511–520 of 604 posts
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Lmao what are you talking/coping about? What happened to carriage drivers is pretty well-documented. Maybe ask one of these AI chatbots, they will summarize it for you.
They drive for Uber now
No employment stability, no benefits, no health insurance, no vacations, at complete mercy of basically a single company.
Yeah, thriving.
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The key phrase is "over the last 200 years". 200 years ago there was just 1 billion people. People had decade(s) to reskill to new profession. Their offspring picked different profession if their parents didn't have good prospect. Changing profession was also not requiring half a decade learning. Now imagine that AI will make 20% people redundant over next 5 years - thats ~1.6 billion people.
To be fair most of the drop was only over a ~100 year period. BTW there is little AI makes "20% people redundant over next 5 years". I would bet $$$ against this.
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Your point being? The horses were replaced alright, carriage drivers are thriving ever since.
Lmao what are you talking/coping about? What happened to carriage drivers is pretty well-documented. Maybe ask one of these AI chatbots, they will summarize it for you.
I, in turn, suggest looking out of the window: modern carriage drivers are called truck drivers and their number is edging towards 10M worldwide.
Now add to this rail carriage drivers, sea carriage drivers and air carriage drivers. Years of progress changed the way you feed your "horse" and made reins somewhat more complex, but fundamentally nothing changed.
Scott Wu! I met Scott at a competitive programming event a few years back. He is one of a very small group of people (going back to 1989) to get a perfect raw score at the IoI, the olympiad for competitive programming. https://stats.ioinformatics.org/people/2686 Glad to see that he's putting his (unbelievable) talents to use. To give you a sense, at the event where I met him, he solved 6 problems equivalent to Leetco…
I've participated in programming olympiads and worked with people of varying skill and I would say that overall the correlation between competitive programming and software engineering in a business environment is probably like 0.2 or less.
I find that questionable. What does "software engineering in a business environment" require that a competent competitive programmer couldn't also learn?
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The obvious alternative to gradient descent here would be Bayes Formula (probabalistic Bayesian belief updates), since this addresses the exact problem that our brains evolved to optimize - how to utilize prediction failure (sensory feedback vs prediction) to make better predictions - better prediction of where the food is, what the predator will do, how to attract a mate, etc. Predict next word too (learn language),…
> The obvious alternative to gradient descent here would be Bayes Formula If you know a little about the math behind gradient descent you can see that an embedding layer followed by a softmax layer gives you exactly the best Bayes estimate. If you want a bit of structure, like every word depends on previous n words, you get a convolutional RNN which is also well studied. These ideas are natural and elegant but maybe…
Not sure what approaches you are considering as dead ends, but RNNs still have their place (e.g. Mamba), depending on what you are trying to achieve.
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> You've latched on that specific word and gone off. No, I haven't. I'm not talking about style, but something deeper. What I'm talking about is something you don't even seem to realize exists in professional writing - which is why you keep thinking I'm misunderstanding you when I am not. I've worked with professional writers, and nothing in the LLM space even comes close to them. It's not a matter of low quality vs…
>What I'm talking about is something you don't even seem to realize exists in professional writing I've read hundreds of books, fiction and otherwise. This isn't a brag, it's just to say, believe me, I know what professional writing looks like and I know where LLMs currently stand because I've used them a lot. I know the quality you can squeeze out if you're willing to let go of any presumptions. You'll notice that n…
That a professional human novelist was able to leverage GPT for their book isn't disproving the grandparent's post. They knew what good looks like, and if it wasn't good they wouldn't have kept it in the book.
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The economy clothes aren't great, but you can get a quality tailored suit for $4000. That's about 6 weeks pay for a PFC in the US Army. A roman legionnaire would pay about a gold ounce for a quality (at the time) set of clothing, however, at the cost of about 6 months pay. They don't build 'em like they used to, but those of us in the rank and file are getting better off. We can't all be "I think I will just buy Hawa…
I think there's a good point in-between a $4000 dollar tailored suit and a $0.13 tshirt made of plastic that is designed for the landfill. I'm unsure why we default to extremes on that regard. A decent made T-Shirt should cost about $40, but right now the $40 shirt costs $.10 to make. Therein lies the self-consuming nature of how things are going right now.
Price does not necessarily imply quality (branding is much more of a factor).
Even if price did imply quality for certain brands, the question would be how much more qualitative? Will it hold 10x more wash cycles or last 10x longer?
In which case a consumer could make an actually informed decision on quality vs. price.
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It's worth pointing out that on their eval set for "issues resolved" they are getting 13.86%. While visually this looks impressive compared to the others, anything that only really works 13.86% of the time, when the verification of the work takes nearly as much time as the work would have anyway, isn't useful. The problem with this entire space is that we have VC hype for work that should ultimately still be being do…
> It's worth pointing out that on their eval set for "issues resolved" they are getting 13.86%. While visually this looks impressive compared to the others, anything that only really works 13.86% of the time, when the verification of the work takes nearly as much time as the work would have anyway, isn't useful. Yeah, I remember speech recognition taking decades to improve, and being more of a novelty - not useful at…
There is no way this is going to make it so that "engineers can focus on more interesting problems and engineering teams can strive for more ambitious goals." Instead it will mean that bosses can fire 75-90% of the (very expensive) engineers, with the ones who remain left to prompt the AI and clean up any mistakes/misunderstandings. I guess this is the future. We've coded ourselves out of a job. People are smiling an…
Software engineering still needs a human in the loop, just like art still needs to be prompted and tweaked by a human that can do composition, or writing that needs to be edited and refined, and so on. AI can't do 100% of the jobs, but it seems like we're somewhere past the 100x capabilities point. AI should be able to make a good employee able to do 100x the output at the same level of quality, and AI only gets more…
There is no way this is going to make it so that "engineers can focus on more interesting problems and engineering teams can strive for more ambitious goals." Instead it will mean that bosses can fire 75-90% of the (very expensive) engineers, with the ones who remain left to prompt the AI and clean up any mistakes/misunderstandings. I guess this is the future. We've coded ourselves out of a job. People are smiling an…
If AI gets good enough to wholesale replace developers, that is amazing news for the world. It's basically AGI. Productivity and GDP growth would skyrocket, tax receipts will explode, gov debts will be paid off, etc.
Because they won't be bought be the displaced workers.