That doesn't make any sense, this is a Jev competitor and a model release, like their Carbon and Argon models. It won't simply be 'killed' like apps might without something to succeed it.
And why not, exactly? OpenAI was more than fine killing Sora with no replacement. I don't see why Google would be any different, especially considering they're notorious for this behavior.
Gemini Decisions API is likely to be used by enterprise customers in real products. Sora was a toy that only seemed to exist to infringe on IP OpenAI didn’t control. Apples and oranges.
> Paid models have an incentive not to do that because if the market discovers it there is a huge economy penalty, but the free open source models don't have that disincentive.
This just fundamentally isn't true. They run on the same economic model, but they have to release the weights to gain credibility, unlike the American labs.
> Do you ever worry whether these open source models have been trained to embed backdoors or leak secrets in very specific circumstances at some point in the future?
Open weight models are extensively analyzed. It is extremely unlikely there is an intentional 'backdoor when X' concept added to any of them. Not impossible, but unlikely for the same economic incentives you see in the other labs, and given that no evidence of anything along those lines has surfaced yet.
We've seen many open source software libraries, frameworks, and hosting platforms with vulnerabilities, backdoors, or leaks.
In my opinion, to suggest open-weight models are extensively analyzed while being net new and continuously released and the model itself being unintelligible to humans seems a bit premature.
It's possible that closed-weight models end up following the pattern of being arguably less secure since there are fewer eyes on them analogous to open source software but I don't think there's a perfect match here.
How about "Using third party analytics scripts is a bad idea in general, because they can and frequently do have vulnerabilities and your trust in $BigCompany is misplaced"?
Exactly. This is what website operators need to learn. People generally don't learn lessons like this without experiencing some pain first, so in my mind skipping straight to the blocklist is the most efficient.
You need to look up what a supply chain attack actually is.
This is not necessarily malicious behavior nor incompetence, unless you consider putting ads on a website incompetence. This problem has been festering for well over a decade.
Nvidia, I get you're all-in on AI, but please at least find a human to write some copy. It's both overly verbose and entirely lacking of important info at the same time.
Why clearly? You mean the tensor pre seed with deterministic pseudo random numbers? I don't have much experience in LLM training, but I do remember from minimization algorithms (like gradient descent) that it's better to start with (pseudo) random starting values and minimize from there. And seeing how I would like my results repeatable, seeding a pseudo random sequence seems logical.
I don't understand why these tensors specifically weren't changed during minimization (training) though. Maybe they were not activated, or a w part of an image decoder or something?
consider most naive possible way one would try to deceive users without exorbitant budget -> attempts a few things you naively would do -> recovers it by chance?
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