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Omega miner Mod

Publish: 2021-05-17 01:17:02
1.

I still remember that at this year's TGS conference, "Dyson ball project" spent 10 minutes to let its name reside in some foreign science fiction and simulation sandbox player communities

Due to the limited experience time, I can't bring you the complete experience of Dyson ball project, but one thing to share is that the current game scale is just the beginning

a few months ago, the author sneaked into the test group of Dyson ball project, which includes only five developers of pomelo cat studio, as well as the publisher gamragame, and a group of test players who analyze many details of the game every day and suggest tuning

at present, the trial version that you see is graally polished out after several months and hundreds of QQ discussions every day. Sometimes I wonder if the sealed test players will be too "harsh" to argue about the sorting cycle (between milliseconds) of a sorter

however, when the base has begun to take shape, it is found that these details will indirectly affect the rationality of the logarithm and the accumulation of the whole logistics transportation network

when a large number of players swarm into the game, these problems will be exposed. Tuning is the most important part of a sandbox game. The potential of project Dyson's ball is enough for the sealed test players to take it seriously. It's a good thing that they have been involved in it for a long time, hoping to polish the game better

"from a part to the final grand proct", the charm of Dyson ball project lies in this

2.

People will wonder what this "Dyson" has to do with that vacuum cleaner, of course not


the Dyson sphere is a super large artificial "sphere" around a star. The Dyson ball project is an amazing cosmic super project created by players from the first miner, laying the proction + processing transportation chain, synthesizing high-level procts, flying to the universe, establishing a planetary resource transportation network, and finally for the continuation of the "master brain"


e to the limited experience time, I can't bring you the complete experience of Dyson ball project, but I can share one thing, that is, the current game scale is just the beginning


the author has sneaked into the sealed beta group of Dyson ball project, which includes only five developers of pomelo cat studio, as well as the staff of gamra game, the publisher, and a group of sealed beta players who analyze many details of the game every day and suggest tuning



however, when the base has begun to take shape, it is found that these details will indirectly affect the rationality of logarithm and the accumulation of the whole logistics transportation network


when a large number of players swarm into the game, these problems will be exposed. Tuning is the most important part of a sandbox game. The potential of project Dyson's ball is enough for the sealed test players to take it seriously. It's a good thing that they have been involved in it for a long time, hoping to polish the game better


"from a part to the final grand proct", the charm of Dyson ball project lies in this

3. Now the development of artificial intelligence is in full swing, which has aroused many people's interest in learning artificial intelligence. When we learn Artificial Intelligence, we will come into contact with algorithms and data. Artificial intelligence is composed of many algorithms. Therefore, we all think that algorithms are more important than data in artificial intelligence learning. But is this the case? In this article, we will answer this question for you
many literatures and reports on artificial intelligence focus on machine learning algorithm as the most important part. Mainstream media seems to equate algorithms with human brains. They seem to be conveying the message that complex algorithms will eventually surpass the human brain and create miracles. Of course, they also emphasize "deep neural networks" and "deep learning," and how machines make decisions. Such reports make people think that a company needs to hire machine learning experts to build perfect algorithms if it wants to apply artificial intelligence. But if an enterprise does not think about how to obtain high-quality algorithm, even after a large number of specific training data learning, the machine learning model will still proce a result that does not match the expectation, which seriously affects people's impression of artificial intelligence
of course, the importance of data is the content mentioned above. If there is no data, it is like buying a mobile phone without battery, and the battery adaptability of the mobile phone is also different. If there is no suitable battery, it can not work normally. In artificial intelligence, if more training data are given to the machine learning model, the more accurate the machine learning model will be. It's like constantly charging a cell phone, so the battery utilization rate will continue to improve. Training data is more important for machine learning model than battery and mobile phone. Therefore, we must pay attention to the key point when we work on artificial intelligence, that is, the quality and quantity of training data are at least as important as the algorithm. We should ensure that the plan and budget for the deployment of artificial intelligence reflect this. This is also something that all enterprises and companies need to pay attention to
in this article, we will introce to you whether data is important or algorithm is important in artificial intelligence. In fact, both of them are important, and there is no one more important than the other. At present, the public's misunderstanding of artificial intelligence is that algorithms are more important than data. Therefore, if we want to learn Artificial Intelligence well, we should treat every project and every stage of knowledge well. I hope this article can help you.
4. Now what platform does not develop offline, just like cbck
5.

The Dyson sphere is a super large artificial "sphere" around a star. The Dyson ball project is an amazing cosmic super project created by players from the first miner, laying the proction + processing transportation chain, synthesizing high-level procts, flying to the universe, establishing a planetary resource transportation network, and finally for the continuation of the "master brain"

The beginning work is similar: Icarus robot starts with collecting natural resources, manually builds mining machines, pumps and other collection equipment, and sends ore, water and oil to the manufacturer or smelting equipment through the transportation track

after the completion of the simple proction and processing chain, a huge science and technology tree is waiting to be unlocked, more demand for synthetic procts and the placement of new buildings make the simple transportation chain more complicated

relying on the sorter, four-way diverter and other transportation auxiliary equipment, we can achieve efficient logistics transportation, and we need to constantly optimize our route to make the structure clear

6. The power consumption of FPGA is the sum of dynamic power consumption and static power consumption, and considering the sum of power consumption of each power supply

power analysis
the total power consumption of the whole FPGA design consists of three parts: 1; 2. Design static power consumption; 3. Design dynamic power consumption
● chip static power consumption: when FPGA is not configured after power on, it is mainly consumed by the leakage current of transistor
● design static power consumption: when the FPGA configuration is completed and the design is not started, the static power consumption of I / O, clock management and other circuits should be maintained
● design dynamic power consumption: the design power consumption after the FPGA design starts normally; The power consumption of this part mainly depends on the level used by the chip, as well as the occupation of FPGA internal logic and wiring resources
obviously, the power consumption of the first two parts depends on the FPGA chip and the hardware design itself, so it is difficult to improve greatly. The third part of power consumption can be optimized: design dynamic power consumption, which accounts for about 90% of the total power consumption, so recing the design dynamic power consumption is the key factor to rece the power consumption of the whole system. As mentioned above, the power consumption will increase the heat output of FPGA. Is there a quantitative analysis? The answer, of course, is as follows:
Tjmax & gt; θ JA * PD + TA
where Tjmax is the maximum junction temperature of FPGA chip; θ JA is the junction to ambient thermal resistance between FPGA and surrounding atmospheric environment, in ° C/W; PD is the total power dissipation of FPGA, and the unit is w; TA is the ambient temperature.
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