The new version of Bittorrent 4.2.0 arrives and these are its novelties

Among the best known ways to share files on the network is the P2P where Torrent is one of the most representative of it. Although listening to the word Torrent is usually associated with piracy and material that infringes copyrights, this way of sharing files on the network is not entirely illegal since many contributions that are free of distribution are also hung, as well as for example, many of the Linux distributions are usually distributed by this means.

As many of you will know, in order to download what a Torrent file contains you have to use a client for it, which among the most popular we can find qBittorrent. This is a cross-platform, free and open source P2P client for the BitTorrent network.

The program uses the libtorrent-rasterbar library for network communication. Bittorrent is written in the C ++ programming language (using the Boost libraries) because it is a native application; It also uses the Qt library.

Its optional search engine is written in the Python programming language, however, if the user is not willing to install Python, he can choose not to use the search function.

This is developed as an open alternative to µTorrent, since it is similar in terms of interface and functionality.

Among the main features of qBittorrent we can find: the integrated search engine, the ability to subscribe to RSS, support for many BEP extensions, remote control through the web interface, sequential download mode in the specified order, advanced settings for torrents , pairs and trackers, bandwidth programmer and IP filter, interface to create torrents, support for UPnP and NAT-PMP.

About the new version of qBittorrent 4.2.0

A few days ago the launch of the new version of qBittorrent 4.2.0 was announced. Version in which we can find a handful of new features and especially improvements and bug fixes around its previous version.

 Among the improvements that are highlighted in the announcement of this new version of qBittorrent 4.2.0, we can find the following:

1. For hash passwords for screen lock and access to the web interface, the PBKDF2 algorithm is used.
2. Conversion of icons to SVG format completed.
3. The ability to change the interface style using QSS style sheets was added.
4. Added dialog "Tracker entries".
5. On the first start, a random port number is provided.
6. The transition to Super Seeding mode was implemented after the time limit and traffic intensity were exhausted.
7. Improved implementation of the built-in tracker, which now best meets the BEP (BitTorrent Improvement Proposal) specifications.
8. Added option to align the file to the edge of the block when creating a new torrent.
9. Added support to open a file or call a torrent by pressing Enter.
10. The ability to remove torrent and related files after the specified limit has been exhausted has been added.
11. You can now select several items at once in a dialog box with a list of blocked IPs.
12. The possibilities of pausing torrent verification and forcing a call to retest completely failed torrents that have not started are returned.
13. Preview command of the double-click file added.
14. Added support for libtorrent 1.2.x and stopped working with versions earlier than 1.1.10.

How to install qBittorrent on Linux?

For those interested in being able to install this new version of qbittorrent 4.2.0 in their Linux distribution, they can do so by typing the commands we share below.

For those who are Ubuntu users, Linux Mint or any other Ubuntu-based distribution should add the following repository. To do this, they must open a terminal and type in the following:

sudo add-apt-repository ppa:qbittorrent-team/qbittorrent-stable -y
sudo apt-get update && sudo apt-get install qbittorrent

While for those who are users of Arch Linux or any other derivative thereof, they install the new version by typing the following:

sudo pacman -Sy qbittorrent

 Those who are Fedora users:

sudo dnf install qbittorrent

OpenSUSE users:

sudo zipper in qbittorrent

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Masakhane, an open source project that allows automatic translation of more than 2000 African languages

When we usually hear about open source projects in most cases, programs or utilities come to mind for everyday work purposes. Although this is not the case as such, since open source covers many more areas.

One of them is artificial intelligence that is currently growing in an incredible exponential manner, although some years ago it was believed that it would be something that would develop well many years later.

Artificial intelligence (AI) is currently used for various cases, of which the most popular are for the detection of objects, people, patterns among other things. It is also used within translators of which many of them are patented by companies.

But in this case we will talk about an open source project which has aroused the interest of many as it is developed to cover a great need in the African territory, which is communication since it is currently estimated that in Africa there are around 2000 languages

Masakhane a project that must be fulfilled for a common good

The project we will talk about is "Masakhane" which is a project that was founded by South African AI researchers Jade Abbott and Laura Martinus and the project is collaborating with AI researchers and data scientists from all over Africa.

When they met at a conference related to machine learning and natural language processing (NLP) this year, they talked about a project to translate African languages ​​into machine learning models and started Masakhane. The name of the project "Masakhane" is a word that means "to do together" in Zulu.

Languages ​​that allow automatic translation in Masakhane include not only native African languages, but also the Nigerian Pidgin dialect in English and Arabic spoken in North and Central Africa. Unlike European languages, these languages ​​have no specific benchmarks or large data sets.

In addition to the importance of giving Africans several opportunities, the benefits of developers participating in Masakhane are listed as "The success of the African AI projects is an African AI researcher." It could lead to relaxed restrictions. ”

Currently in Masakhane it has about 60 developers in Africa (South Africa, Kenya and Nigeria) of which each participant collects data in their native language and trains the model.

In Kenya, English is often used in schools and other public places, but in everyday life different languages ​​are used for each tribe, so Siminyu felt there was a communication gap. It was. Therefore, AI developer Siminyu decided to join Masakhane.

Siminyu believes that translating African languages ​​through machine learning will lead to growth in the use of AI in Africa, which will help people in Africa use AI in their lives. Siminyu argues that projects across the continent, such as Masakhane, are important to connect African developers and research communities and achieve long-term and sustainable collaboration.

“Language differences are a barrier, and eliminating the language barrier will allow many Africans to participate in the digital economy and, ultimately, in the AI economy. "I feel it is the responsibility of those who participate in Masakhane to get people who are not involved in AI society," said Siminyu.

Masakhane's attendees say that the developer community in Africa is expanding rapidly and that the benefits of machine translation for African languages are significant.

“We can solve the problem. We have experts, we have knowledge and intelligence ... I think they will become a foothold to contribute to the world. An African developer says.

Finally, if you want to know more about the project, you can check the details on their official website. The link is this.

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