Monte Zweben proposes a whole new approach to MLOps that allows to scale models without increasing latency by merging a database, a feature store, and machine learning.
/PRNewswire/ Splice Machine, a real-time machine learning and AI solutions provider, today announced the release of Livewire Pulsar, the latest edition of.
How feature stores can reduce the ‘Groundhog Day’ effect for data scientists
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Splice Machine’s Monte Zweben explains how feature stores can help cut down the monotonous parts of a data scientist’s job.
Many people pursue a career in data science because they love solving problems. But something called the Groundhog Day effect can limit that, according to Monte Zweben, CEO of real-time AI company Splice Machine.
Zweben, who previously worked as the deputy chief of AI at NASA’s Ames Research Center and sits on the advisory board for Carnegie Mellon University’s School of Computer Science, believes feature stores can help.
Location: Grand Rapids, MI
Tim Heger is the CSO/CISO at HealthBridge
, a first-of-its-kind employee financial security solution that provides a financial resource to help bridge the gap between the high cost of healthcare and an employee’s financial wellbeing.
Heger
has spent the last 20 years focused on emerging technologies and helping global companies scale to meet the demands of a consumer-centric digital ecosystem.
What was your first job? I was the French fry cook at our local A&W for $1.10 per hour. Coney dogs, fries and root beer would be my diet for several summers.
How did you get involved in cybersecurity? I’ve been involved with the internet/eCom/security for a long time. Prior to joining HealthBridge I spent many years in the eCom world where security and privacy has some of its roots. The move to the cloud greatly accelerated my focus on security, since as we all know, the “cloud” just means someone else’s data centre that you don’t have any vi
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Machine learning (ML) seems to work so well for big tech companies while so many businesses outside of Silicon Valley have yet to fully implement ML to its fullest. I recently visited with Monte Zweben, CEO of Splice Machine, creator of an ML engine that creates, deploys, and manages ML models, and I asked him why.