311–320 of 589 posts
I think maybe they are project managers since the programming is outsourced to Ai, but the idea don't seem to catch on there
Basically, participants spent less than half an hour, 4 times, over 4 months, writing some bullcrap SAT type essay. Some participants used AI.
So to accept the premise of the article, using an AI tool once a month for 20 minutes caused noticeable brain rot. It is silly on its face.
What the study actually showed, people don't have an investment or strong memory to output they didn't produce. Again, this is a BS essay written (mostly by undergrads) in 20 minutes, so not likely to be deep in any capacity. So to extrapolate, if you have a task that requires you to understand the output, you are less likely to have a grasp of it if you didn't help produce the output. This would also be true of work some other person did.
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I can count the amount of times in my 20 year career that I've had to look at compiler generated assembly on one finger and I've never looked at the machine code produced by an assembler (other than when I wrote my own as a toy project) is the same true of LLM usage? absolutely not and it never will be, because it's not an abstraction
It's still early stages, that is why. It is not yet good enough or there is not yet sufficient trust. Also there are still resources allocated to checking the code. I saw a post yesterday showing Brave browser's new tab using 70mb of RAM in the background. I'm very sure there's code there that can be optimized, but who gives a shit. It's splitting hairs and our computers are powerful enough now that it doesn't matter…
I have been hearing (reading?) this for a solid two years now, and LLMs were not invented two years ago: they are ostensibly the same tech as they were back in 2017, with larger training pools and some optimizations along the way. How many more hundreds of billions of dollars is reasonable to throw at a technology that has never once exceeded the lofty heights of "fine"?
At this point this genuinely feels like silicon valley's fever dream. Just lighting dumptrucks full of money on fire in the hope that it does something better than it did the previous like 7 or 8 times you did it.
And normally I wouldn't give a shit, money is made up and even then it ain't MY money, burn it on whatever you want. But we're also offsetting any gains towards green energy standing up these stupid datacenters everywhere to power this shit, not to mention the water requirements.
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It's delegation then. We can use different words if you like (and I'm not convinced that delegation isn't colloquially a form of abstraction) but you can't control the world by controlling the categories.
One argument for abstraction being different from delegation, is when a programmer uses an abstraction, I'd expect the programmer to be able to work without the abstraction, if necessary, and also be able to build their own abstractions. I wouldn't have that expectation with delegation.
Managers tend to hire sub managers to manage their people. You can see this with LLM as well, people see "Oh this prompting is a lot of work, lets make the LLM prompt the LLM".
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As the other comment said, LLMs are not an abstraction. An abstraction is a deterministic, pure function, than when given A always returns B. This allows the consumer to rely on the abstraction. This reliance frees up the consumer from having to implement the A->B, thus allowing it to move up the ladder. LLMs, by their very nature are probabilistic. Probabilistic is NOT deterministic. Which means the consumer is neve…
It's delegation then. We can use different words if you like (and I'm not convinced that delegation isn't colloquially a form of abstraction) but you can't control the world by controlling the categories.
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Really? No signs of slowing down? A year or two ago when LLMs popped on the scene my coworkers would say "Look at how great this is, I can generate test cases". Now my coworkers are saying "I can still generate test cases! And if I'm _really pacificcccc_, I can get it to generate small functions too!". It seems to have slowed down considerably, but maybe that's just me.
Sorry for the bluntness, but you sound like you have a lot of opinions about LLM performance for someone who says that doesn't use them. It's okay if you are against them, but if have used them 3 years ago, you have no idea if there were improvements or not.
It's not reasonable to treat only opinions that you agree with as valid.
Some people don't use LLMs because they are familiar with them.
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We're just moving up the abstraction ladder, like we did with compilers. I don't care about the individual lines of code, I care about architecture, code structure, rigorous automated e2e tests, contracts with comprehensive validation, etc. Rather than waste a bunch of time pouring over agent PRs I just make them jump over extremely high static/analytic hurdles that guarantee functionality, then my only job is to ide…
As the other comment said, LLMs are not an abstraction. An abstraction is a deterministic, pure function, than when given A always returns B. This allows the consumer to rely on the abstraction. This reliance frees up the consumer from having to implement the A->B, thus allowing it to move up the ladder. LLMs, by their very nature are probabilistic. Probabilistic is NOT deterministic. Which means the consumer is neve…
Colleagues are the same thing. You may abstract business domains and say that something is the job of your colleague, but sometimes that abstraction breaks.
Still good enough to draw boxes and arrows around.
And, it is something we need to talk about loudly, but I guess it wouldn't crank up a number of followers or valuation of AI grifters.
Anecdote here, but when I was in grad school, I was talking to a PhD student i respected a lot. Whenever he read a paper, he would try to write the code out and get it working. I would take a couple of months but he could whip it up in a few days. He explained to me that it was just practice and the more you practice the better you become. He not only coded things quickly, he started analyzing papers quicker too and…
What I do personally is for every subject that matters to me I take the time to first think about it. To explore ideas, concepts, etc… and answer questions that would ask to ChatGPT. Only once I get a good idea I start to ask chapgpt about it.
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As the other comment said, LLMs are not an abstraction. An abstraction is a deterministic, pure function, than when given A always returns B. This allows the consumer to rely on the abstraction. This reliance frees up the consumer from having to implement the A->B, thus allowing it to move up the ladder. LLMs, by their very nature are probabilistic. Probabilistic is NOT deterministic. Which means the consumer is neve…
> An abstraction is a deterministic, pure function, than when given A always returns B. That is just not correct. There is no rule that says an abstraction is strictly functional or deterministic. In fact, the original abstraction was likely language, which is clearly neither. The cleanest and easiest abstractions to deal with have those properties, but they are not required.
1. Language is an abstraction and it's not deterministic (it's really lossy)
2. LLMs behave differently than the abstractions involved in building software, where normally if you gave the same input, you'd expect the same output.