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Enterprise policies are different, and in some cases weird. In this article, we will describe a very unusual problem raised by one of our customers. In a nutshell, the organization does not allow bringing any devices onsite, no smartphones, no mobile phones, and even no hardware tokens are allowed on-premises. At the same time, the organization is using Office 365 services from Microsoft and has enforced multi-factor authentication for all users to be activated.

To address this issue, our research and development team has spent some time and found a solution, which is a paper-based TOTP token. We are hereby presenting the solution, which is available for free (well, if you don't count the paper and ink cost).

Our solution is a web-based tool that generates the list of one-time passwords (OTPs) for an arbitrary seed. The list can be printed out and handed over to the end-users to serve as their second factor for authenticating in Azure AD with multi-factor authentication enabled. To associate this paper TOTP token with a user, you can follow the same procedure as with the regular TOTP tokens.

The procedure is simple, you enter the seed and click on submit to get the list generated. You will get a printable list similar to the one shown below for the next few days. By changing the number of future OTPs you can make the list longer or shorter.

This article could have been born about a year ago – that's when the PVS-Studio team decided to try agile. However, we wanted to experience it hands-on before we told the world about it. Aside from introducing agile, we decided to switch from Bitbucket to a new task tracker. We also wanted to upgrade many of our internal development processes. No time for an article!

Looking out for the best in app chat solution providers to enhance your business.

Getting confused with so many options to choose among  Sendbird and Twilio competitors. 

Then, let’s have some clarity with a detailed discussion over the feature comparison to go for the best Twilio and Sendbird alternative.

There is a lot of commotion in text-to-speech now. There is a great variety of toolkits, a plethora of commercial APIs from GAFA companies (based both on new and older technologies). There are also a lot of Silicon Valley startups trying to ship products akin to "deep fakes" in speech.

But despite all this ruckus we have not yet seen open solutions that would fulfill all of these criteria:

• Naturally sounding speech;
• A large library of voices in many languages;
• Support for 16kHz and 8kHz out of the box;
• No GPUs / ML engineering team / training required;
• Unique voices not infringing upon third-party licenses;
• High throughput on slow hardware. Decent performance on one CPU thread;
• Minimalism and lack of dependencies. One-line usage, no builds or coding in C++ required;
• Positioned as a solution, not yet another toolkit / compilation of models developed by other people;
• Not affiliated by any means with ecosystems of Google / Yandex / Sberbank;

We decided to share our open non-commercial solution that fits all of these criteria with the community. Since we have published the whole pipeline we do not focus much on cherry picked examples and we encourage you to visit our project GitHub repo to test our TTS for yourself.

Building console application can produce an unexpectedly much larger file than you would think due to implicit references.

What is the problem and how it can be solved?

Content marketing is an endless endurance race. You can’t put a cap on business growth, even if you’re a tech industry giant. A single success is not enough — every time you reach the finish line, it moves further away. Retaining your existing customers is no walk in the park either. When you go silent, you are actively ignoring your audience. There’s no way around it — you need to pump out content.

However, doing that day in and day out requires a lot of stamina. So let’s look at why we get tired in the first place, and figure out how to avoid it. [Previous article: The true cost of free labour].

At the very beginning of this year, Apple released the source code for macOS – Big Sur. It includes XNU, the kernel of the macOS operating system. A few years ago, PVS-Studio has already checked the kernel source code. It coincided with the analyzer release on macOS. It's been a while since then. The new kernel source code has been released. A second check? Why not?

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.