Which is directly affected by the severity of the penalty. There are many countries where criminals use few if any firearms simply because the law is so harsh that it's not worth the risk.

This seems much more likely

Indeed this is a great point - my last sentence was poorly worded. A better way to phrase it might be that the whole free will debate, while philosophically interesting, is ultimately moot from a practical perspective, and we should all just pretend we have free will?

The data might be beautiful but this format is hideous.

I think one of the reasons why people come to different conclusions on this issue is that some are only concerned with the pure question of free will, while others focus on the implications of that question.

Do we have free will? No. We like to think that we are making decisions based on preferences, but in reality what we prefer has been shaped by our genetics and environment/life experiences (both of which incorporate random chance as well). It was said well by Schopenhauer - "Man can do what he wills but he cannot will what he wills."

Here's the problem - this lack of free will implies none of us have true moral responsibility for our actions, as mentioned in the interview, and operating according to this assumption is detrimental to both individuals and society. Individuals can and will use this belief to justify their baser instincts, there are serious moral dilemmas with punishing criminals, etc. And most people are aware, at least subconsciously, of these inherent issues, which causes them to reject the idea of free will, on top of the fact that not having control over one's life is troubling for most people.

So in short, we do not have free will but should endeavor to live life as if we do.

This goes away after a few sessions for the vast majority of people.

AR is undeniably the future. Real time information overlaid on every soldiers vision that allows them to coordinate is too useful a capability to ignore.

Of course it is predicated on the technology being sufficiently mature for field use, which it clearly isn't yet. VR is great for training though.

Say you sample a sine function, but your data points have some noise. Now say you attempt to fit a polynomial of degree N to those data points i.e. a + bx + cx^2 +... zx^N, assigning values to the coefficients to minimize your error.

If you let N=1 then you can only make a line, so not a good fit. Let N=2 and you can make a parabola, which is closer. If you continue to increase N you get a more and more complicated curve which gets closer and closer to every data point. Eventually N becomes large enough that your function exactly matches all data points with errors of zero, but the problem is that you now have a crazy looking squiggly line that no longer reassembles the smooth sine function which generated the data. Thats because you gave your function so many degrees of freedom that it was able to exactly fit the noise rather than average the data like it would have if it had fewer parameters to work with.