vanuatu

5 ms·

1.
by vanuatu 8d 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
2.
by vanuatu 8d 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
3.
by vanuatu 8d ago
Why are we using consumer prices when the vast majority of their revenue is from enterprise api usage?
4.
by vanuatu 9d 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
5.
by vanuatu 9d ago
unironically the second scenario sounds better
6.
by vanuatu 9d 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
7.
by vanuatu 13d 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
8.
by vanuatu 22d 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
9.
by vanuatu 22d 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
10.
by vanuatu 22d 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
11.
by vanuatu 22d 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
12.
by vanuatu 24d 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
13.
by vanuatu 26d 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
14.
by vanuatu 26d ago
You're right, computers are definitely the same speed as they were 20 years ago.
15.
by vanuatu 29d 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!
16.
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
17.
by vanuatu 1mo ago
you can just state things without reading the article nowadays!
18.
by vanuatu 1mo 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
19.
by vanuatu 1mo 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
20.
by vanuatu 1mo ago
but you can keep asking questions ad infinitum very nontrivial problem knowing when to stop and making assumptions
21.
by vanuatu 1mo ago
intelligence is not omniscience though
22.
by vanuatu 1mo ago
gotta make it less obvious
23.
by vanuatu 1mo ago
it was terrible for weavers it was great for workers around the world who now can afford clothes
24.
by vanuatu 2mo ago
I think a lot of people who grew up in developing countries or low income neighbourhoods adopt this perspective (I did both)
25.
by vanuatu 2mo ago
having goals above financial well being is a luxury belief
26.
by vanuatu 2mo ago
insert Obama awarding Obama meme
27.
by vanuatu 2mo ago
at human-level AGI there would be no need for people to 'buy' when the machines can just do
28.
by vanuatu 2mo ago
They are busy moving the goalposts, saying this isn't impressive or worth worrying about :)
29.
by vanuatu 2mo ago
that makes sense to me in a conceptual sense however inference is very profitable and plummeting in cost for a given point on the intelligence curve, and nvidia gpus can serve different models so they are protected post-buildout
30.
by vanuatu 2mo ago
can someone explain why this is actually bad? nvidia spends X amount to invest in data centres or investments on the agreement that the counterparty spends Y amount back, the net delta is the actual amount of value being transferred aka Nvi

More ›