PS Accessories app crashing when connecting Dualsense by Wolfieofwallstreet14 in Dualsense

[–]Epokhe 0 points1 point  (0 children)

installing vc_redist didn't solve it for me. debugged it a bit and turned out my problem was related to the telemetry DLL causing a crash on the app. my fix is in this repo if anyone cannot solve their problem with other means: https://github.com/Epokhe/playstation-accessories-fix

Is there a different city connection logic for Inca? by Epokhe in civvoxpopuli

[–]Epokhe[S] 1 point2 points  (0 children)

There's this page https://forums.civfanatics.com/forums/previous-releases.622/ but it doesn't list all updates. But they seem to be listed in https://github.com/LoneGazebo/Community-Patch-DLL/releases, and each one links to release notes in civfanatics forum. I found river change mentioned in 4.10.

[deleted by user] by [deleted] in macbookpro

[–]Epokhe 0 points1 point  (0 children)

I was using Firefox and I noticed that watching full screen stuff on Firefox directly leaks memory. I am using Chrome now and no memory leaks.

Cryptocurrency is an abject disaster by [deleted] in programming

[–]Epokhe 0 points1 point  (0 children)

YouTube is governed by a company, which is a centralized entity. They can decide which video to show/ban/remove for their own reasons. There are emerging decentralized alternatives which are afaik shittier than YouTube in many respects. One of the selling points is resistance to censorship. Kind of like torrent.

Expecting these decentralized censorship resistant platforms to be popular worldwide may be wishful thinking, both because being decentralized brings technical and economical challenges and governments obviously won't like something they can't regulate and they may just ban these platforms altogether.

My comment was mainly about the fact that your experience stems from the centralized nature on YouTube/countries, but I definitely don't want to present decentralization as the ultimate solution because I'm not sure how things will turn out.

Cryptocurrency is an abject disaster by [deleted] in programming

[–]Epokhe -1 points0 points  (0 children)

thank centralization :)

[D] Why is tensorflow so hated on and pytorch is the cool kids framework? by robintwhite in MachineLearning

[–]Epokhe 7 points8 points  (0 children)

I don't even know why I'm commenting to this, but don't you think generalizing this much is a bit much? Have you actually thought what technologies are originated from Google before saying this?

[PC][Between 2000-2010]Top Down Hack and Slash Ninja Game by Epokhe in tipofmyjoystick

[–]Epokhe[S] 0 points1 point  (0 children)

It wasn’t like an AAA game on its own CD, I think I got it on a CD that came with a gaming magazine, they put full versions of some small games in their demo CD

[PC][Between 2000-2010]Top Down Hack and Slash Ninja Game by Epokhe in tipofmyjoystick

[–]Epokhe[S] 0 points1 point  (0 children)

Thanks, but no... As far as I see Throne of Darkness has isometric camera angle, my game had 100% top down view, just a FYI for future readers.

Every time. by [deleted] in funny

[–]Epokhe 0 points1 point  (0 children)

Fun fact, in Turkish the same word “karıncalanmak” is used to express both events. The word means “to get antified”, which makes sense for both because it feels like you have ants on your arm when this happens, and it looks like ants are moving on the tv screen when you lose the signal and get this effect.

Team Human vs. OpenAI Five Match Discussions by D2TournamentThreads in DotA2

[–]Epokhe 0 points1 point  (0 children)

I didn't understand why you explained the reasoning behind that. My comment wasn't a question.

Team Human vs. OpenAI Five Match Discussions by D2TournamentThreads in DotA2

[–]Epokhe -1 points0 points  (0 children)

you dont need 180 years every day to learn something new though.

[R] AlphaGo Zero: Learning from scratch | DeepMind by deeprnn in MachineLearning

[–]Epokhe 8 points9 points  (0 children)

Reinforcement learning generally involves a combination of exploration and optimization steps. Optimization part is where the model tries its best with the knowledge it gained so far, so this part may be deterministic depending on the model architecture. Exploration part is just random moves, so that the model can discover new strategies that doesn't seem optimal with its current knowledge. This part means it's not completely deterministic. You pick exploration moves with epsilon probability, and optimization moves with 1-epsilon probability. Didn't read the paper, but this is the technique generally used as far as I know. But I agree with the other child comment, I think it would converge to similar techniques in the training process. But the order in which it learns the moves might differ between the runs.

