Three startups compete for Swiss BIC of CERN’s prize

The Swiss BIC of Cern is a startup competition providing high-tech startups access to accelerator technology expertise and encourage the industry to use the solutions developed at research centers such as CERN and the Paul Scherrer Institute (PSI) in Switzerland.

CERN and PARK INNOVAARE have nominated three Swiss startups to proceed to Phase II for the fourth edition of the program. The startups were selected to proceed based on their IP requirements and market potential, which were evaluated in Phase I. During the next stage (six weeks), the teams will draft a comprehensive business plan to pitch to an independent Selection Committee. The most outstanding solution will receive CHF 50’000 Seed Money, access to CERN’s IP and know-how, further business and technical support from FHNW and PSI and membership at PARK INNOVAARE, Villigen.

The following startups are competing for the prize:

condenZero | Denys Sutter & Dominik Biscette (Rechsteiner) and Johan Chang
CondenZero develops and manufactures a cryogenic sample holder for cryo-EM. The product is based on a novel proprietary cooling technology that can cool down samples in less than ten minutes and sustains the base temperature for over 24 hours. This allows researchers who rely on cold temperatures to work more efficiently and effectively: They avoid waiting time and costs for cool-down cycles and gain the time needed to conduct scientific work properly. Over a thousand research centers are conducting experiments using cryo-electron microscopy, opening a market estimated at USD 5 billion for condenZero.

Hoursec Energy Efficient Computation | Alexandra Pinto and Edoardo Charbon
Founded in 2020, Hoursec aims to reduce three thousand percent the energy requirements for Deep Neural Network models training and inference requirements. This guarantees the reduction in data storage and movement for data analysis. Thanks to Synaptic functioning, the startup is able to MAXIMIZE the ratio of information transmitted per epoch. With its theoretical re-thinking for an Optimal Algorithmic Design Tool, the company has a granular approach to Complex Systems. It also has the Datacenter approach in the sense of blending Optimization and Analytics. The main application is in Machine Learning at the Edge, where low power solutions are necessary.

Lumiphase| Lukas Czornomaz, Stefan Abel and Jean Fompeyrine
Lumiphase develops novel optical communication chips that are very inexpensive, super compact and highly efficient. They allow the industry to replace today’s costly and power-hungry connections with a new generation of electro-optical links, ultimately enabling a new paradigm in datacenters‘ architecture and leading to more flexible, efficient and sustainable use of computing resources.

 (RAN)