trained

Can you provide any examples of trained women vs trained men fighting in a martial arts competition?

The OP is implying that an employer should not only pay a salary, but pay for an employee to get trained.

>> Can you provide any examples of trained women vs trained men fighting in a martial arts competition?

It isn't due to some sense of greed or superiority, but from a trained desire of self preservation.

We have trained machines to understand sports at a level of sophistication that exceeds that of most collegiate players.

Programming is still lucrative enough for most people that they chose this over the job they were originally trained for.

At that size of contract, you had better be able to provide trained, high quality workers who can consistently deliver.

That's not just random chance, that's a set of users highly-trained in the art of dodging ads, with an extremely-low-but-not-yet-zero failure rate!

So most structural gains are hard to keep, which goes for any trained skill.

Also the Nork military while large, really wouldn't add anything to the capability of the South - it's poorly equipped, malnourished and badly trained.

She wouldn't stand a chance against any decently trained MMA artist.

Much akin to me listening to Indian classical music, Jazz: I would often encounter trained listeners breaking out into a (silent) applause.

Certainly any adult (whether male or female) that has trained for 10 years or so will be "strong enough".

The 6th point is very interesting: "Adversarial examples generalize across models trained to perform the same task, even if those models have different architectures and were trained on a different training set."

As someone who has trained in MMA extensively, "the greats" tend to be those who embody this for long whiles in their careers before eventually (and generally, inevitably) regressing to the mean.

> As someone who has trained in MMA extensively, "the greats" tend to be those who embody this for long whiles in their careers before eventually (and generally, inevitably) regressing to the mean.