why would Google, Microsoft and OpenAI oppose a torpedo against open models? Aren't they positioned to benefit the most?
There are a number of related threads linked, but I’ll personally highlight Jeremy Howard’s open letter as IMHO the best-argued case against SB 1047.
Who are these wide range of >$100mm open source models he's thinking of? And who are the impacted small businesses that would be scared to train them (at a cost of >$100mm) without paying for legal counsel?
[1] https://en.wikipedia.org/wiki/Defense_of_Marriage_Act
[2] https://en.wikipedia.org/wiki/Personal_Responsibility_and_Wo...
[3] https://en.wikipedia.org/wiki/Illegal_Immigration_Reform_and...
[4] https://en.wikipedia.org/wiki/Dietary_Supplement_Health_and_...
"Thanks to fair use, you have a legal right to use copyrighted material without permission or payment. But thanks to Section 1201, you do not have the right to break any digital locks that might prevent you from engaging in that fair use. And this, in turn, has had a host of unintended consequences, such as impeding the right to repair."
https://www.eff.org/deeplinks/2020/07/what-really-does-and-d...
that's the worst
I’d be careful with that cognitive bias, because obviously companies dumping poison into water sources are going to be opposed to laws that would prohibit them from dumping poison into water sources.
Always consider the broader narrative in addition to the specific narratives of the players involved. Personally, I’m on the side of the fence that’s grumpy Newsom vetoed it, because it stymies the larger discussion about regulations on AI in general (not just LLMs) in the classic trap of “any law that isn’t absolutely perfect and addresses all known and unknown problems is automatically bad” often used to kill desperately needed reforms or regulations, regardless of industry. Instead of being able to build on the momentum of passed legislation and improve on it elsewhere, we now have to deal with the giant cudgel from the industry and its supporters of “even CA vetoed it so why are you still fighting against it?”
Generally speaking, it’s in ours’ and the company’s best interests to keep as little data as possible for two big reasons: legal discovery and cost. Unless we’re explicitly required to retain historical records, it’s a legal and fiscal risk to keep excess data around.
That said, there are situations where your input is captured and stored regardless of whether it’s sent. As you said, whether it does or not is often a simple search away.
The flop targets in that bill would be like saying “640KB of memory is all we will ever need” and outlawing anything more.
Imagine what other countries would have done to us if we allowed a monopoly like that on memory in 1980.
One of those is $100MM in training costs.
The other is measured in FLOPs but is already larger than GPT-4, so the “think of the small guys!” argument doesn’t make much sense.
How do people on a computer technology forum ignore the 10,000x improvement in computers over 30 years due to advances in computer technology?
I could understand why politicians don’t get it.
I should think that computer systems companies would be up in arms over SB 1047 in the same way they would be if the government was thinking of putting a cap on hard drives bigger than 1 TB.
It puts a cap on flops. Isn’t the biggest company in the world in the business of selling flops?
Inversely to your sarcastic “understanding” about politicians’ stupidity, I can’t understand how tech people seem incapable or unwilling to actually read the legislation they have such strong opinions about.
We periodically raise flop limits in export control law. The intention is still to limit China and Iran.
Would any computer industry accept a government mandated limit on perf?
Should NVIDIA accept a limit on flops?
Should Pure accept a limit on TBs?
Should Samsung accept a limit on HBM bandwidth?
Should Arista accept a limit on link bandwidth?
I don’t think that there is enough awareness that scaling laws tie intelligence to these HW metrics. Enforcing a cap on intelligence is the same thing as a cap on these metrics.
https://en.m.wikipedia.org/wiki/Neural_scaling_law
Has this legislation really thought through the implications of capping technology metrics, especially in a state where most of the GDP is driven by these metrics?
Clearly I’m biased because I am working on advancing these metrics. I’m doing it because I believe in the power of computing technology to improve the world (smartphones, self driving, automating data entry, biotech, scientific discovery, space, security, defense, etc, etc) as it has done historically. I also believe in the spirit of inventors and entrepreneurs to contribute and be rewarded for these advancements.
I would like to understand the biases of the supporters of this bill beyond a power grab by early movers.
Export control flop limits are designed to limit the access of technology to US allies.
I think it would be informative if the group of people trying to limit access of AI technology to themselves was brought into the light.
Who are they? Why do they think the people of the US and of CA should grant that power to them?
Your delusions and lack of nuance shown in this very thread are exactly why people want to regulate this field.
If developers of nuclear technology were making similar arguments, I bet they’d have attracted even more aggressive regulatory attention. Justifiably, too, since people who speak this way can't possibly be trusted to de-risk their own behavior effectively.
There is a reason why we report time (speedup) in spec instead of $$
The price you pay depends on who you are and who is giving it to you.
With the other threshold, it creates a disincentive for models like llama-405B+, in effect enshrining an even wider gap between open and closed.
And even if it were, if said guy has such amount of compute, then it's time to use some of it to describe the model's safety profile.
If it makes sense for Meta to release models, it would have made sense even with the requirement. (After all the whole point of the proposed regulation is to get some better sense of those closed models.)
A much better objection to static FLOP thresholds is that as data quality and algorithms increase, you can do a lot more with fewer FLOPs / parameters.
But let’s be clear about these objections - they are saying that FLOP thresholds are going to miss some harms, not that they are too strict.
The rest is arguing about exactly where the FLOP thresholds should be. (And of course these limits can be revised as we learn more.)
Like if I’m a startup reliant on open-source models I realize I don’t need liability and extra safety precautions but I didn’t hear any guarantees that this wouldn't turn off Meta from releasing their models to me if my business was in California?
I never heard any clarifications from the Pro groups about that
There’s no new disincentive to open sourcing models produced by this bill, AFAICT.
Actually, wait, if Grok is losing to GPT, why would Musk care about Llama more than Altman? Llama hurts his competitor...
Should we crown one the king?
Or perhaps it is better to let them compete?
Perhaps advanced AI capability will motivate advanced AI safety capability?
When framed like that: why be opposed, it hurts your competition? The answer is something like: it shrinks the pie or reduces the growth rate, and that's bad (for them and others)
The economics of this bill aren't clear to me (how large of a fine would Google/Microsoft pay in expectation within the next ten years?), but they maybe also aren't clear to Google/Microsoft (and that alone could be a reason to oppose)
Many of the ai safety crowd were very supportive, and I would recommend reading Zvi's writing on it if you want their take
The thing that large companies care the most about in the legal realm is certainty. They're obviously going to be a big target of lawsuits regardless, so they want to know that legislation is clear as to the ways they can act - their biggest fear is that you get a good "emotional sob story" in front of a court with a sympathetic jury. It sounded like this legislation was so vague that it would attract a hoard of lawyers looking for a way they can argue these big companies didn't take "reasonable" care.