logancbrown
logancbrown on Hacker News
Nobody has shamed users for having unused compute, only stating that it is not economically optimal when there are global restrictions on a resource.
Underutilization was indeed a problem before. The anecdotes you've presented are not broadly applicable.
The entire reason SETI@Home started was because people had unused hardware sitting idle at home.
Every company I've ever been in has had slides on resource utilization for procured hardware.
In fact not only could the two statements be true, in fact both are true. People want to ignore otherwise because doing so will make local LLM inference sound like the only option when only one is considered.
"Few people will argue with the logic of whether it is technically accurate"
Must why people in this HN thread are throwing out so many ad-hominems instead.
Two statements can be true and he stated one of them. Sam is not wrong.
1. Local inference can cause a large under-utilization of resources from users that do not run local inference hardware at capacity over the hardwares lifespan. This is under-utilization and under-utilization is not optimal from an economics perspective.
2. The concentration of inference hardware to singular providers can aggregate power to single systems or organizations, and their incentives may be at odds with individual users.
The same power dynamic and economics struggle has existed nearly everywhere for all of history. For example, if you want to decide to own or rent a piece of heavy construction machinery for business, you will find a long list of do-not's on the rental contractual terms, but you are more than welcome to buy your own and operate your own machinery at several times the price for the hours used and use it however you want.
> But is it anything more than a neat hobby at this point?
It effectively already is. It may end up in the same domain as Haiku OS, Plant 9, or Squeak, but they are all still interesting domains of research.
Reading stuff like this continue to make advances and new releases is like a fever dream when everything else is all AI.
This is by openrouter, which a single service that may not be representative of the entire token market
The difference is the same, whether you have 10k series representing the same variables or 10k series representing different variables decomposes into the same forecasting problem that you can either over-generalize across all time-series, producing worse accuracy at the tails, or train a model for each individual forecast, producing worse accuracy in general due to limited data input.
No reason to spend time classifying and worrying about cross-series validation when you use a TSFM.
All the businesses with product catalogs for example, every product can have several time series associated with it.
If a business has 10k employees, you have, at minimum, 10k time series to perform employee analyst operations over. There are several hundred companies in the US with 10k+ employees.
There are many more than 10k postal zipcodes in the US to perform forecasts over.
A lot of misconception around the utility of foundational time series models on HN.
Sure, you could train a XGboost model on a time series with holiday or event covariates, but what if you have 10k different series to forecast for?
You could train 10k different models, one for each series, but then they have very little history to learn from. Alternatively, you could train a single generic model to cover all 10k, but then you have to deal with scale mismatch between series in addition to the feature dev overhead between series. A TSFM saves a ton of work in modeling each of these series and could potentially generalize better to produce more accurate forecasts.
Yes, because I am the one who enacts agency over the CNC machine.
Tabasco is much more of a spice than a sauce, and I reckon thats one of the reasons its so popular. I can put Tabasco on many more foods of different types than I could with Cholula, Franks, Tapatio, Valentina, or Sriracha
The scenario is distinctly different: in one scenario the government had "control" over it and in the other a private corporation has "control".
This "holier than thou" attitude in this comment is precisely the reason why HN users have largely misunderstood tech trends and desires by the general public.
If it were made illegal then news journalism, documentary filmmaking, sports broadcasting (crowds), street photography, and police-body camera footage would become extinct almost overnight.
Your response is unrelated to the content of this thread (the open sourcing of hardware/software)
LARPing would imply pretending to do something, but not actually doing it. Here they appear to be actually doing it (open source product). Is there something Im missing?
Why are you so mad about orbital data centers? Your language is full of hate and vitriol. Let people build things that other people say are impossible or infeasible, find out if they work, turn out they dont work, then make improvements. If someone proposed the combustion engine to you in 1700 Im sure you would reply the same negative way.
This argument sounds reminiscent of "this is not AGI/ASI". Arguing over definitions is arbitrary. This is an operational data-center that is processing data on TPUs. That alone qualifies as an orbital data center.
Are you moving the goalpost? There are other people in this thread right now that are stating exactly that running orbital GPUs in space will not physically be possible (heat limits, etc).
Genuine question: why are there so many people up-in-arms on orbital data centers? Like they have a personally vested interest in ensuring their opinions on failure are correct? There are many people on HN that despise it and say it will not and will never work, but here we are, they are flying them up to space and presumably, will start working soon.
This is the same as AWS's new quickSuite platform?
Residential contractors are typically not the same as commercial contractors. Simply for the fact that commercial charges 2x what residential does is one of those reasons. Not saying there is zero overlap, but the pools are not totally shared.
Amazon doesn't provide financial breakdowns between Ads & E-commerce fulfillment and inventory costs, so take the Wall Street article with a grain of salt.
This analogy really only works assuming that maintaining [insert company]'s institutional expertise requires N engineers to maintain individual lines of code manually.
This is already showing not to be true with AI. Institutional knowledge is not the same as knowing how to implement low-level software details. Even today, every company does not need engineers to remember git cli syntax by memory, how to write parsers for JSON, or write the large amount of boilerplate from scratch that is at every software company. Most company's already hire engineers who have zero experience in the existing code base, yet they are productive despite this lack of institutional knowledge. For a company to maintain institutional knowledge they may only need N/K engineers.
You can't imagine a singular person and reason who would want an improved Siri?
Obvious false analogy in your earlier argument.
Steal someone elses work, whose work was also AI generated . . .