4 ms·
A bit thin on detail, but will this require confidential VMs with encrypted GPUs? (And I wonder how long before someone cracks SEV-SNP and TDX and pirate copie
by rwmj 2y ago
A bit thin on detail, but will this require confidential VMs with encrypted GPUs? (And I wonder how long before someone cracks SEV-SNP and TDX and pirate copies escape into the wild.)
- unsnap_biceps 2y agoThe number of folks that have the hardware at home to run it is going to be very low and the risk of companies for leaking it is gonna make it unlikely IMHO.
- notpushkin 2y agoI think home users would be the least of their concerns.
- RadiozRadioz 2y agoIt only takes one company to leak it
- franga2000 2y agoOr one company to get hacked and the hackers leak it
- spacebanana7 2y agoRealistically the only people able to run models of this size are large enterprises. Those enterprises won’t take the risk of being sued for using a model without proper permission.
- nxobject 2y agoI don't know – if there's still dumb money being thrown towards AI in non-tech and non-privacy-heavy industries, especially ones traditionally targeted by ransomware, there'll always be a chance of datasets getting leaked. I'm thinking retail and consumer product-oriented companies. (There's always non-Western governments without strong security orgs, too.)
- blackoil 2y agoNations.
- FilosofumRex 2y agoor large government sponsored entities like Mossad. Air gapping won't protect against spying. Good luck trying to sue them
- BiteCode_dev 2y agoThey can get "hacked" and wooops.
- deleted 2y ago[deleted]
- vasco 2y agoAt the pace models improve, the advantage of going the dark route shouldn't really hold for long, unless I'm missing something.
- miohtama 2y agoAccess to proprietary training data: Search, YouTube, Google Books might give some moat.
- maxloh 2y agoWe have Common Crawl, which is also scraped web data for training LLMs, provided for free by a non-profit.
- UltraSane 2y agoThe Common Crawl is going to become increasingly contaminated with LLM output and training data that is more likely to have less LLM output will become more valuable.
- kouteiheika 2y agoI see this misconception all the time. Filtering out LLM slop is not much different than filtering out human slop. If anything, LLM generated output is of higher quality that a lot of human written text you'd randomly find on the internet. It's no coincidence that state-of-art LLMs increasingly use more and more synthetic data generated by LLMs themselves. So, no, just because training data was produced by a human doesn't make it inherently more valuable; the only thing that matters is the quality of the data, and the Internet is full of garbage which you need to filter out one way or another.
- SXX 2y agoProblem with filtering is that LLMs can generate few orders of magnitude more slop than humans.
- bjackman 2y ago> I wonder how long before someone cracks SEV-SNP https://bughunters.google.com/blog/5424842357473280/zen-and-the-art-of-microcode-hacking https://bughunters.google.com/blog/5424842357473280/zen-and-...
- NoahZuniga 2y agoI'd expect watermarked model weights plus a lot of liability to distinctivise leaking the model.