AI has become deeply ingrained in the everyday life. The matter in question does not only touch upon the mobile phones that almost everyone carries within easy reach. Today, voice assistants and smart speakers are mainly used to turn on music, turn off the lights or forecast the weather. AI chatbots are getting smarter. The use of new technologies and the general development of neural networks makes it possible to chat or answer questions, write a script, a scientific work, or program code. One of the key differences from previous GPTs is that the new version is trained to continue the text and answer questions. The answers that the bot gives surprise users around the world. Yes, there are still questions about these answers and their validity, and everyone is sure that technology needs to be improved. For a technology to become revolutionary, it must find a better, new, breakthrough application. Although no, such an application has already been invented. Farcana decided to combine the functionality of the GPT chatbot and a voice assistant. By offering players a new approach to familiarizing themselves with game mechanics and general account management, Farcana promotes its advantages over others and rapidly contributes to AI's overall development in the digital society.

Regaining lost abilities via the formation of new neural pathways as a result of extensive practice and retraining is a key feature of the rehabilitation process. However, patient boredom is a big issue in rehabilitation owing to the extensive practice that is necessary. Awareness of the value of haptic (touch-enabled) interfaces in computer applications has grown because to the emergence of games with buzzing joysticks and consumer electronics with touchpads. Some forms of haptics, however, are paving the way for cutting-edge computer-based rehabilitation solutions, such as "serious games," which are only one use of haptics' potential to enhance clinical treatment. In this paper, we aim to review the methods and technologies of haptic feedback that are used for medical treatment and rehabilitation. Developing and innovating better haptic feedback technology has the potential to expand and improve access to virtual healthcare such as the doctor being able to "feel" a patient's tumor from miles away by being paired with robotic devices.

Despite the fact that their neurobiological processes and clinical criteria are well-established, early identification remains a significant hurdle to effective, disease-modifying therapy and prolonged life quality. Gaming on computers, gaming consoles, and mobile devices has become a popular pastime and provides valuable data from several sources. High-resolution data generated when users play commercial digital games includes information on play frequency as well as performance data that reflects low-level cognitive and motor processes. In this paper, we review some methods present in the literature that is used for identification of digital biomarkers for Parkinson's disease. We also present a machine learning method for early identification of problematic digital biomarkers for Parkinson's disease based on tapping activity from Farcana-Mini players. However, more data is required to reach a complete evaluation of this method. This data is being collected, with their consent, from players who play Farcana-Mini. Data analysis and a full assessment of this method will be presented in future work.

The Highlights are the most interesting, selling moments from video stream, which can make the viewer watch the entire video. They are like a shop window: everything that is bright and colorful goes there. Seeing them, the user can understand in advance what is inside the video. And they are more versatile than trailers: they can be made shorter or longer, embedded in different places in the user interface. The user sees a selection of highlights as soon as he gets to the website or watches a video clip on YouTube or even a section of a stream of a popular blogger/influencer. The user's attention is immediately attracted by the most memorable shots. Naturally, it is becoming more tedious to manually create all video highlights, due to the immense amount of material that the highlights are needed for. Thus, creating an algorithm, capable of automating the process would make the process significantly simpler. Besides easing up the work, this process will pave the way to a whole set of new applications that before did not seem real. At the same time, this would be a new process where the AI would not need to be fully supervised by a human, but be capable of identifying and labeling the most interesting and attractive moments on screen. After doing a literature review on video highlight detection, this paper has utilized the model presented in the study by [1] to determine the possibility of attaining highlights from the Farcana 2.0 version Twitch video feed.

BCI as a technology has been developing relatively quickly in the past several decades. Numerous gadgets and devices have been presented on the market. Yet, if most of them are related to medicine and partly education, there are not as many which have to do with ultimate gaming. Of course, wearable devices constitute the sphere of medical data acquisition. However, none of them have to do with gaming education and training. This paper presents an overview of the existing BCI models focused on gaming. It suggests an experimental system justifying its necessity in the impact it would have on the gaming world. The utilization of BCI capabilities in developing a relatively new direction can change the sphere of gaming training altogether.