cnr.it is a domain which belongs to the Italian Research Council, and that subdomain seems to be a blog by the Institute of Microelectronics and Microsystems.
These are not scammers, it's probably an amateur researcher which published that information in a blog which is usually read by no-one. Probably it wasn't even meant to be public. But because of the prestige of the domain, it becomes first in relevant searches.
If you track down the author and send him a quick mail, I'm 100% sure they'll help.
> it's probably an amateur researcher which published that information in a blog which is usually read by no-one.
Ah, but this is the new method of SEO trickery and credential scamming. Publishing a 'guest post' on a high-ranking blog subdomain of a trusted instititution. There was a story of someone doing this on Harvard University's blogs, which I can't find right now.
But I found something even better. An actual UpWork posting promising to publish your crap on Chapman.edu's university blog:
Honestly, a researcher should know better to not plagiarize or to give attribution better than that. This is core in their job. If they do exactly this in their papers, it's going to be bad for them and they know it.
It's good they linked to the original post and that the link is the first thing we see, but nothing says that it's the source, and no paragraph explains that the content comes from elsewhere.
I also don't see why the content should be copy-pasted instead of just a link.
I see no malicious intents, it's probably done in good faith, but meh.
To the author: did you try to reach out? I'm sure something can be done about it if it bothers you. I expect the author of this copy to be receptive.
> I also don't see why the content should be copy-pasted instead of just a link.
Quite possibly an easy way to preserve the content in case the original goes offline and to share it with colleagues. Perhaps they wanted to link to it from some long-lived or even printed material. Not saying it’s the best way to do so, but it’s plausible and not malicious.
It’s plausible and not malicious, understandable too, but it's not hard to say it in a sentence at the beginning of the post.
This is a public blog, not some internal website.
Anyway, my previous comment probably sounds harsh because it is the way I wrote it (because I previously worked in a research lab, so I kinda feel disappointed), but I still consider this a minor fuck up and it happens to everyone, for sure.
If you can, try removing the source of stress. Depending on your situation, this may involve changing work environment.
I've been there, I was at a point in which I would either burn out (if I wasn't already) or change environment completely. I changed environment, and it's been the most difficult yet the best decision in my life
Exactly the same here! What a memory. In my case, my fellow students started sending broadcast messages which included a lot more profanity. They reached the computer of the school principal, which immediately came to our lab asking for explanations. Lucky for me, the teacher was a great guy who just knew I was the one that started all that mess, but he didn't say a word.
I also remember writing .bat fork bombs during the pauses. My classmate would pick a victim and while they were away I would completely freeze their PC. Yes, silly. And don't get me started on the remote shutdown messages, again enabled by default.
> Instead of doing anything fancy, my program generates the coefficients at random to explore the space. If I wanted to generate a good driver for a course, I’d run a few thousand of these and pick the coefficients that complete the course in the shortest time.
It is worth pointing out that this strategy can likely overfit on the data that you have used for training: when you change the track, your car may not behave as good as before. In other words: the coefficients are only good for that specific track(s).
The author is still using Machine Learning, even if not with neural networks: the need for rigorous strategies for model selection doesn't disappear.
> It is worth pointing out that this strategy can likely overfit on the data that you have used for training: when you change the track, your car may not behave as good as before. In other words: the coefficients are only good for that specific track(s).
More generally, I think this approach is only suited to "static" courses, which only matter in contrived demos. Any real use of a steering algorithm requires reacting to conditions that can't be predicted a priori; e.g. if you have to avoid collisions with other cars, and one car is controlled by a human player, every run is effectively a different track and overfitting like this would not be an option.
Sure, that's clearly the intent, but it's not what's written. What's written is that those industrial engineers who don't like sand, are also Anakin Skywalker.
Mostly opinions without data, as usual. Why can't we as a community switch to a more serious scientific/engineeristic approach, at least in those areas where it is easy to do so?
Why should I trust this blog post on the "Caching" point, for example? It's got no data and no references.
"What are the chances that your user has visited a site which uses the exact same CDN as your site?" ... hey, you can measure that.
These are not scammers, it's probably an amateur researcher which published that information in a blog which is usually read by no-one. Probably it wasn't even meant to be public. But because of the prestige of the domain, it becomes first in relevant searches.
If you track down the author and send him a quick mail, I'm 100% sure they'll help.
I've worked at CNR.