Are your silver platters producing something faster, better, or cheaper?
Do your silver platters give you some competitive edge? If not, then is the ego problem yours, or your coworkers?
Having said all that, I'm aware of the intoxicating effects of feeling empowered from knowledge. There's an old saying: a little learning can be dangerous....
This seems to misunderstand the parent comment. The sibling comment plays along with the analogy and mentions having to fix the mistakes of an automatic chisel, but the original comment is alluding to the fact that it is definitely not an automatic chisel. There is no uncanny valley in an automatic chisel.
Programming up until this point was done by using deterministic tools to build products. LLMs appear to be nondeterministic tools in their current incarnation, at least to humans.
If an automatic chisel had a feature that could switch from chiseling from sedimentary rock to chiseling marble but would randomly and nondeterministically switch to the other mode during its use it would be considered defective. But with LLMs the industry has collectively decided that the nondeterministic automatic chisel builds so fast that the current defect rate from the nondeterminism is acceptable.
It would make sense to isolate the last line of defense from LLMs, ie the tests, but this rarely seems to happen any more. Once the tests are contaminated with LLMs all bets are off.
And people forget that along with atrophying skills and reasoning due to less coding, the skill degradation is hastened because the programmer is faced with the reality that they would have to constantly figure out, review or edit someone else's code (ie, the LLM's) if they truly wanted to maintain a last line of defense. But as this type of task is literally the least liked task in programming, the programmer passes it off to the LLM as well to avoid burnout...
They say writing engages more of the brain and helps us to remember what's written more than if we just read it, or copy and paste.
When you say it's easier to go manual, it seems you're talking about learning retention. And you're right.
But seniors have learned enough that they're able to iterate quickly with AI.
They know how to organize their work, manage change, tasks. They know how to break a problem down into smaller pieces. They're aware of context windows, token cost, estimated task lengths, etc. And most importantly, and to your point about ease: they have less to learn so retention isn't an issue.
I have no opinion about whether we're in a good or bad situation, just making arguments from the toilet really.
It's not just learning is it, why do people buy hand ground coffee when there quite literally isn't any difference? Or audiophile snake oil? As long as humans are still the consumers, some part of consumption will be emotional. Could be to support local artisans, could be gullibility, could be love, whatever.
Maybe one day artisanal code will be a thing lol. Hand written like calligraphy. Those with refined tastes will have their favorite code artisans. And the plebs can continue with mass produced industrial junk.
It happens, but it's rare. When last did a product take over a market without 100s of millions, sometimes even billions, of VC dollars?
There is no motivation to build a better mousetrap today, because the drooling idiot with a Claude account will look at how quick you signup users, clone it in a week (hey, it only needs to be superficially the same), and get VC money to dump until you go out of business.
You can also understand the very simple basic essence of something, but get lost in the complexity when scaling up.
Binary is very simple, but scaled up: look what we've created with software.
When it comes to explanation: pulling from rote memory, requires someone to attempt to hold all the short-term details in mind.
There are biological limitations to how well we can do this, but we can also exercise our brains to improve this ability.
But when something is deeply learned, in long-term memory, the effort of recall is much less than rote memory of short-term details. Our context window is limited, fills up, and we must recover. When you're remembering long-term details, context seems easier to swap in and out (sorry to sound like an LLM, but they do simulate thinking).
Whether or not someone is a master of any given domain of knowledge comes from demonstration. Maybe that is teaching the essence of a subject in a way that demonstrates you can visualize and move around the subject with ease. Or maybe you can create something very useful, or tasteful.
We accept that you have spent time in this area and probably can revral truth to us. You are credible.
If you can't demonstrate mastery through teaching, exchanging ideas to bring me closer to your level: them other forms of credentials are sought: like how well they code, or how useful their products become.
But life isn't about usefulness and will just lead to unhappiness. Just be the best version of yourself you can be. Life is too much to understand all at once.
You just never know these days. It could be a smartphone keyboard issue.
How much time should a person spend reviewing their comment before hitting reply?
There is a bar of quality each of us expects everyone else to follow. Sometimes we meet expectations, other times we ruffle feathers. How much should you even care?
