I read a decent number of papers. If you’re looking for something specific, and abstract isn’t enough. If you want to research something specific that’s not the core focus of the paper, you at least need to skim it.
If Hank Greene is understaffed, using AI to prefilter papers isn’t a terrible use of the technology.
He didn’t state what his actual process was. People assume that just means firing out a query and no bothering to check it, he said he uses it to summarize sources to see if they are worth reading. I don’t think that’s unreasonable if he still reads them.
Regarding using it to write scripts, I think if you use LLMs to generate something you are good at making and are picky and opinionated about, the review process very quickly makes you skeptical about the output.
Before the response, IP rights and environmental effects of LLMs are completely valid and are a valid reason for opposing them. Don’t just assume someone’s using it out of laziness instead of in an attempt to scale up their own work.
I think you can start with niches or regional groups, they then start inviting others in.
WhatsApp and Discord basically had to bootstrap themselves and did it through niches and meeting a clear market need but we’re then bought up by Facebook. There were plenty of group chat competitors and voice chat competitors.
A good product and marketing strategy can bootstrap an audience. You likely need to provide something beyond just a phone book. Even outside of Facebook there’s a million of those but getting an audience for a new product is far from impossible, tons of new games do it all the time.
Sounds like they just moved the research over to isomorphic labs, also even from the onset people quickly took the original approach and paper and made their own versions tuned for their needs.
Feels more like a research project having achieved its goals, the key players moved on, and they’re closing the Deepmind part of it as it’s not really useful anymore.
2 out of the 3 of motherboard, CPU, GPU
Ok