Gridcoin has just had a successful protocol update to version 5! Before version 5, it was mandatory for a cruncher to switch to the team Gridcoin, in order to be rewarded with this cryptocurrency.

From now on, any BOINC cruncher, regardless of team, can earn Gridcoin for their work. 
Solo cruncher must send a new beacon within the next 2 weeks to not lose any past unclaimed rewards.

The BOINC community is about 10 times the Gridcoin community. It is believed that the removal of the Team Requirement should spark interest among BOINC crunchers for Gridcoin.

We built the kit of Prusa model i3 MK3s in about 12 hours, which is currently the best 3D printer available on the market.

The kit is ideal for learning how a 3D printer works. Josef Prusa modified the original Open Source RepRap design (Replicating Rapid Prototyper) where the plastic pieces of the 3D printer to be built are printed by another 3D printer. At time of writing Prusa Research has supplied 130'000 printers worldwide and owns a printing farm with 1'000 3D printers.

Hydrique is the leading provider of hydrological forecasts in Switzerland and abroad. deep space computing will provide hardware consultancy and help Hydrique to enhance existing and proprietary Deep Learning algorithms, so that they run on graphic cards. 

As of this morning, the best resources of our Computational Cluster are dedicated to the projects Folding@home and Gene@home (through TN-Grid in BOINC), that directly look at how COVID19 interacts with the human ACE2 receptor. Rosetta@home and GPUGRID also partially look at COVID19 and there we already have a multi-year contribution. deep space computing also supports several other projects fighting common diseases with its CUDA Supercomputers. Our computational cluster was mainly built with recycled computers supercharged by graphic cards bought second hand.

 

 

 

Deep Space will open the Asset Optimization Day 2019 in Bern with an introductory talk on Deep Learning on Friday, December 6. The full program of the conference is here. You can download the presentation in German "Einführung ins Deep Learning" here.