amazing video. first time I seen this channel but I’m impressed, not only with all the effort for gathering the data but also with the video itself, its one thing to do all this work of implementing the code and playing the simulations but presenting all this data in an entertaining way is just as hard, if not harder.
Okay, I’m in. I don’t preorder games anymore, but I’ll definitely be keeping an eye on day 1 reviews to make sure the game isn’t broken so I can buy it right when it comes out!
I also don't preorder, and I DO buy basically all FromSoft games on release because I know they'll be bangers. But I've been burned before with Dark Souls 3 suddenly increasing in price by 50% in my region right before launch. I'm torn. I guess I'll wait and see, again.
Whenever I hear of a game I might like, or buy one on a whim I add it to a list. I do something similar with books and movies. The purpose of the lists aren't to put pressure on myself, but to remind myself of all the things I'm interested in and to avoid the feeling of "I have nothing to play/read/watch". If I'm not enjoying something, I just won't finish it and I check it off the list so I know I tried. For me, deciding what to do with my limited time can give me analysis paralysis. I don't see the list and backlog as a chore, but more of an easy menu of options that I've already considered.
I really wish more indies could take on the no-sales policy. It’d give me tons more peace of mind to buy a game when I actually want to play it, rather than always waiting and doing weird backlog hoarding when Valve decide it’s wallet-opening-time.
But as the video shows, the policy was a risk for Wube even back in the day – it’s an even bigger risk now that everyone and their dog expects to wait for the sale, and especially if you happen to have a game that’s not quite as incredibly popular as Factorio.
It’s not exactly the same thing, but itch.io allow developers to have a “reverse sale”, where the price goes up for a given period. It was mostly a joke feature, perhaps intended to provoke a little thought about sales culture.
I always preferred the HLL model of sweaty milsim over Squad but…
A decent number of games have tried (US-)Vietnam over the years and it just doesn’t work. Because people think of the Vietcong versus GIs in jungles or ambushes in towns and along the river. And… the problem with that is it was a ridiculously asymmetrical fight. Like, yes, some troops did have AKs but mostly they were using WW2 era weaponry and maybe SKSes And firing precision shots through a jungle was a whole thing.
It was incredibly rare that these were standing fights. They were bloody ambushes that either ended in slaughter or… kind of just wandering away. And while that could be REALLY REALLY interesting from a gameplay standpoint it also breaks the milsim model of “every ticket matters”
As for those standing fights? They really weren’t that different than any other cold war conflict except that the ridgeline might be a wall of jungle.
Also… look, playing HLL pretty much guarantees you are dealing with, at best, rampant racism because “They were racist back then”. As someone who has tried to find some fun shooters over the years… going to Vietnam IMMEDIATELY reminds everyone that it is still perfectly okay to be mark wahlberg levels of racist towards Asian people. The number of videos on games like Rising Storm that just have random “ha ha, spawn at ching chong” from even “respected” youtubers is just infuriating.
Have you actually played Rising Storm 2: Vietnam? I thought the setting worked decently well there. And I really didn’t encounter any racism aside from popular lines like “Welcome to the ricefields mfer”. It still has a couple of populated servers going even though it’s kinda outdated compared to HLL or Squad 44.
Yes, I have. RSV is mostly corridors outside of a few maps that try to represent a trenchline. It sort of works because spawns are fast and tickets are plentiful but it is still mostly just a day at the Metro in BF3+. Once you start making tickets count more, that starts being a lot less viable.
And yes, I experienced a LOT of anti-Asian hate while playing. Understand that some of us have different levels of tolerance for that than others (which was kinda my point on why this is gonna be extra bad).
My dude, most of the biggest battles of both Vietnam wars were against the standing army of North Vietnam (PAVN), which was a proper army, not just against the VC that were irregular insurgents attacking the South.
Okay. I am not familiar with Knudsen but holy crap at the number of times he has said “All the good will the community had for arthmoor and the unofficial patch had finally run out. But NEXT TIME, NEXT TIME people won’t be so forgiving…”. Also very much not a fan of the editorializing when he highlights the text from a forum post but does word replacement or puts on a nasty voice.
And I assume the constant Argonian face zoom ins are arthmoor’s avatar or something but… I just kind of giggle every time I look up and see that arg-O-face.
Very informative video but he is no Jacob Gellar or Joseph Anderson. Also… putting some barriers in the way of my half-baked plan to replay the TES series over the next few years. Was really hoping my days of spending hours making mod lists was over.
CSGO used to have Overwatch which is an anti cheat system that uses trusted and experienced players to go through video footage of reported players. With this method I both reported blatant spinbotters, wall hacking, and other chears. I also was on the side of watching back footage of hacking players.
Say AI trains on this data, it might work.
I’m not a fan of this though because knowledgeable and experienced players will be better than AI.
