> how do we identify these people who add nothing positive — or not enough positive — to our lives?
The dude invokes bayes theorem (the theorem that is trending right now) to solve such a basic issue? His grandmother can give him better advices than Bayes.
ML or more generally mathematics do not cause anything. People who misuse mathematics are to blame here. Some fields are simply using tools they don't understand and this predates ML advances by decades. Thinking of stats use in psychology and medicine for instance.
This trend of presenting ML are some kind of magic powder is ridiculous. I blame hyped presentations by influential ML scientists for this.
OK, my point is what could be done beyond generating images in some style? Can we generate interesting mock data given a database for instance (of course this is exactly what you did in a way, but I have in mind e.g. a database containing some numerical/categorical features known to a specific accuracy)?
> Turns out it can disentangle pretty much any set of data.
All the example I have seen (including your links) are variants of face generation algorithms. Any ideas on how this could be useful beyond image generation in some style? Specifically for (data) science?
Sorry if this is a naive question.
Edit:
By "variants of face generation algorithms" I mean any image generation really.
I used skype extensively in its pre-Microsoft era as pretty much all the academics i know. It was synonymous of exciting discussions with collaborators. It had something special which set it apart from usual calls. A kind of special space for discussions.
Last time i used it it took me a day to figure out what my username was. Had to search forums, ask on the internet, and finally navigate the awful microsoft website back and forth to finally find a childish live:xxxxq122 username (MS blocked my 10+ years account because it didnt like the date of birth i provided in a hurry. I was “too young” to use the service). I have no idea now what happened to basic things like a contact list. The new interface should be studied in design schools on all the things that shouldn’t be done.
I find myself using whatsapp or gtalk for meetings now. Having to call collaborators using the same device/service i use with my family. Thanks Microsoft.
The difference lies in the fact that absolute rigor to assess truths is not as fundamental in theoretical physics as it is in mathematics. Uncertainty is accepted. Physics puts a premium on empirical results and intuition over the more formal treatments common in mathematics (many important results/tools are not mathematically well-defined e.g. Feynman path-integral in d > 1).
I don't think the "you can do anything" mindset works in real life. It helps self-help book authors sell their stuff, but it's not a good strategy to live by. (Incidentally, this reminds me of Key & Peele's "You can fly" sketch).
What does work though is this: advanced formal education in a topic. Once you have that you can start thinking on how to solve some simple open problems. And if you are lucky and turn out to be extremely smart, you may be able to tackle more challenging problems. Some amount of self confidence may also you to keep going but doesn't make you a genius overnight.
Simply going to a mindset where things are 'not hard' is closer to delusion than it is to anything else.
In academia we get often emails from people who solved quantum gravity (e.g. using fire), show us how einstein is wrong (e.g. using a pendelum), etc. I'm pretty sure they also convinced themselves to "Stop believing everything they're told about how "hard" something is"
> It's not that hard people. Stop believing everything you're told about how "hard" something is.
There are still many problems in physics and mathematics which are considered "hard" (e.g., dark energy, Riemann hypothesis, etc). Can we crack them by simply adopting your positive mindset?
> Feynman concluded: “for my money Fermat’s theorem is true”.
> "the main job of theoretical physics is to prove yourself wrong as soon as possible."
Great example of the main difference between mathematicians and theoretical physicists .
This reminds me of another magician, Enrico Fermi, who was also an extremely good mathematician but didn't pursue rigor or precision for the sake of it: 20% was good enough precision for him for most cases.
> but it's a zero-information statement until they describe what they know that I don't
I don't think it's a zero-information statement at all. If S. Weinberg tells me that my physical arguments are wrong but he doesn't have the time to say how/why, then it's certainly a non-zero information statement and I'll scrutinize my line of thoughts thoroughly after that. Dismissing this as a zero information statement would be pretentious from my part. The same goes for you against the expert in political finances.
It seems that there's an underlying assumption in your argument that we're all equal and equally capable of having opinions on anything unless someone comes to us, and spends time thoroughly showing us why we are wrong. Or that we are all correct until proven wrong. This is problematic because 1/ we're not all equal, and acknowledging that we dont know everything is important, 2/ it's unlikely that there's always an expert around willing to spend time educating us everytime we feel the need of commenting on things we dont know, and 3/ we may not comprehend why we are wrong by lack of proper education.
I was thinking specifically of the AI/ML folks. Many top researchers from universities, google, open ai, fair, etc. are super active online. I don't think they do it for career visibility.
I agree. I've come to the same realization recently when I started following the work of some CS researchers. I was (and still am) amazed to see how active they are on the internet (here, twitter, medium, youtube, github, blogs, etc.)
In the far more conservative physics community, there are (essentially) only two ways of communicating that are acceptable: writing academic papers, or delivering academic talks. Online presence is seen with suspicion.
I am not sure if this is a good or a bad thing.
>People who do a lot of personal PR are more likely to be narcissists—and this is a more negative indication in disciplines where self-promotion is an anomaly.
We have here someone who doesn't/never work/ed on HEP but on something so remote from it that I would find it hard to even call it physics sometimes. She goes on a sudden crusade against HEP and all its (prominent) practitioners who spent years working on it. She uses some facts we all agree on (uncertainty about the future, etc.) then twists them in a way that makes it look as if the whole HEP community is part of a huge conspiracy to deceive the public. Our truth warrior then courageously exposes them in her ... blog. BS.
On the other side how the hell can she justify her salary and grants to taxpayers? Why isn't she doing some biology or something? It's all so incoherent.
I used to read her when she was less crazy. But I really can't stand her anymore ... it's just too much.
It's all very strange. Two of the most popular and active bloggers in HEP are totally crazy and politically extreme (although in opposite extremes). Blogging seems to be an unhealthy activity for physicists.
The vast majority of the refugees in Europe are in 2 countries: Germany and Sweden. Read my comment above. The rest of European countries, including France and central Europe, essentially reacted by voting for populists (borderline fascists in some countries).
Your second comment on Germany is totally irrelevant.
And 1 million people for Europe is nothing considering the total population and wealth of the union. As I write in the comment you ignored: some of the poorest and smallest countries in the world took in more than a million refugees and without help.
1. Refugees are not migrants. 2. A few thousands refugees almost broke Europe (excluding Germany and Sweden). Extreme right on the rise pretty much everywhere (including Germany and Sweden). And we're talking about the richest countries in the World. Compare that with Colombia, Jordan, Lebanon to name but 3 countries.
> The US alone accepts one million immigrants per year.
"of whom about 600,000 are Change of Status who already are in the U.S". However, it's not about immigration.
How many Syrian/Libyan/Afghan/Venezuelan/Iraqi _refugees_ did the US take in the last 5 years? (You've probably noticed that the examples I cited are not random).
The dude invokes bayes theorem (the theorem that is trending right now) to solve such a basic issue? His grandmother can give him better advices than Bayes.