DeepBrain Chain, a decentralized AI computing platform has published the 37th issue of its progress report series, outlining progress in the areas of technical, community, and business development.

DBC beta

DeepBrain Chain detailed the release of DBC beta of its AI Training Net, which allows users to rent computing power to train artificial intelligence algorithms.

DeepBrain Chain claimed numerous feature inclusions and and improvements, many pertaining to the scheduling and activation of tasks. In DBC, if an AI training task has been stopped a specified period of time, its storage will be deleted automatically. However, the task can be restarted at any time before deletion. If a node has been restarted, reactivation of any previous training tasks will require manual user authorization.

Node support was also extended to include Jupyter notebook, an open source tool that integrates code and its output into a single document that combines visualizations, narrative text, mathematical equations, and other rich media.

The team also claims to have “fixed bugs that stalled training and optimized user experience.”

An update was made that divides GPUs into separate containers. The result is that multiple users can use the same node simultaneously, which increases the network’s scale and throughput.

DeepBrain Chain Closed Strategic Discussion Group

In addition, the report highlighted a closed strategic discussion group created to assist DeepBrain Chain in its decision making through “feedback and consensus.” So far, the group is claimed to have over 50 members “that have the best interests of DBC in mind.”

Part of the group’s focus is to establish a cooperative community of developers, investors, and users in regards to the governance of the DeepBrain Chain ecosystem. It’s envisioned that community goals will be discussed by the group before the official governance model of the platform is decided on.

Current discussion points are said to be:

  • AI training net and website dashboard
  • Token swap plans and details
  • Staking/Masternodes and chain details
  • Token usage and voting rights of community
  • Open sourcing/GitHub and code

A decision was made recently by the community concerning the open source licensing of DeepBrain Chain’s code. Over 55 percent of the members polled voted to not make the code fully open source by the end of March.

Individuals can participate in DeepBrain Chain’s closed strategic discussion group by joining its Telegram channel and asking admins about requirements of entry.

Business Development

DeepBrain Chain also updated its community on its activity in sales and business development for use of its AI training net and distributed computing power. Progress was reported as follows:

  • Opened discussions with Tmxmall, a translation memory management and sharing company
  • Drafted a contract with Yulan Technology Co, a manufacturer of intelligent driving products, car networking, and car wireless charging
  • Drafted a “comprehensive solution” for an AI tech park in the Chongqing municipality in southwestern China
  • Started a strategic collaboration with the Sichuan University of Science & Engineering. The collaboration will reportedly focus on AI training and introducing students to the potential of DeepBrain Chain’s computing power
  • Followed up on an “AI smart solution” involving the companies China Coal Technology Engineering Group and Sanyou medcial device quality control – in a joint collaboration with a company named VNX

Signing off on the report, DeepBrain stated that it is in the progress of updating its website and apologized for any inconvenience. Some website users may experience “incorrect user info or no info at all.” The team stated that they are aware of these bugs and will fix them as soon as possible.

The full report can be found at the link below: