhetoric?


  • No, code is not imprecise. It does exactly what you tell it to every time.

    And that is exactly why it is imprecise, because it’s a human conceiving it. You don’t want code to do what you type, you want code to do what you define. It is easy to define what a program needs to do, it is not as easy to then translate that to something a machine understands. You are doing the interpretation for the machine, that is all that coding is and we will look back on this approach as comical. Now that machines have the ability to understand what we define, we can skip the harder steps and focus on building things instead of playing Rosetta stone and beating ourselves on the chest because we consider ourselves to be champions at it.

    What you are doing is comparing the perfect coder with LLM’s in their infancy and then conclude that the former makes less mistakes, I’m not sure why I have to point out that that is an unfair comparison.

    I can make the same broken comparison about AI generating images. Will a Picasso produce beter art? Of course, for the time being, but the AI generates in seconds what we humans do in hours or days. And for a very wide base of what we do, the AI is already sufficient in its job even though the technology is young.

    I’m sure you’ll agree that everywhere a form of AI has been implemented, from playing chess, go and StarCraft, to medical imaging, folding proteins… whatever, it quickly surpassed the quality of its human counterpart. Compared to those examples, generating code is a relatively easy task. And yes I understand that those use different “AI” than LLM’s.

    The study you’re linking completely ignores code quality.

    The study shows that your claim about productivity is false, now you’re moving the goalposts. You’ve made a lot of claims, but it all stems from a narrow distaste in how LLM’s function and you haven’t backed anything up.


  • That’s the “AI” GitHub uses, that they’re referring to, that is a stronger reason not to use their platform than to use it.

    You’re missing the point. You tripped over the word “AI”, then equate it to just an LLM and on top of that you claim that nobody is getting any use out of it. Not only is your argument circular, it’s also based on a false premise.

    The entire point of code is to clearly and effectively communicate what you want.

    No, the point of code is to arrive at software that does what you want. Currently, we have to describe what our software needs to do, then mangle code into doing what we want. AI, and even an LLM, has the ability to take over everything after we provide the description of what we want and even write the tests to make sure it does that. The billions spent on bug hunting, quality assurance, acceptance testing and liability cases clearly show that it is not easier than natural language. Something we start learning before we’re even born.

    But copilot and others are not just tools to spit out code, they are a replacement for search engines with the ability to not only instantly provide you with a relevant answer, but also to explain their reasoning with the ability to go back and forth about details that would otherwise take you through multiple Google searches and trawling through different websites and fora to maybe distill an answer. Clearly it goes without saying that this interface with what “the internet” knows is a major step forward to how we find and apply relevant information.

    natural language is imprecise by definition

    But so is code unless we write it to be precise. And it is far more easy and productive to define what that precision needs to be than it is to write and test. A project without unit tests is half the price of a project with tests, that alone should tell you something about the idea of precise code being easy. Knowing full well that every bit of software starts by defining it in natural language anyway. It goes without saying that if code and test generation is automated after that initial step, productivity is increased massively.

    Every attempt to demonstrate the LLMs improve productivity in software development fails miserably and shows that it doesn’t do that. It’s not capable of doing that.


    The main finding was that programmers who did not use AI completed the task in 160.89 minutes (2.7 hours) on average, whereas the programmers who had AI assistance completed the job in 71.17 minutes (1.2 hours). The difference between the two groups was statistically significant at the level of p = 0.0017.

    https://www.nngroup.com/articles/ai-programmers-productive/

    Just one example by the way…


  • LLMs are what you’re advocating for, because it’s what Copilot is.

    I was afraid you’d say this, but I gave you the benefit of the doubt. It doesn’t matter what copilot is, you tripped over the word “AI”, then reduced it to LLM’s, and are now full circle by saying copilot is an LLM.

    I think my original response to you was that you were short sighted in your argument, and this latest comment just underlines that you have issues with what AI is now, not what it is becoming.

    It doesn’t lead to better software, it doesn’t lead to more efficient development

    Eventually it will be all we need to write software.

    All for obscene energy draws to zero benefit.

    Oldmanyellsatcloud.jpg

    I’ve gotten plenty benefit out of LLM’s, and millions of people with me, maybe you’re doing it wrong? Why do you think this absurd amount of power usage can be justified? Don’t you think interest and actual usage are the reason?






  • Fewer mistakes might be a side-effect, but the real reason why this will be welcomed by the military and our dear leaders is because they don’t have to stir up the public emotionally so that we give up our sons and daughters. It will further reduce our opposition to war because “the only people dying are the bad ones”. I can’t wait to read how the next model will reduce the false positive rate with another percentage point. Of course, I think it requires little imagination or intellect to figure out what the net result will be when the most noteworthy information we get from a war is the changelog from its soldiers, who have zero emotional response to taking a life.

    Just like tasers were introduced to reduce gun incidents and are now often used as a form of cattle prod, they will function creep the shit out of this, and our adaptation to the idea of robots doing the killing will be over before we’ve perfected the technology.

    It was unavoidable though, someone always has to have the biggest gun. It’s not our technological advancement that has to adapt to our mentality, we have to adapt to technological advancement. Perhaps the nuclear bomb was simply not frightening enough to change our ways.





  • historic grievances again

    Oh the irony.

    and I myself am not attempting to broaden context in order to force an angle the article isn’t making.

    Why are people who defend Israel always such insufferable weasels?

    You’re hiding behind an article that already takes things out of context and then you act as though it is the right thing to do to not provide any.

    Of course you can’t “broaden the context”, or your entire point would fall apart. This is what Israel and its supporters do, they pick an arbitrary point in time, pretend that the conflict started then, and use that as an excuse to escalate.

    I find it extremely insulting to mine and our collective intelligence when someone tries to argue otherwise. Nobody buys your victim complex anymore, have some decency and self respect and stop peddling it.




  • In what world would a country in a similar situation not support groups that try to counter an invading force? What about the assassinations inside Iran? The terrorist attacks orchestrated by the west? The sabotage of their nuclear facilities? How is it that those things can go on for decades, and then when Iran finally reacts, people go “oh look what these maniacs did, how dare they!”

    Do you not care that Iran was on the receiving end of these things, or were you simply not aware?

    Iran has been notoriously docile because it knows the US had been looking for an excuse to attack it. Just like Wesley Clarke stated.



  • That’s like poking a bear and then halfway through your shenanigans claim you’ll have to put it down because you’re in danger. What a bunch of hollow rhetoric. There’s 3 sentences in your paragraph and each one is just a slogan. Each one vague enough that it means both nothing and anything you can think of.

    Diverting from the usual warmongering is not isolationism, in fact, the problem you allude to is the result of the former, not the other way around.

    I know it’s a crazy idea but perhaps we should look at our failed approaches from recent history and try to learn from it. But judging from your edit, you have an extremely short attention span mixed with tunnel vision. Where were you when the US and its allies assassinated people inside Iran? Funded terrorist groups to carry out attacks in Iran? Sabotaged their nuclear facilities? Or, you know, when the idea of another pre-emptive attack on that nation was so imminent that one presidential candidate figured it’d be funny to fuel that by singing “bomb bomb Iran”, based on nothing but the lie that they were close to getting a nuclear bomb?

    Was all that a festering problem that Iran should’ve responded to, or is it different when you’re on the receiving end?