GamingChairModel

joined 3 years ago
[–] GamingChairModel@lemmy.world 3 points 5 hours ago

It's like responding to your employee losing an arm, ripped off by your tiger, and saying "I'm never going to financially recover from this."

[–] GamingChairModel@lemmy.world 1 points 15 hours ago (1 children)

Basically they'd need about as much in radiator fin surface area as they would have in solar panel area. The ISS has 8 solar array wings, 35m x 12m, that can produce about 30 kW each, or 240 kW total, in sunlight (which is only half the time). The ISS has a complex cooling system, but relies on 4 radiators about 3.1 m x 13.6 m to reject up to 14 kW of heat each (56 kW total) for cooling the solar arrays themselves. The main cooling system uses 6 radiators, each 23.3 m x 3.4 m, to reject 70 kW of heat (from this report it sounds like each radiator may be capable of rejecting more than 1/6 of the heat but that the system as a whole needs to be kept under 70 kW of heat rejection).

So that seems like about 650 square meters of radiators can provide about 120 kW of heat rejection.

Today, a 72-GPU Blackwell server is 130 kW in a single server rack. The next generation rolling out now has 72 Rubin GPUs in a 230 kW server, in a single rack. And that's not even a "data center." That's just a single (albeit very powerful) server. How many can you string together, with networking equipment beaming data connections back down to the ground, before the ratio of solar panels and radiators to the actual ship size becomes unworkable?

That said, it's technically possible, especially if you can radiate the heat at higher temperatures than the ISS does, as the Stefan-Boltzmann law shows that the hotter the radiator, the more heat it can reject. Just completely infeasible from an engineering and economical standpoint, for any data center that hopes to be relevant in an age of 100+ MW data centers.

"I read your message but have nothing more to add"

ACK

If you're ok zooming out far enough you can serve a static image of the pale blue dot and a red arrow pointing to it.

Dental 3D printing is a different beast from consumer printers. The dental printers are already certified to actually create regulator approved devices that can go in a patient's mouth.

[–] GamingChairModel@lemmy.world 1 points 3 days ago (1 children)

The CBA with the union provides the protections. The bare minimum the state requires for everyone isn't all that relevant when you have a negotiated contract for much more than that bare minimum, whether it's for-cause termination protections, mandatory notice and severance pay for layoffs, etc.

No, the article is saying that it is why these robots were popular. Because unlike a human delivery person, there was no tip expected for the robots.

Exactly. Cloud connected devices should still be able to do all the offline and/or local things when its connection to the server is down.

My lights, door lock, air conditioning, and smoke detector all have some online functionality, but they all still work normally locally and offline when my Internet is down, including programmed functions by time of day, etc.

Trade secrets necessarily have to be analyzed under the protections of contract law.

Something can only be a trade secret if the purported owner of that proprietary information protects the confidentiality of that information, including through contractual restrictions. That's why I'm talking about contracts when asking whether trade secret protections apply.

I just pulled up the ChatGPT terms of use

Who's talking about ChatGPT or OpenAI?

I just pulled up the Anthropic commercial API terms, since that's the situation covered by the original article (big corporation using Anthropic's paid API):

Use Restrictions. Customer may not and must not attempt to (a) access the Services to build a competing product or service, including to train competing AI models except as expressly approved by Anthropic; (b) reverse engineer or duplicate the Services; or (c) support any third party’s attempt at any of the conduct restricted in this sentence.

Ok, so it's a contract that purports to prohibit pretty much this kind of model weight extraction, and I'm saying that Anthropic probably considers the model weights to be trade secrets.

Are you under the impression that trade secret protection only happens when the contract says the words "trade secret"?

Or, analogously, consider customer lists. Having a contract that says "don't copy my customer lists even if I sometimes disclose a single customer at a time when we partner together on projects" is probably enough to adequately maintain trade secret protection over those customer lists, even if individual customers are sometimes disclosed under a contract.

I'm just stating what I believe the law is, not what it should be, or even claiming that what the law is today is good. I'm just saying everyone should be aware that the law is quite protective of big corporations and their proprietary secrets. I still think this qualifies as a trade secret that they've protected with their own contracts.

[–] GamingChairModel@lemmy.world -1 points 6 days ago (2 children)

Ok, do these countries also make a contract not to distill LLMs void, as well?

[–] GamingChairModel@lemmy.world 0 points 6 days ago (4 children)

Can you name a country where signing up for a paid account to an online service, and using the service and paying the invoice that comes in, doesn't form a legally binding contract between the customer and the vendor?

 

I've read some of Ed Zitron's long posts on why the AI industry is a bubble that will never be profitable (and will bring down a lot of companies and investors), and one of the recurring themes is that the AI companies are trying to capture growing market share in an industry where their marginal profits are still negative, and that any increase in revenue necessarily increases their costs of providing their services.

But some of the comments in various HackerNews threads are dismissive, saying that each new generation of models makes the cost of inference lower, so that with sufficient customer volume, the companies running the models can make enough profit on inference to make up for the staggering up-front capital expenditures it took to build out the data centers, train their models, etc.

It's all pretty confusing to me. So for those of you who are familiar with the industry, I have several questions:

  1. Is the cost of running any given pretrained model going down, for specific models? Are there hardware and software improvements that make it cheaper to run those models, despite the model itself not changing?
  2. Is the cost of performing a particular task at a particular quality level going down, through releases of newer models of similar performance (i.e., a smaller model of the current generation performing similarly to a bigger model of the previous generation, such that the cost is now cheaper)?
  3. Is the cost of running the largest flagship frontier models going down for any given task? Or does running the cutting edge show-off tasks keep increasing in cost, but where the companies argue that the improvement in performance is worth the cost increase?

I suspect that the reason why the discussion around this is so muddled online is because the answers are different depending on which of the 3 questions is meant by "is running an AI model getting cheaper over time?" And the data isn't easy to synthesize because each model has different token prices and different number of tokens per query.

But I wanted to hear from people who are knowledgeable about these topics.

 

Curious what everyone else is doing with all the files that are generated by photography as a hobby/interest/profession. What's your working setup, how do you share with others, and how are you backing things up?

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