871–880 of 978 posts
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> given the enormous costs The costs are enormous only in America. The actual cost is much lower. American technogy in general is ridiculously overpriced -- compare the cost for raw compute on AWS versus Hetzner for example.
Apples to oranges. The AWS premium buys you a much broader platform with autoscaling, dozens of instance families, managed databases, serverless products, IAM, global regions, etc.
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iphone is 50x better? because you get a blue box around your text rather than green? androids and iphones are approximately the same thing the kinda obvious direction LLM training can go is into the direction of particle physics, and the training is set up democratically and through universities and via multi-state funding then the resulting weights end up open, the same as the particle detection data
> androids and iphones are approximately the same thing Yet... Android holds 70.6% of global active devices to iOS at 28.7%, but iOS captures 64.2% of consumer app spend. [1] > and the training is set up democratically and through universities and via multi-state funding Possible, certainly. But this case also applies to China and its "open-weights" strategy. They won't be able to form companies either or get ahead.…
Based on the above stat, it sure seems like Androids more versatile and inexpensive for a much larger group of users.
Hmm...that sounds familiar....
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I wonder what the thinking inside NVIDIA is at the moment. They have countless examples to learn from here, about the danger of not being willing to cannibalize your high end products. But, of course, there’s a reason that there are lots of examples of this sort of failure. There’s plenty of competition that would be happy to attack them from below, though…
Make money while there's money to be made then pivot to the next scheme? Gaming > Bitcoin > LLMs > Robotics Jensen's job is to just be one step ahead of the market dynamics to keep the investor dollars flowing.
“Jensen’s job is to just be one step ahead of the market” — how is that a “just”? That’s arguably one of the most difficult things to do reliably (judging by how much payout it can give you). Feels like saying he’s making “just” billions of dollars.
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> 15 months ago, the top model on the Artificial Analysis index was GPT-o3. It scores 30 on the Artificial Analysis index. There must be something really of with those benchmarks. Yes, hallucinations gotten better, but I don't see that the big frontier models got so much better in the last 12-18 Months. They just put out bigger wall of texts and feel smarter. But they still make way too many stupid errors
12 months ago "way too many stupid errors" was constant news. Today, you rarely hear about those anymore. Sure, the novelty of the errors has worn off a bit and thus the reporting. Nevertheless the quality has improved immensely in this regard. Also, AI video generation is now so good and accessible that it is very, very regularly used for memes, disinformation and proper (short) movie projects. AI image generation e…
Maybe people just got bored of reporting and reading about them.
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Why did Google give Android away for free?
But they could do that because it didn’t cost them hundreds of billions of dollars to create Android and they could retain 99% of control over end users.
The lesson of the last 50 years of the computer and software marketplace is that free and low-end eventually wins. - PCs destroyed minicomputers. Mainframes survive, but serving a much tinier portion of the market than they used to. - PC office productivity software destroyed expensive professional products. - Windows (low end) and Linux (free) completely destroyed the UNIX marketplace, and again, have taken huge mar…
The problem (right now) is that Open Weight models depend right now on huge companies to spend billion of dollars to train and develop them, all backed up by their incentives and their state to support this, while essentially giving away their monetization path. With open source projects, the benefit was that each individual could improve the complex system (e.g. Linux Kernel) interpedently, and over time the benefit…
Is it companies or is it governments?
If governments around the world see LLMs built from public knowledge as pre-competitive as the public knowledge itself, then why wouldn't they sustainbly fund it?
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At least China is being consistent: they do not give a single f*ck about intellectual property or copyright…but they also give away all this distilled knowledge away for free. I’m not an American so I don’t particularly like the idea of giving an American cartel of AI companies having so much power over this technology. I don’t necessarily buy into the “China bad”, “they are communists” and all that BS either. I will…
They're dumping, dude. They subsidize important industries so they can give it way so cheaply that free markets can't compete, and when those companies fail, they swoop in and make a profit. uber did the same thing with taxis! This isn't a free resource - it costs billions to build out the infra and maintain the inference to provide this, and you think they're doing it out of the goodness of their hearts lol. Come on…
> at least admit you're happier giving china your data than the us
Yeah of course I am. How many schools has China bombed using AI to pick a target?
I’m Canadian. Being anti-American is in my DNA.
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So, OpenAI and Anthropic say the Chinese models are only as good because they distill their models. How true is that. I am sure it adds something. But is it more like a marginal 1% improvement or something really significant?
if distilling was so easy and could give you frontier LLM on openai/anthropic output, then how come there are no hundreds of frontier labs in the US market, all distilling and competing for the TRILLION dollar market valuation ???? its all bs spread by oai/anthropic in order to ban open weight models and monopolize the market for two US companies and protect their trillion dollar valuations