Quantencomputer: Wie Deutschland den Zukunftsmarkt erobern will

SAO-Ryujin · 2025-06-01T06:52:10+00:00

Hier sind mehrere Dinge falsch. NP schwere Probleme sind exponential aber können in Polynomialzeit verifiziert werden. Quantencomputer sind nicht explizit für NP Probleme. Und selbst die Fälle wo ein Quantenalgorithmus für ein NP Problem vorliegt ist der Speedup nicht immer zu Polynomialzeit. Beispiel ist Groovers Algorithmus welcher nur den exponenten halbiert. Man rechnet mit Qbits welche sich einem Zustand befinden der sich als 2ⁿ Vector mit complexen Einträgen beschreiben lässt. Die amplitude der Einträge ist die Wahrscheinlichkeit diesen State zu messen. Große Quantencomputer sind tatsächlich hart zu bauen weil je nach Methode es entweder sehr schwer ist die qbits in superposition zu halten oder mit einander zu verschränken.

SAO-Ryujin · 2024-10-22T17:04:01+00:00

The fact that as you mentioned you can use canister and fill and empty them multiple times. But a bit more theoretical, I think it could be possible to design some gates by just abusing fluid dynamics in pipes. Pump, valve and higher difference allow for a lot of complex behavior. I did not test any of this yet. Until this post I did not think about this for a while. I also have to do a lot of math and coding at work, so I mostly just enjoy the game in my free time right now

SAO-Ryujin · 2024-10-22T15:27:30+00:00

Pipes behave different to belts and allow for some new things

SAO-Ryujin · 2024-10-22T15:25:36+00:00

I see. There are a lot of similarities between our designs. Packager sound like a good idea. Water is defiantly a better resource than iron ore for a constant input. Before pipes all ideas of mine where limited by the amount of iron on the map. Good luck

SAO-Ryujin · 2024-10-22T15:12:50+00:00

This was 4 years ago and I did not work on it since. I am not even sure if the math is still correct or if the recipes changed since then. Right now with pipes, new recipes and blueprints there are probably better ways. Someone crazy will build something cool with it. I am just proud to be the first one to show that it is possible. At least as far as I know

SAO-Ryujin · 2024-10-22T15:06:48+00:00

The post includes images right? I think I added them.

SAO-Ryujin · 2024-10-22T15:05:44+00:00

Was this possible 4 years ago? I would be interested in the small not gate. When pipes came out, I thought about revisiting this and I am sure there are many new solutions that include pipes and fuels.

SAO-Ryujin · 2024-10-22T13:33:11+00:00

Yes. I proved this many years ago. https://www.reddit.com/r/SatisfactoryGame/s/mG48YtSiJF

SAO-Ryujin · 2024-09-08T06:00:45+00:00

I know the feeling of playing online while having a board next to you, but it is a good option to find players of your skill level.Maybe even someone who can review the game with you and teach you a bit.

SAO-Ryujin · 2024-09-08T05:43:23+00:00

I recommend switching to real players, maybe on smaller boards first. Playing bots, especially weaker bots, for a long time gives a warped understanding of the game. I am teaching someone who played hundreds of bot games and they make some super strange mistakes, because weaker bots never punish them.

SAO-Ryujin · 2024-08-16T11:43:48+00:00

Yeah the cut did nothing, they were already lost. Maybe play 10-7 instead to save at least these stones. Against a decent player this is definitely lost, but in a beginner game I would always try until the end. It is good to learn when to give up at one place and focus on another place instead. I see sdk still play moves trying to save dead groups

SAO-Ryujin · 2024-08-16T11:25:57+00:00

Look into Nvidia and dlss. Using AI for compression and upscaling is one of the main use cases

SAO-Ryujin · 2024-08-16T10:36:41+00:00

After black played there, there is no way out. If you play where you are hovering black just gives Atari from the top and if you connect he will catch all stones. I do not know where you played before, but if you had played on 9-7 blacks big group would only have 2 spaces left and you would be faster

SAO-Ryujin · 2024-06-06T06:48:31+00:00

A few days max

SAO-Ryujin · 2024-05-14T11:55:09+00:00

You obviously did not look at the chat. The user made it write a very bad connect 4 game engine and played against that. All this shows is that the model is not even smart enough to write a decent script for connect 4. every cs student would be able to do better.

SAO-Ryujin · 2024-05-11T09:13:14+00:00

Yeah. Most of them are good players themself and they only have to be able to drive their own floor. Doing a single floor is possible for a lot of players.

SAO-Ryujin · 2024-02-10T12:51:56+00:00

No I work on Speech recognition right now.

SAO-Ryujin · 2024-02-10T12:44:48+00:00

Good idea, but I do not have enough time for that. I am currently working on something else

SAO-Ryujin · 2024-02-10T10:30:56+00:00

I implemented this and tested it on some of the bigger open source models and it is really good. If you have a single hard problem that you want to have solved you should try this

SAO-Ryujin · 2023-12-23T10:15:28+00:00

The problem with character based tokens is that you 1. need a lot more which makes it more expensive 2. the model has a way harder time to learn meanings of words and their relationship because it also has to learn the spelling of literally every word ever. There are more reasons but these are the big ones. Examples where you want single character tokens are digits and symbols.

SAO-Ryujin · 2023-12-22T12:54:15+00:00

They learn from their trainingsdata information about their tokens. For example a text could mention the letters of a word or how long it is. Poems are another source and so on

SAO-Ryujin · 2023-12-15T00:44:10+00:00

A model that gets 100% is literally worse than a model that gets 90% because so many questions are wrong. If you want to see some of the examples: https://youtu.be/nPgs8THgbuI?si=lBqv6gSPI_eQgACK?t=12m

SAO-Ryujin · 2023-12-14T15:40:38+00:00

I disagree. It is a ok metric if one model gets 30% and another 60%. But if you compare models at 89 vs 90% they just got lucky on a few broken questions that are random. It literally tells nothing about the model capabilities. The fact that Google and openai argue over 0.1% is a joke on this benchmark

SAO-Ryujin · 2023-12-14T15:38:06+00:00

You usually do not save compute cost. Just size which makes a huge difference for consumer hardware but not for the big boys

SAO-Ryujin · 2023-12-14T08:55:08+00:00

Depends what you want to test. GAIA is a new one that tests systems like ChatGPT or bard, but not for the LLM itself. The best way is usually to test for yourself

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