vanuatu

5 ms·

1.
by vanuatu 5d ago
No, it's not. We don't really have a good definition of intelligence. If we can imagine non-carbon based life forms, I don't think its a leap to imagine non-human brain based intelligence (octopi?) > If you think LLMs are
2.
by vanuatu 5d ago
Famously, Microsoft stop progressing after 2000. Facebook disappeared after 2008. BTC stopped appreciating since 2013. All the investors in these trends regretted it.
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by vanuatu 5d ago
I don't think intelligence needs to take the shape of human-like intelligence, nor human-like data efficiency. I'd argue they are intelligent entities, superhuman in some ways due to being run on silicon but extremely data ineffic
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by vanuatu 5d ago
But deciding the next token is not a merely mechanical process. Even if the string of tokens from our swapped out humans ends up being syntactically incorrect, it's due to the combination of intelligently selected tokens. (Presumably i
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by vanuatu 9d ago
my take is that the human operator behind it was implied. give it a year and open source Fable / Astra models are running wild, what happens when a malicious group or nation state decides to let loose?
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by vanuatu 10d ago
I've seen it be very effective (moreso than human agents at resolving issues) but its extremely implementation sensitive, so you're more likely to encounter a bad one in the wild than a good one. There are voice agents picking up
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by vanuatu 10d ago
I think its the opposite, the grunt work is done by AI, the remaining skills are difficult to acquire and software engineers command a higher premium (but there may be less software engineers in aggregate)
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by vanuatu 12d ago
I interview a lot of larping 'AI engineers' that either vibe coded a side project or were involved in low stakes pilots Irl theres a short list of companies that actually build / apply ai at scale. for people trying to break
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by vanuatu 12d ago
ai slop article, but if you want to maximize earnings in any tech boom the best opportunities lie at the companies driving that boom.
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by vanuatu 12d ago
I did by applying most eng roles at frontier companies don't require prior experience specifically with AI, there's a ton of regular engineering work required to train / serve models
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by vanuatu 18d ago
https://www.seangoedecke.com/ai-inference-is-obviously-profi... https://www.mindstudio.ai/blog/anthropic-inference-margins-7... its even higher depending on the model, how optimized it is, and the chip
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by vanuatu 18d ago
serving models is very profitable (70%+) but the issue is you need to invest in training the next iteration. but so far all of anthropics models have been profitable fully loaded the vast majority of the labs revenue is from enterprise api
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by vanuatu 18d ago
Why are we using consumer prices when the vast majority of their revenue is from enterprise api usage?
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by vanuatu 19d ago
if you're going by anecdata, myself and a few of my colleagues (senior ics) switched jobs relatively easily for a solid pay increase within the last year. definitely easier than post-covid engineering (hardware, software) and data cent
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by vanuatu 19d ago
unironically the second scenario sounds better
16.
by vanuatu 19d ago
I think this is Jevon's paradox playing out in full force, and I'm quite confident we'll continue to see the growth in well paid STEM jobs despite the anecdata in this thread (anecdotally my group of ICs on tech have all seen
17.
by vanuatu 23d ago
large parts of ai research likely to be automated first most swes don't work in jobs where they only work on bounded measurable tasks. there will probably be more "engineers" than ever
18.
by vanuatu 1mo ago
i mean the meta point is having "AI skills" is understanding the jagged frontier and operating accordingly Given that we can keep making infinite abstractions with software if we actually saturate software demand with AI then I do
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by vanuatu 1mo ago
To be clear, I think young people need to learn traditional software engineering skills too (.. maybe having the wrong attitude towards it is even worse than the aptitude!) A junior with no foundational SWE skills will just become a meat wr
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by vanuatu 1mo ago
You'd be surprised, I used to do a first round technical screen where we let the interviewee use any ai tool they want to build a simple api (and they can oneshot the problem if they just pasted it into any capable agent). I quite like
21.
by vanuatu 1mo ago
- knowing what to prompt - directing the model and knowing when its going off the rails - verification - setting up the right loops, harness, graphs around the models economics still apply to hiring people. if all your competitors are using
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by vanuatu 1mo ago
we should exercise critical thinking then heaps of people on this site expect them to be omnipotent then claim it’s fake when it doesn’t read minds
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by vanuatu 1mo ago
I think what a lot of people miss about jevon's paradox is the elasticity of demand of the underlying resource textiles had jevons paradox, and many more textile workers were employed even when textile machines were being created, unti
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by vanuatu 1mo ago
You're right, computers are definitely the same speed as they were 20 years ago.
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by vanuatu 1mo ago
Should be easy to build a competitor in a week, pitch to some VCs then have them kingmake you to a $1B exit to another portco then!
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by vanuatu 1mo ago
You can go ahead and build it then, then sell it for only $100M to a competitor. Should be easy peasy
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by vanuatu 1mo ago
you can just state things without reading the article nowadays!
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by vanuatu 2mo ago
wonder how much of the ai CX hate is availability bias where people really notice it when it breaks but you never see the whole picture on total impact it seems very implementation dependant, I know a startup with incredibly realistic voice
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by vanuatu 2mo ago
I used to think this was true until my company adopted a similar process, and the amount of very senior candidates who used it very ineffectively was highly surprising (eg staff candidate only using the default Google search AI), whereas th
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by vanuatu 2mo ago
but you can keep asking questions ad infinitum very nontrivial problem knowing when to stop and making assumptions

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