#PersonalOpinionOnOldishGame
You can't really finish #MonsterHunterWorld, but I have played as much as I am going to (100+ hours), so here are a few thoughts about it.
TL;DR: it is a good game with some incomprehensible flaws.
1/
Monster Hunter: World is the Nth (with N being a large integer) game in the the Monster Hunter series, but it was the first one I ever played (the new one, Monster Hunter: Rise is only on Nintendo Switch).
2/
The story is non-existent, so let's ignore it. It is just a poor excuse for you to run around some well designed maps hunting and killing dinosaur-like monsters.
There are only 5 maps in the base game, but they are large enough not to be too repetitive.
3/
The main strength of the game are the battles against huge monsters. The monsters are well designed, well animated, and act in a way that you get the feeling they exist on their own, and not just as opponents to the player.
4/
The monsters will feed, tussle with each other for territory, poo, lay eggs, steal eggs, get angry if you steal their eggs etc.
They are by far the strongest point of the game.
5/
The combat system is good and centered around the idea that you have the choice between a number of different weapons, each playing very different, to choose from. The huge choice is a confusing at the beginning, but chances are you will have fun with at least a few of them.
6/
Weapons range from "sword and shield", to submachine guns, to weird contraptions that change shape while you fight. It makes no sense, but the result is fun, so 🤷🏻‍♂️
7/
The main problem of the game is that the menus are the worst menus ever designed by a human mind. And in a game where browsing through the menus is ~20% of your time, this is a big problem.
8/
It genuinely feel like they had a bad menu in the '90s and instead of making it better, they just added layers of nonsense to it through the years.
Eventually you get used to it. But it is objectively bad.
9/
The other problem is that the game is designed to encourage mindless grinding. Do you want to forge this weapon? You will need an ingredient that has a 1% chance to drop from this big monster! So you are expected to just keep hunting the same monster over and over.
10/
I had fun with it (honestly, the fight are not very difficult even for my ageing reflexes. So it was a relaxing activity), but it feels it really needs to be streamlined and cleaned up of a ton of legacy mechanics.
11/11

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More from @j_bertolotti

Sep 12
#PhysicsFactlet (342) Lagrange multipliers
Strictly speaking Lagrange multipliers are not "Physics", but they are so useful to solve so many Physical problems, that it is definitively worth looking at them.
1/
Before we even introduce them, let's solve a super-simple problem, which will form the basis for our motivation to look into Lagrange multipliers:
Find the minimum of the function f=x²+y².

Yes, I can hear you shouting x=y=0, but let's still do the calculation.
2/
The way you find the minimum of a function is to check the points where all the partial derivatives are zero (in this case we have 2 variables, so we will look at the partial derivatives with respect to x and y): df/dx=2 x, df/dy=2y --> 2x=0, 2y=0 --> x=y=0.
3/
Read 15 tweets
Jul 18
#PhysicsFactlet (335)
Yesterday, at a small playground where my son was playing, I saw this Kugel fountain, so here comes a short thread about Kugel fountains and how they work.
🧵 1/

(Alt Text: a Kugel fountain slowly rotating in a sunny day.)
First of all, what is a Kugel fountain?
There are a few variations on the theme, but usually they are big stone spheres, sitting on a hemispherical hole, with water flowing from below. Despite their weight, they can spin with a small push, and keep spinning for a long time.
2/
How does it work?
It can't be buoyancy, as the stone sphere is a a LOT more dense than the water (we all have direct experience of stones sinking when you put them in water, and this one is not any different).
3/
Read 10 tweets
May 13
#PhysicsFactlet (331)
"Anderson localization" is a weird phenomenon that is not well known even among Physicists, but has the habit of popping up essentially everywhere.
An introductory thread 🧵
1/
The idea of "localization" originally came about as an explanation (by P.W. Anderson, hence the name) of why the spins in certain materials did not relax as fast as expected.
nobelprize.org/prizes/physics…
2/
What Anderson realized was that when you have a wave (in this case a quantum mechanical wavefunction) that propagates in a random system, interference can play a major role, and potentially impede propagation completely.
journals.aps.org/pr/abstract/10…
(Paywalled)
3/
Read 19 tweets
Mar 7
New paper on #ArXiv!
"Tracking moving objects through scattering media via speckle correlations"
With @YJaureguiS, and Harry Penketh.

Short(?) thread explaining what it is about.
1/
arxiv.org/abs/2202.10804
Scattering is a major problem for imaging, and it doesn't take very much of it before we can't see essentially anything of what it is happening.
Not surprisingly, imaging in the presence of scattering is a very active field of research.
2/
There isn't a single best way on how to deal with scattering, and the answer depends a LOT on how much scattering we are talking about and its properties.
As a rule of thumb, the most complicated situation is where all light is multiply scattered.
3/
Read 13 tweets
Jan 3
#TheLongRoadToLearnSomethingNew
I decided it is high time I learn something about machine learning. I couldn't care less about learning how to use Tensorflow or any other package that do machine learning for you. I "just" want a Physicist's intuition for how and why it works.
1/
A million years ago I asked here for advices on resources. Some were very good advices, some were not. But I am mow armed with a textbook, and will irregularly update here on my progresses.
2/
I am not very far on my path. I've read a few online resources and (so far) the first 30 pages of this book.
I am aware machine learning is a HUGE topic, so I will begin by concentrating on neural networks (and probably a sub-sub-class of neural networks).
3/ Image
Read 11 tweets
Dec 31, 2021
#PhysicsFactlet The ones I am most proud of from 2021 (in chronological order)
A visualization of what an eigenvector is (at least for 2x2 matrices)
Pulse chirping (keeping the pulse duration constant for ease of visualization, although in reality one usually keeps the bandwidth constant)
Read 8 tweets

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