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The University of California, Berkeley in November wrapped up the AMPLab, a five-year computer science research lab that produced, among other things, the Apache Mesos cluster management software and the Apache Spark data processing engine. Today the university is announcing what comes next: RISELab.

The new five-year initiative has financial backing from Amazon Web Services (AWS), Ant Financial, Capital One, Ericsson, GE Digital, Google, Huawei, Intel, IBM, Microsoft, and VMware.

AMPLab figures Ken Goldberg, Michael Jordan, Randy Katz, Michael Mahoney, David Patterson, and Ion Stoica are sticking around for the new program, alongside new participants like Databricks cofounder and chief executive Ali Ghodsi and Trifacta cofounder and chief strategy officer Joe Hellerstein. But the new organization has a new focus.

“Like much of the big data movement, the AMPLab focused mostly on offline data analysis problems, where minutes and hours could be devoted to extracting value from data. By contrast, the RISELab researchers are looking to make real-time decisions in milliseconds,” the team said in a statement.


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RISELab already has a slew of projects listed on its website. Among them are a tool called Allegro that rewrites queries in order to bring back differentially private results and a modeling framework called Paris that’s meant to figure out performance of workloads using different types of virtual machines (VMs) in public clouds.

Like MIT and Stanford, Berkeley has played a role in the history of computing. Berkeley RISC, the Berkeley Software Distribution (BSD), and RAID have come out of it — during previous five-year labs — not to mention graduates like Eric Schmidt and Steve Wozniak.

“The difference between traditional labs elsewhere and Berkeley’s labs is that at Berkeley each lab has a well-defined vision and goals. The five-year duration provides a natural deadline to measure whether the lab has successfully delivered on its goals,” Stoica told VentureBeat in an email.

“For example, the vision of AMPLab was to ‘make sense of the big data’, and the goal was to build ‘the next generation of open-source data analytics stack to be used across industry and academia’. Similarly the vision of RISELab is to enable ‘intelligent real-time decisions with strong security’, and the goal is to develop ‘platforms, tools, and algorithms to support applications that require intelligent real-time decisions on live data with strong security.'”

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