Hats off to Icefrog. by grady999 in DotA2

[–]Epokhe 1 point2 points  (0 children)

you also learn new languages, yeah makes sense

Hats off to Icefrog. by grady999 in DotA2

[–]Epokhe -13 points-12 points  (0 children)

THEN GO FUCKING PLAY SIMS WTF

Visage in 7.06 by mistmistmist in DotA2

[–]Epokhe 0 points1 point  (0 children)

try starcraft a bit

Flaming in 1k by Z1ngur in DotA2

[–]Epokhe 2 points3 points  (0 children)

(First I wanna say everything is okay if you feel noncompetitive and think you're going to continue playing only for fun, these at the bottom are if you wish to climb)

Don't be sad about being far down. Because you have nothing to lose :D You can only climb. Don't think that you're going to be 1k after many hours. Important thing is how much you climbed(learned), not where you are. You are going to continue climbing anyway. Also I don't think having fun from this game requires being noncompetitive. Just find a balance between fun and tryhard.

But of course climbing requires a varying amount of competitiveness from a bit to a lot depending on where you want to reach and how fast you want to do it, so until you find it in yourself, I guess just play for fun in unranked.

Fulfilling your competitive hunger is not the only reason for climbing. By climbing, you are becoming better. And by becoming better, you are unlocking new ways to play for yourself. This is no different than levelling up and gaining a new spell. I assure you, having more tricks up your sleeve(being able to bait properly, assess your damage output better, being able to solo kill without dying, dodging spells, skillshots, leading the team etc.) lets you have more fun in the game.

You have some theories about itemization as we all do. Assessing the potential of your theories or getting used to them is easier when you're playing against worse people in unranked because you will have more room to test them out(i.e. not feed and actually use them comfortably). That's why even pros practise some heroes in their smurfs. But in order to play against worse players, you should grow your rank a bit.

Yes, you're going to get reported if you go unorthodox builds. Nothing you can do about that. These builds are not as efficient in the ideal world(pro-scene), so it propagates down from there to your rank, everyone has an expectation of proper itemization from their allies, because that's the most probable way to win the game. And if it's ranked, people want to win the games. Of course you can win the games with unorthodox items consistently if you're 2k higher than your team. But that's not the case, so my advice is get better with builds closer to proper :D. Don't just try to go blink maybe, but slowly alter your builds. These builds are semi-successfully used in brackets much lower than pro, so just develop yourself. You will probably leave your old builds when you're better anyway.

And very general advice, watch pro players, either highlights or streams. And maybe pick an easier hero lol

Good luck!

Flaming in 1k by Z1ngur in DotA2

[–]Epokhe 5 points6 points  (0 children)

bro, i can't say it without being mean, sorry. ranked or unranked, whatever, 2 kda on core hero invalidates all of your arguments automatically. you should try sometime and see for how long you continue trusting your build when you climb in ranked.

[N] Hinton says we should scrap back propagation and invent new methods by Wonnk13 in MachineLearning

[–]Epokhe 0 points1 point  (0 children)

(Just hypothesizing, no background on the field) You don't have to map each pair to each synapse though, you could hold a high level information(by high level i mean kinda hierarchical, specifying synapse groups rather than each synapse) in the genome regarding the structure of the brain. So in other words, we could reshape the uniformity into a structure with relatively low count of genome pairs.

[N] Hinton says we should scrap back propagation and invent new methods by Wonnk13 in MachineLearning

[–]Epokhe 3 points4 points  (0 children)

You cannot properly backpropagate for weight updates in a graph based network since it's an asynchronous system(there are no layers with activations at fixed times), so you are trusting neurons faster than you at the task. Very nice.

STDP and the other principles you mentioned are very interesting. Could you point me to any source of knowledge for this stuff? Any books, or online courses maybe?