151–155 of 155 posts
Earlier quoted context omitted.
A quick google seems to suggest the median software pay in Austria is about €60k. That translates to an hourly wage of roughly 31€/h . Your range of 80-120 gives a yearly wage of like 155k-234k which is clearly far too high for an average.
The discrepancy is probably consulting vs salaried.
Earlier quoted context omitted.
I mean, you probably can just turn off defective parts of the network. You better believe if this becomes popular they would salvage yields by selling "dumber" chips at a discount.
except that if you do, you've just implemented a different model, with no way to tell which part of it is wrong
Earlier quoted context omitted.
Cloud can pay more for RAM until all the RAM producers withdraw from the consumer market, then prices will go back down. End users will still get access to RAM. The cloud terminal they purchase from Apple, Google, Samsung, or HP will have all the RAM it will ever need directly soldered onto it.
Ram upgrades are happening because of ddr5. Nvme upgrades are happening because of pcie5. Prices will come down once everyone is done upgrading.
While I understand why they used the METR data, a cleaner look would be against the current cost-optimal frontier of open models (e.g. GLM-5.1 and MiniMax-M2.7). That paints a very different picture. Comparing just the frontier models at the time of the METR report invariably leads to looking at providers who are pushing the limits of cost at the time of the report. GPT-5 was shown as being on the costly end, surpass…
Calculating hourly costs for these models makes me think that the decision of when to hire an SWE vs. increase use of AI may follow a similar pattern to the decision to use cloud compute vs. on-premises. I don’t cost $120/hr (incl. fringe), but my employer pays my salary all year long, no matter if I am working or on vacation. Whereas if they use an AI model to do the same work, they may be happy to pay $120/hr or mo…
While I understand why they used the METR data, a cleaner look would be against the current cost-optimal frontier of open models (e.g. GLM-5.1 and MiniMax-M2.7). That paints a very different picture. Comparing just the frontier models at the time of the METR report invariably leads to looking at providers who are pushing the limits of cost at the time of the report. GPT-5 was shown as being on the costly end, surpass…
Calculating hourly costs for these models makes me think that the decision of when to hire an SWE vs. increase use of AI may follow a similar pattern to the decision to use cloud compute vs. on-premises. I don’t cost $120/hr (incl. fringe), but my employer pays my salary all year long, no matter if I am working or on vacation. Whereas if they use an AI model to do the same work, they may be happy to pay $120/hr or mo…