At plinth, we've built a software/AI platform for charities to help them measure their impact and get more funding for the work they're doing. We work with both charities and funders (e.g. foundations, Government), providing a way to easily collect, visualise and report on client and impact data.
We're looking for an engineer with experience with React, NextJS etc, who wants to spend almost all their time heads down writing code, and not spending time in meetings.
I think it's a case of tech bubble vs the rest of the world. Most people are not subscribing to the paid version of ChatGPT, but a lot of people who spend a lot of time with these things are.
I'm not sure. The figures I've seen suggest that GPT3 required 10x more energy to train than GPT2 (e.g. https://www.nnlabs.org/power-requirements-of-large-language-....), so I think a roughly 1-2 order of magnitude increase in energy usage from GPT2 to GPT3.5 makes sense.
I can definitely imagine they're not covering the amortised cost of the training with the cost per individual inference request. It seems less likely to me that they're making a significant loss on each subsequent request, but again no source from me on that either.
Looking a bit more into this, I found this paper: https://arxiv.org/pdf/2311.16863.pdf. It references a table saying that text generation uses 0.047 kWh per 1000 inferences, which is 1-2 orders of magnitude lower than my estimate. Though that is for GPT2, so possibly tracks to something roughly in the ~0.001 kWh per inference for GPT3.5.
Do you have any better sources for the power usage stats? It would be good to get a bit closer on that front. Having said that, even if the cost share is closer to 80%, that still puts it on par with a laptop for an average person.
That's actually not correct. Stripe invoicing charges 0.4 or 0.5% on top of the normal payment transaction fee (for either card payments or bank transfers). Essentially, you are paying a % fee for a nice PDF (plus some reconciliation/reporting etc)
It was written at the end of 2019, do you think it's just wrong? Or has it changed that much in the past 2 years? Or is it a different set of startups?
A UBI that doesn't apply to foreign migrants isn't exactly universal.
Also, the second order impact of oil money appreciating the currency and therefore the reducing the international competitiveness of non-oil industries definitely has a big impact. In contrast, in a UBI situation, GDP still depends on the productivity of the country, not just the wealth generated from a niche (in terms of employment) extractive sector.
Yeah it was statically hosted in the end (initially it wasn't quite static). When it was at its most popular, the total site size including JavaScript was around 70kb as far as I can remember, so it didn't come anywhere near as high as 70TB.
Part of my worry was that I messed up the caching initially so it was making API calls on the server for each request. Once I fixed that, there wasn't really anything to worry about.