61–70 of 282 posts
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Most management consultants are useless. But there are some realities you must accept. Number 1. In a team of 20-30 engineers there is only one extremely god "why is he with us" engineers who is great at technical stuff and being a people person. However, no matter how nice he is his approach to his job, it is a job and I will only drop hints how the management should be done. He doesn't care about where the company…
Needs an /s.
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Most management consultants are useless. But there are some realities you must accept. Number 1. In a team of 20-30 engineers there is only one extremely god "why is he with us" engineers who is great at technical stuff and being a people person. However, no matter how nice he is his approach to his job, it is a job and I will only drop hints how the management should be done. He doesn't care about where the company…
Man, write drunk, but edit sober.
Pipe /dev/random, transform to decimal, and you just got an amazing increase in performance for calculating decimals of Pi. Nobody said precision was important anyway.
Honestly if you don't care about precision, /dev/zero is going to give you more throughput. Plus, I personally guarantee it's correct to within an error margin of 4.0. You can't offer the same with /dev/random!
It switched from always guessing composite to always guessing prime. Much less accurate.
Not surprised. It's frighteningly good, and a perfect match for programming. I often ask GPT4 to write code for something, and try if it works, but I seldom copy and paste the code it writes - I rewrite it myself to fit into the context of the codebase. But it saves me a lot of time when I am unsure about how to do something. Other times I don't like the suggestion at all, but that's useful as well, as it often clari…
It's simlar to what happens to people who knows a language (not coding language), stop using it or go back to use translator, and when they need to use it themselves, they are unable.
Having been a consultant, what strikes me about this is the next, to me seemingly obvious question: What if you just removed the consultants entirely and just had GPT-4 do the work directly for the client? If you’re a client and need a consultant to do something, you have to explain the requirement to them, review the work, give feedback, and so forth. There will likely be a few meetings in there. But if GPT-4 can ma…
Companies like BCG and McKinsey are mostly about liability, as a CEO you call them, pay them the big bucks, have them make up plans and strategies, if it works out you get the credit, if it doesn't then well "we worked tightly with experts from McKinsey, etc. so the blame isn't on me"
HN is so bad at predictions. Just a few months ago HN was awash with comments that confidently claimed LLMs were no more than stochastic parrots and unlikely to amount to anything. > I can't help but think the next AI winter is around the corner. [0] Yeah, right. [0] https://news.ycombinator.com/item?id=23886325
If you make a hilariously bad prediction then that tells you your model about that thing is off and needs correcting.
So if you do nothing to that model and still make predictions...
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This is one step removed from "try different things until it works" style of programming. Not to say you're of of those programmers, but it certainly enables those sorts of programmers.
And what's the harm in that? That's how I first started out programming decades ago.
My questions to naysayers:
* Do you or anyone you know use GPT-4 (not the free GPT-3.5) to do productive tasks like coding and found it to help in many cases?
* If you insist it’s useless, why do millions of people pay $20 a month to access GPT-4 and plugins?
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The article certainly didn't invent the term 'Centaur', but I haven't seen cyborg used in that way. It does seem a bit clickbaity.
I like Cory Doctorow’s use in “Chickenized Reverse Centaur”.
https://m.youtube.com/watch?v=6pieIoEi8Ds
I love it when a complicated set of conditions can be losslessly encoded in a short, easily remembered label.
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I’ve also found the act of describing my problem to GPT4 is sometimes just a helpful as the answer itself. It’s almost like enhanced rubber duck debugging.
We need an inverse GPT4-style LLM that doesn't provide answers but instead asks relevant questions.