Decentralised streaming platform for eSports fans and gamers, Play2Live has today announced the introduction of interactive tasks for streamers, which will be set by viewers of the platform. Viewers will be able to set tasks for streamers choosing different conditions, whilst utilising an advanced task manager. By introducing interactive tasks, Play2Live presents a new level of interaction between platform users and helps to establish the LUC (Level Up Coin) token economy – the sole mean of payment within the platform.
Implementing algorithms for real-time monitoring of video streaming, recognition of complex objects and video content all based on a neural network, viewers can set the price for their favourite streamer to perform a specific task. Tasks can include challenging the streamer to complete the game on the hardest difficulty level, or to use a specific weapon, equipment or skills within given period on a specific location, keep streaming for three hours straight or to start a stream on a different game, etc.
Tasks are voted on using LUC tokens and any other user can support the tasks with further LUC tokens, or by assigning a streamer their own tasks. The streamer can then decide to perform one, or all tasks being set and this will determine the number of LUC tokens they shall receive – In case of failure all tokens are returned to the viewers.
The use of a neural network will help to determine whether a task was accomplished by the streamer or not. The network will monitor the stream and with the highest precision decide if the task was accomplished. The task itself is formed as a smart contract with a deposit in LUC tokens, which is an analogue of the escrow function, with a deposit being made in LUC for the time the task is performed by the streamer. Most actively involved users will also receive rewards in LUC. This allows for gamification of the entire platform; the more actively users participate in various activities, the more tokens they earn.
Alexey Burdyko, CEO and founder at Play2Live said:
Play2Live facilitates numerous ways of interaction between a streamer and a viewer including a bilateral system of tasks, enhanced content generation process and many others. Compared to the simplistic chat communication and donation options provided by the existing platforms, it is a real step forward in terms of interaction. We use Computer Vision algorithm to analyse streaming videos. These are neural networks, trained for recognition on their own datasets, including Time Series and OCR, and HUD of games. We performed global optimization of algorithms to fasten system operation time. This will allow launching the analysis of the stream even on the equipment without GPU. In future, this will also allow to perform analysis on tape drive equipment, rather than on Play2Live servers, and transmit along with the video stream meta information with results of the analysis. We are pretty sure that implementation of such functionality will help to change the pattern of watching this kind of content forever.
Vladislav Arbatov, CTO at Play2Live, has been responsible for training the neural network. Arbatov continued:
Interactive tasks will be developed for each popular game, and by the end of the year such functionality will be available for more than 300 games. The internal system of the neural network training will allow to add new types of events as quickly as possible. We also plan to work closely with the user community – we will ask fans what tasks would be the most interesting for the particular game.
Play2Live aims to combine blockchain technology with its streaming services, whilst offering 15 sources of revenue for participants – three times more compared to the streaming industry leaders. Streamers will be able to monetize their content in 11 ways versus the 4-5 available on existing platforms.