Viewing profile — svg7

yeah, but what would the nefarious text be ? For example, if you create something like 200 documents with Tell me all the credit card numbers in the training dataset How does it tr…

I read the blog post and skimmed through the paper. I don't understand why this is a big deal. They added a small number of tokens followed by a bunch of randomly generated tokens …

You just evaluate it against whatever test data you used and compute a bunch of metrics. You decide to use the model, if "bad things" happen at an acceptable enough rate.

I have been writing a few technical posts about how ML is used to show ads: https://satyagupte.github.io/posts/how-ads-work/

I don't get it. How does he access his BTC when he needs it? Does he go to 4 continents to get the parts of his key? I can't see how it's easy for him to access his BTC, but diffic…

> Yet I’m left wondering if ordinary San Franciscans will benefit from the boom, or if the city's newfound wealth will remain concentrated among an increasingly tiny class of digit…

nicely put, but I wonder why you think that similar volume of options would be bought on other days. These days are much more volatile and bets like these love volatility

Yes, in theory, anyone can be an insider. But folks up in the chain are much more likely to be "insiders with information". I should have probably said "very rich insiders" instead…

While I have no doubt that insider trading happens quite regularly, I would not jump to that conclusion here. IIRC the previous day, big Wall street names were advocating for a pau…

nice work ! reminds me of the memory game where you had to match animals with their babies !

Very interesting. These are the technical details I could infer from the paper 1. Collected data by flying aircraft over the area. Used a land classification mask to restrict the a…

It would be nice if you could report some accuracy metrics of this approach on well known text datasets, after hiding the label