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Algebra and language (writing) are two different learning tools. When they are combined, we can expect new methods of machine understanding to emerge. To determine the meaning (to understand) is to calculate how the part relates to the whole. Modern search algorithms already perform the task of meaning recognition, and Google’s tensor processors perform matrix multiplications (convolutions) necessary in an algebraic approach. At the same time, semantic analysis mainly uses statistical methods. Using statistics in algebra, for instance, when looking for signs of numbers divisibility, would simply be strange. Algebraic apparatus is also useful for interpreting the calculations results when recognizing the meaning of a text.
Grind is a process of slowly getting valuable resources (be it experience points or loot) by repetitive and often simple tasks in video games. It has been present from the beginning of gaming but has become more widespread with the popularization of online RPG games because of their leveling systems and competitive elements.
It is highly criticized by gamers around the world for making games boring and work-like, yet many people specifically choose to play grind-heavy games. The reason might be because they find simple repetitive tasks relaxing and distracting from real-life problems, as a form of escapism.
However, there is also a gameplay reason for grinding: getting valuable resources early can make a game easier later. Some popular games like Diablo are even centered around grind. Thus, everyone will have to grind at some point to prevent gameplay from getting too difficult, which quickly becomes an inescapable habit. Later, gamers might apply grinding even to games that do not require it. Interestingly enough, grinding early on can also make the late-game boring because it is going to be too easy if the game was not designed for grinding. For example, in Subnautica, getting a lot of resources early on will make some of the late-game tools useless because all the resources that could have been gained with them have already been gained.
From the example above, we can see that grind does not always improve the gameplay. We can also see that it is not always a necessary process and can be either minimized or avoided entirely: sometimes, the need for it exists only in our mind, forcing us to diminish the fun of actually playing the game. Is it just a question of habit or is there any other reason for us to grind?
Author: Chris Punches (@cmpunches, Silo group). License: "Please feel free to share unmodified".
The following text is an unmodified copy of now removed issue #2250 on rms-open-letter.github.io repository. The text claims multiple violations of different policies, codes of conduct and other documents in creation, content and support of the "Open letter to remove Richard M. Stallman from all leadership positions". The issue has not been addressed.
Starting a startup can be tricky. To make money, you need clients. To attract clients, you need a portfolio. To have an attractive portfolio, you need to… Well, you see where I’m going with this. A lot of founders offer their services for free to escape this cycle. However, there are plenty of issues with this approach. It’s certainly not the silver bullet it might seem. Here we are discussing this topic in detail.
Reverse engineering might seem so complex, that not everyone has the bravery required to tackle it. But is it really that hard? Today we are gonna dive into the process of learning how to reverse engineer.
First of all, try to answer yourself, what are you hoping to achieve with reverse engineering? Because reverse engineering is a tool. And you should choose the right tool for your task. So when reverse engineering might be useful?
Most influential programmers say that code must be self-documenting. They find comments useful only when working with something uncommon. Our team shares this opinion. Recently we came across a code snippet that perfectly proves it.
By the beginning of 2021, Qrator Labs filtering network expands to 14 scrubbing centers and a total of 3 Tbps filtering bandwidth capacity, with the San Paolo scrubbing facility fully operational in early 2021;
New partner services fully integrated into Qrator Labs infrastructure and customer dashboard throughout 2020: SolidWall WAF and RuGeeks CDN;
Upgraded filtering logic allows Qrator Labs to serve even bigger infrastructures with full-scale cybersecurity protection and DDoS attacks mitigation;
The newest AMD processors are now widely used by Qrator Labs in packet processing.
DDoS attacks were on the rise during 2020, with the most relentless attacks described as short and overwhelmingly intensive.
However, BGP incidents were an area where it was evident that some change was and still is needed, as there was a significant amount of devastating hijacks and route leaks.
In 2020, we began providing our services in Singapore under a new partnership and opened a new scrubbing center in Dubai, where our fully functioning branch is staffed by the best professionals to serve local customers.
Users sometimes ask how new diagnostics appear in the PVS-Studio static analyzer. We answer that we draw inspiration from a variety of sources: books, coding standards, our own mistakes, our users' emails, and others. Recently we came up with an interesting idea of a new diagnostic. Today we decided to tell the story of how it happened.