☆ Yσɠƚԋσʂ ☆

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Joined 6 years ago
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Cake day: January 18th, 2020

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  • There’s a bigger problem here which is that models themselves are general commodities and there’s just not enough difference between them for any one player to differentiate themselves. A company can get ahead of others by a few months, but then the rest quickly close the gap. It’s a really low margin business because you constantly have to burn a ton of money just to stay a bit ahead, and you have diminishing returns the longer you do it.

    The only rational approach is to treat models as shared infrastructure akin to Linux because the money is going to be in customization niches. Companies will charge to tune models for specific use cases and charge support for that. There’s also going to be money at the bottom for hardware vendors making chips and memory. But the middle tier of generic LLMs is just relentless involution driving profits towards the bottom.











  • The whole trope that LLMs need absurd levels of energy use has not been true for a while now. People latched on to this idea because early models were hideously inefficient, as is the case with pretty much any new technology. Today, you can run local coding models on your laptop that surpass the capabilities of frontier models needing whole data centres to run just a year ago. You no longer need an inordinate amount of computing power to run any of this stuff, and performance gains haven’t stopped. There’s no indication that we’re close to any sort of a limit here.

    Also, nowhere did I say that a socialist world would have developed it in the same fashion. I’m merely pointing out that it would have been developed, and there would have been many existing use cases which I listed which have little to do with commercial incentives. I get the impression that you’re conflating hype with the actual legitimate use of which there are plenty already.

    Finally, there is really nothing stopping people from developing this technology in open source fashion. And that’s the way to decouple this tech from commercial incentives going forward. There are already open models to build on, and that should be leveraged to develop completely open alternatives which are community driven.












  • You’re entitled to your opinion, but finding vulnerabilities goes far beyond simply doing static analysis. LLMs are able to find vulnerabilities that emerge from subtle interactions between different features, where things like keys and security credentials aren’t handled properly, and finding these by hand in a large codebase is nearly impossible.

    The very process of finding these vulnerabilities gives you a path towards making an exploit. And the LLM can actually do this laborious process largely autonomously as well. It can probe a site for example, look at the results, and iterate on them. It’s an incredibly effective tool for both finding exploits and testing them out in the wild.

    In fact, you can ask piefed devs about their recent security debacle that an LLM exposed and gave a step by step guide for exploiting.