nvrmnd

I think you could easily argue that social media links to the news websites provides more value to the news website than vice-versa. If, for example, only the headline and sub-headline were quoted in the posts without the link -- which the Heritage Minister indicated would not constitute a fee -- any discussion could still take place, and certainly there would be even less benefit to the news organization.

Any news website can already prevent Facebook from generating link previews through meta tags, as I understand. But very few, if any, websites do this indicating that they understand it's not in their interests.

Perhaps people are not reading the articles because the _discussion_ is more valuable to them than the content of the article? Don't we all occasionally jump to the comment section on HN/reddit instead of reading the article? Seems to me that many news organizations have not yet figured out how to provide their customers with a product they are willing to "pay" for.

I mean, any brief visit to a small news website without an ad-blocker or, worse, a scroll through the comment section, should make this fairly evident.

> should I be more worried that there's something invisibly going wrong there?

I think what anyone should be cautious about is thinking that these more sophisticated methods can allow MCMC methods to significantly scale up to larger problems. But they are probably 2-10x at best, if it's well suited to your distribution (however you characterize that). Often it's not enough to keep up with the dimensionality of the models people want to use. I remember struggling to get this to work on a Bayesian neural network that was maybe 100 parameters, tiny by todays' standards.

As for approximating hyper-parameters, again if it's an easy problem, sure, probably something will work. But I do have to say I find this really fascinating when you start to get into these harder problems with MCMC algorithms. The first thing that comes up is how do you know that a sampler is drawing samples from the correct distribution? how exactly do you quantify that? Usually each sampler takes the same amount of time to produce a sample, so what you're really comparing is which one is giving "better" samples. But.. they are all supposed to be drawing from the same distribution, so how can one sample be better than another. If they are not drawing from the same distribution, then how can you possibly know which one is the right one!

So I'm simplifying the problem here, and not to disparage any of the fine work on autocorrelation and mixing rates and all that, but you have to admire just how impossible this is generally.

Yes by all means, though I do hope anyone who is using this default algorithm is familiar with the other pitfalls I mention.

I did a PhD on Monte Carlo methods, and I remember really enjoying how elegant the HMC is. But seeing this here I feel I should comment, in the event that anyone happens to read this and thinks it would be a useful algorithm to implement. Words to heed:

"Monte Carlo is an extremely bad method; it should only be used when all alternative methods are worse." -- Alan Sokal

The reality of the situation is that you would only bother understanding and implementing such a complex algorithm if you had a rather difficult distribution to sample. Unfortunately, that means that you are very unlikely to know whether the answers you are getting are at all correct. You may have a bug in your code (highly likely), or the method's hyper parameters may be poorly tuned (likelier still), or the MCMC chain is not mixing rapidly leading to undetectable approximation error (almost certainly).

Almost always I would recommend attempting to simplify whatever model you are approximating and to use a method where approximation quality can be assured, rather than attempting to approximate complex (high dimensional) distributions with a more efficient algorithm like HMC.

Of course, sometimes you must approximate such models, and for this you should be glad the method exists, and good luck to you.

I had assumed this pilot was mostly discussing observations made during non-combat missions. Training and other enforcement activities in times of peace probably make up the majority of a military pilots career flying hours.

I got a let out of Karpathy's video lectures on youtube, for example: https://www.youtube.com/watch?v=kCc8FmEb1nY

He mentions a few of the bigger papers in multilayer perceptrons (aka deep networks) such as attention is all you need, I think a good place to dive in before coming back to visit some fundamentals.

Is this a question of jurisdiction? I mean the people living together in a slightly larger area get to decide together what they want the collective area to be like as well right? Surely local politics can be overruled when the policies start having a material effect on individuals outside of the local jurisdiction.

I spent some time researching this after reading your comment, not a lot admittedly. There seems to be a great deal of uncertainty around the topic but I came away with the impression the parent comment is closer to the truth than your own.

I don't see that implication being made and I have trouble believing anyone could read that into the above in good faith. The linked questions mentions that this has created an uncomfortable environment for female undergraduates -- but no allegations of illegal behavior.

Joking aside, what this could mean is a larger percentage of ad revenue shared with smaller publishers (website and mobile apps). The current situation is not entirely unlike the app-store cut these companies take.

It's not a good headline, if you read the article it is mentioned that the tested vehicles could only operate for 4 hours before "conking out". Which I can only assume means they are running out of charge. I would expect the charging time for these niche vehicles is not state-of-the-art and the infrastructure is poor, so that makes sense.

This is also a very interesting concept/question when it comes to AI writing software for practical applications.

Would a large language model benefit from descriptive variable names when it comes to code understanding, or would this just be for human benefit? My first thought was that a computer (e.g. compiler) does not care what the token is named. But a large language model may actually benefit from it, certainly chatGPT is sensitive to it.

But then, doesn't it mean that it could be fooled by misleading variable names (as a human would), something we would criticize any system for. "Alpha*** is easily fooled by changing variable names, making it completely unusable for blah blah".

> The difference between Twitter and Facebook is that Facebook can make money.

Twitter is profitable (last 2 quarters) and is earning something like $3B a year.

https://www.nasdaq.com/symbol/twtr/financials?query=income-s...

Note that salary is also close the same wage (~10% more) as an electrician, accountant, or boilermaker.