I empathize with most of what he writes, but an irritatingly common pattern I notice when people criticize SV is pointing at destitute people next to wealthy people - as if proximity is the same as causality. California has more than its share of destitution, but fifty years of NIMBYs and catastrophically bad housing policy are a better candidate for blame. If you make housing expensive you shouldn't be surprised when people go unhoused and when everything becomes expensive because labor (which has to be housed) is expensive.
It's not just housing supply, despite YIMBYs being the loudest voice in the room and housing supply is the most common presumptive scapegoat for all the poverty woes of SF.
There's another side. California is also much friendlier to the homeless and devotes way more resources to even trying to care for them. Meanwhile, the rest of America ships their homeless to a handful of destinations, with California's major population centers being top targets.
Having lived there, I don't think you need to blame the people living in the houses to be disheartened to see that kind of wealth disparity in such stark contrast, regardless of the reasons. It's sad to live in a place which has so much money flying around and so many wealthy people that can't find a way to help the most vulnerable or the working class.
To be fair it does seem pretty random when stuff gets taken up and when it doesn't. AFAICT sometimes content that ends up very popular is ignored the first few submissions.
For people who point out that this incentivizes companies to leave San Francisco, that's probably not a coincidence. Many SF politicians see tech as the enemy and would be happy to see companies go elsewhere.
Not really. Fine-tuning fundamentally changes the model weights to be more amendable to a particular use case/domain; the few-shot prompts for GPT-3 is just a guide (and it's very easy for the model to ignore said guides and go on a tangent).
If you could finetune the 175B model, you'd likely get even better results for these Q&A prompts. (unclear how the OpenAI API is implementing its finetuning demo but I believe it's not on the 175B model).
I briefly tested it with 'That doesn't make sense.' which worked, but switched back to yo because I'm looking at the probability of the first word and 'That' is too common to assume that the rest of the completion is 'doesn't make sense.'
I'd try with a few different responses according to the type of nonsense question: "That doesn't make any sense", "How could I know that?"/"No one knows that", "That's a matter of opinion", etc.
Author here. I'm afraid this did actually happen to me personally.
A few people have mentioned a slashdot story, I've never seen it but would love to if anyone who read it could link to it. It shouldn't be too hard to believe that there could be more than one elaborate case of resume fraud.
Author here. Your guess is as good as mine, but probably for the reasons other people have mentioned here. It would be making the lie in public, attached to his own name. The fake profiles aren't attached to anyone real.
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