What actually exists but what I have yet to see implemented in any game I play are those server-side “AI anti-cheat” solutions like from anybrain that basically just analyse the players behavior to fit certain criteria. According to areweanticheatyet.com though there are four games using it already (the most well-known one probably being Lost Ark). In theory ai models can be very efficient and accurate at this (we are not talking about transformer models here like with the current llm craze) but that all depends on how they train a model and what the training data looks like.
I am not sure what the user above is thinking, but to play devil’s advocate:
One thing that modern AI does well is pattern recognition. An AI trained on player behavior, from beginner level all the way up to professional play, would be able to acquire a thorough understanding of what human performance looks like (which is something that games have been developing for a long time now, to try to have bots more accurately simulate player behavior).
I remember someone setting up their own litmus test using cheats in Tarkov where their main goal was just to observe the patterns of other players who are cheating. There are a lot of tells, a big one being reacting to other players who are obscured by walls. Another one could be the way in which aimbots immediately snap and lock on to headshots.
It could be possible to implement a system designed to flag players whose behavior is seen as too unlike normal humans, maybe cross-referencing with other metadata (account age/region/sudden performance anomalies/etc) to make a more educated determination about whether or not someone is likely cheating, without having to go into kernel-level spying or other privacy-invasive methods.
But then…this method runs the risk of eventually being outmatched by the model facilitating it: an AI trained on professional human behavior that can accurately simulate human input and behave like a high performing player, without requiring the same tools a human needs to cheat.
Cheating humans already perform closely enough to trick such a system. Many cheaters are smart enough to use an aimbot only for a split-second to nail the flick. With a tiny bit of random offset, those inputs indistinguishable from a high-skill player.
These tricks may make it indistinguishable to a human moderator, but machine learning is actually really good at detecting that. But most companies don’t have the expertise, resources or training data to build a proper model for it.
Machine Learning is really good at CLAIMING it detected that.
The reality is that every few months there is a story about a fairly big streamer/e-sports player MAYBE getting caught cheating on stream. Sometimes it is obvious and sometimes it really becomes “Did they just know the map well enough to expect someone to come around that corner?”.
And a lot of times… it really is inconclusive. A somewhat common trope in movies is the veteran gunslinger literally aims at the wall of a stairwell and tracks where they expect the head to be and either fires a few rounds through the wall or waits for them at the bottom and… that is not entirely inconceivable considering that people tend to not crouch or move erratically down stairs. Obviously Jonathan Banks has a wallhack but Mike Ehrmantraut is just that damned good.
And false positives are a great way to basically kill a game. ESPECIALLY if they are associated with demonstrably false negatives too.
But you can be damned sure most of the major esports games are already doing this. It really isn’t expensive to train and they have direct feeds of every player in a tournament or twitch event. The issue is that there are (hopefully) tens of thousands of servers active at any moment and running Computer Vision+Inference on every single server is very costly.
And… I seem to recall there was a recent intentionally poorly defined Movement about maybe keeping user hostable dedicated servers a thing? How does that mesh with having every single server need to phone hom (a fraction of) all 32 players feeds to a centralized cluster?
Machine learning doesn’t necessarily require a centralized cluster. Usually running those kinds of models is pretty cheap, it’s not an LLM basically. They usually do better than human moderators as well, able to pick up on very minute ‘tells’ these cheats have.
I understand your point about edge cases, but that’s not something the average player cares about much. E-sports is a pretty niche part of any game, especially the higher ranks. You just want to filter out the hackers shooting everyone each game that truly ruin the enjoyment. Someone cheating to rank gold instead of silver or whatever isn’t ruining game experiences; they’re usually detectable too, but if you get a false negative on that it’s not the end of the world. A smurf account of a very highly ranked player probably has a bigger impact on players’ enjoyment.
Depending on the model, inference can be run with CPU only. To distinguish what was originally proposed (a momentary flick consistent with aimbotting), you are either doing ray tracing (really expensive) or analyzing (effectively) video feeds. Both of which tend to put things more into the GPU realm which drastically increases the cost of a server.
But also? The only way these models can work is with constant data. Which means piping feeds back home for training which basically is never inexpensive.
Aside from that: if it was as simple as you are suggesting then this would be a solved problem. Similarly, if people don’t care about hackers outside of e-sports then there would be no reason for games to spend money on anti-cheat solutions when any match that matters would have heavy scrutiny. And yet, studios keep pumping out the cash for EAC and the like.
Since human beings are hot garbage and will always cheat, I really enjoyed playing against the AI soldiers in BF. It can also ensure that the game is playable forever OFFLINE.
Where I live I cant play BF4 anymore. Servers are down for my country, but I paid money for the game. Digital media is a scam once the servers go down. That is why I jailbroke every console I own. Ppl are already reviving BF2 with AI bots. The future is looking bright.
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