Today, Yandex has announced a collaboration with CERN, the European Organization for Nuclear Research, in which Russia’s leading search company will provide its computing resources and data processing technologies, including MatrixNet, to CERN researchers. In return, Yandex gets wide access to extremely large-scale experiment datasets that will help improve its proprietary machine learning technology, MatrixNet, and ultimately its search results.
Today’s announcement takes the collaboration, which began in April 2011 when CERN started using Yandex’s servers for some of its data simulation, to the next level. While MatrixNet is already being tested on one of seven experiments currently running at the Large Hadron Collider – the world’s largest particle accelerator – a more user-friendly service to help scientists leverage the technology without assistance from Yandex specialists is currently in the makings.
Set for launch in May this year, this customised version will help physicists at CERN to better deal with inhumanly large amounts of data (10bn particle events per year has been detected since the first protons were fired through the LHC in 2008). As Andrey Golutvin of CERN says:
Today’s physics deals with large datasets that need to be properly processed and interpreted. New discoveries are all but impossible without meticulous data analysis.
Specifically, the use of MatrixNet could enable scientists to detect very rare events which wouldn’t otherwise have been detected. It will most likely also allow for detecting these events at much greater precision, meaning that hypotheses and theories can more accurately be confirmed or refuted.
A key feature of MatrixNet, which Yandex launched in 2009, is its ability to take into account a vast number of factors without relying on a particularly large sample size to achieve high relevancy or confidence levels – an important feature when trying to identify consistency of extremely rare event instances.
Yandex has been open to contribute to more experiments since the initial launch of its custom-built search tool for event detection at CERN in April 2012, and with today’s announcement it appears that its machine learning technology will become a more integral part of data analysis processes at the biggest particle physics laboratory in the world. However, while dealing with these vast datasets is said to improve the technology of MatrixNet, it remains unknown how big an impact it could have on search quality going forward.
Immanuel Simonsen
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