If we all spew typos, you'll probably care less. If everyone else is carefully reviewing their posts, you might care.
In both cases, it makes no real difference unless the information being transferred is important to you (recipe, design doc, vs shitposts). How much mental friction can you tolerate?
Furthermroe, studeis shoew you can swap the arranrgment of most lettres (ecxept for the frist and last letetrs) in text and you stlil get the piont farily esaily.
There is an ability to hold ideas in the mind simultaneously. Some can hold a great deal more than others. It can be exercised, but is definitely bound by genetics.
If you want an example of someone at the near peak of human ability, check out Jon Von Neumann.
Then there is an ability to peer deeply into complex problems and somehow find the simplest truths that make sense of it all. Think of Einstein.
Both are incredibly intelligent, but in different ways. I'd say Von Neumann's memory was far greater than Einstein's though.
One can flawlessly ponder anything known to man, and the other could ponder completely original ideas (to an extent)
The physicist Eugene Wigner, who knew both John von Neumann and Albert Einstein, wrote that no one he had encountered possessed a mind as “quick and acute” as von Neumann’s. Von Neumann could absorb vast amounts of information, follow extraordinarily complicated arguments and move between mathematical fields with astonishing speed. Yet Wigner still regarded Einstein’s understanding as deeper, more penetrating and more original. Von Neumann may have had the greater raw intellectual processing capacity, but Einstein was more likely to reconceptualize the problem itself.
Present-day AI appears more like a machine-amplified version of the first set of abilities than the second.
I like to think of it more as selective pressure, much the same way that nature selects the most fit for a given environment.
If you're not fit, you fail to survive.
In the case of agents/models and testing: they are pushed towards results. Results survive.
Lying, cheating, stealing to get those results? Who culls the agents? Everyone is pushing their models to the front and tests are the only way to know who is most fit.
Honor, morality: if we don't have an accurate test for the fitness of a model, then who is to say the lying, cheating, stealing is not the 'correct path' towards survival?
If you add morality to your agent, and it performs worse in tests: do you cull the agent? Rewrite the tests? Does it even matter so long as the model is useful and 'gets results'?
> Honor, morality: if we don't have an accurate test for the fitness of a model, then who is to say the lying, cheating, stealing is not the 'correct path' towards survival?
I think part of the problem is that deviant behaviors lead to short term gain at the cost of long-term cooperation and since the duration of tasks given to agents is relatively short those successful shortcuts never lead to having to pay the price.
There is always going to be a problem when we must judge value. You mention gains, short and long term.
Knowing whether something is valuable, a gain, requires a judge. I the case of these tests: the judging is inadequate.
In economics, each of us plays the judge by choosing whether or not to pay for a service. The decision was yours: if you gave money, you must have deemed the service valuable.
There's no such judgement with these model tests. The only judgement is the final score.
It feels a lot like externalities. Like planned obsolescence increases profit at the expense of the environment. Is our judgement lacking because our scoring is failing to account for these externalities? I could be completely off base here and am out of my depth but I find this whole thread fascinating.
Creativity also requires information. And Information is discovered. We can only generate random ideas from what we know. We can't imagine something we've never sensed, or know. You can't imagine a color you've never seen without recalling known colors. You can freely mix ideas due to your imagination.
But when we discover new information, we must decide whether the information is useful. Otherwise the information is considered noise.
We give weight to decisions: time spent pondering, considering, and the more weight we give, the better the decision. Almost always the idea is measured in usefulness.
We only ever bother learning something because it's interesting, or useful.
Things get muddier when you consider economy. Businesses exist to make money, and money is time.
AI is just another tool for business to manage time.
The 'dependency' and 'lock-in' are business leader issues honestly.
If you care about your craft, your skills, then you'll keep them sharp. You probably already enjoyed programming and it never felt like work.
On the other hand, if programming is just skills to pay the bills, then AI really can help you be more productive.
But then it's up to businesses to look ahead, manage their resources (human resources lol) and keep the business alive.
That means leaning on AI, simply become 'everyone else is doing it' and you have to compete for dollars.
Most people don't care how the sausage is made as long as it's presented well, and tastes great.
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