I think if you offered the two options to users with even partial differences in price, most users would go for the cheaper option even if they had to do cartwheels to process payments.
TfL settles every 24 hours, so you'll only have a single purchase per 24H regardless of how many journeys you've taken.
I'd also argue that in this case the fault is on the cardholder for being with a shit bank when better options exist in the vast majority of countries.
Given the option, I think most customers would absolutely rather use the company's system, if the company offered lower prices for buying through them. Of course, that assumes both systems would be on offer - but if there's market pressure for companies to offer Apple as an option, that may be enough.
It would probably be upvoted if it was astroturfing. Hacker News doesn't have a huge commentariat, I think it's just a few people with an axe to grind.
That's sort of an arbitrary distinction. Both are abnormal presentations that cause significant problems in day-to-day life and consequently have clinics set up to treat the issue. Whether the issue is voluntary for a particular patient is also similarly important in assessing an appropriate treatment modality.
Putting the obvious political agenda aside, I would argue teenage girls faking tourettes is pretty much the same phenomenon as teenage girls faking gender dysphoria. It's not helpful to pretend that faking tragic mental conditions isn't a phenomenon among teenagers.
"Both are abnormal presentations that cause significant problems in day-to-day life"
The same was one-hundred percent true about homosexuality for nearly all of human history in most societies. If the "day-to-day problems" are because other people are mindlessly hateful and intolerant, who exactly has the mental health issue? In terms of homosexuality, we now largely agree it is the bigots, not the queers, who have the problem.
Many groups are social pariahs, none have a suicide rate close to the transgender community. Dysphoria by itself is clearly horrible to deal with, that's why people are willing to have double mastectomies in the pursuit of easing their mental pain. A vaginoplasty is incredibly invasive and isn't going to have a meaningful impact on day-to-day social judgement. I really don't buy the claim that it's purely or even primarily about acceptance.
I would also point out that the the trans community themselves are advocating for greater access to treatment, not less. It's really not the same as the gay rights movement. Unlike gay people, treatment is literally one of their objectives.
Is that overfitting? I thought overfitting was explicitly when your model fits itself so well to the training data that its ability to generalise to your target environment begins to decline. The size of the training set and the performance on it don't really matter, all that matters is that performance in the specific environment you intend to deploy the model in starts dropping. In your case, you're training the models for a very narrow deployment target, and they remain competent.
Couldn't you use this logic to say that AlphaGo is overfit because it can only play Go, not chess?
Is this true? I would have thought all you would need is to give it an input that maps to a 3d surface that's adversarial. There's an extra step in the pre-prep pipeline, but the basic technique is the same - gradient descent on inputs until you derive those that are sufficiently adversarial.
All neural nets are vulnerable to adversarial examples. It's a fundamental property they hold, because they're essentially stacked linear models. So (for example) they get more confident about their predictions when given a sufficiently out-of-domain input - adversarial training is essentially just finding paths that trigger an out-of-domain response.
I don't see how an additional transformation before input precludes that.
I mean you train your network to produce images that translate into adversarial 3d surfaces.
You don't need to produce the correct 3d surface if the surface recogniser is neural - you just need to produce a 3d surface that's adversarial. The adversarial surface could be completely unrealistic, like these adversarial images. (Although the adversarial generator could also be trained with "realism" as a constraint.)
Are they able to detect depth independent of the surface of a presented image? That would make it harder, but the point of failure then is just figuring out a way to dynamically fool them. I wouldn't be confident saying that's impossible.
Yes, FaceID uses actual depth/distance data by projecting IR dots during scanning. So you would either need to very precisely mock these somehow, or create an actual 3D surface.
Yes, Face ID uses infrared depth sensors so it shouldn’t be possible to use just a printed image. You might be able to fool it with by printing with some strange material that fools them, but I don’t see the point with coming up with such an advanced technique. Then you might as well just print a 3D model.
This is completely untrue. Contrary to popular belief, sitting at a desk is extremely healthy in comparison to manual labour, which destroys your body over time.
Standing all day is also worse for your back than sitting all day. Even being a shop assistant is harder on your body, and particularly your back, than sitting at a desk. (Alternating, i.e. an office job with a sit/stand desk, is best.)
The primary issue is complete lack of inactivity (a large component just being weight gain), which you can combat by exercising outside of the office.
People already have the option to not lay bricks. They don't choose it, because they need money.
I get that everyone is going to say, "well then, UBI" but bear in mind in an automated society, power is disproportionately in the hands of the people who own the machines, and they're unlikely to part with their wealth voluntarily.
