SAN FRANCISCO, Oct. 15, 2020 /PRNewswire/ -- Splice Machine, the only scale-out SQL database with built-in machine learning, today announced the launch of 'ML Minutes,' a new podcast designed to democratize machine learning and make it more exciting to a broader audience. Hosted by Splice Machine co-founder and CEO, Monte Zweben, every 15-minute episode feels like a conversation with a friend, except each friend is a cutting-edge ML researcher or practitioner.
"There is a huge disparity in technological literacy in the US," said Zweben. "There are many long-form podcasts out there that wax poetic about the exciting details of machine learning and AI, and there is a distinct audience that enjoys and benefits from this format. But there is a much broader audience out there that desires knowledge about how ML can benefit society. We want to reach this audience, and help overcome 'terminator-itis', or the misconception that AI is going to take over the world and "destroy humans."
In every episode, guests have only one minute to answer each question. The show generally follows the path of: tell us about yourself, what's the problem you're solving, why does it matter, how are you studying it, what challenges have you faced, how have you overcome them, and what's next. Additional bonus questions vary depending on the guest, and allow the speaker to go deeper into topics of interest.
The first three episodes will go live today and include interviews with:
Tom Mitchell – Tom Mitchell is a university professor at Carnegie Mellon and a legend in Machine Learning. Mitchell founded the world's first Machine Learning Department at Carnegie Mellon University's School of Computer Science in 2006, and led it as Department Head for its first 10 years. Tom's research bridges Machine Learning, AI, and Cognitive Neuroscience to explore some of the most interesting and groundbreaking questions of our time. In his episode, Mitchell will break down how ML is helping humans understand the processing of language in the brain.
Krishna Rao – Krishna Rao is an Earth scientist currently pursuing his PhD at Stanford University. In his research, Krishna develops technologies that measure forest health using remote sensing and machine learning. In his episode, Krishna will discuss how machine learning can help prevent California forest fires – a topic that couldn't be more timely!
Manuela Veloso – Dr. Manuela Veloso joined J.P. Morgan in July 2018 to create and head their AI Research Lab. Currently on leave from Carnegie Mellon University, where she is the prestigious Herb Simon University Professor in the School of Computer Science, Manuela founded the CORAL research laboratory, for the study of autonomous agents that Collaborate, Observe, Reason, Act, and Learn. Her research includes major works on autonomous robots, Artificial Intelligence, and Machine Learning. In her episode, Dr. Veloso will discuss the role of AI in the world of finance.
"What I want people to understand is that AI is a tool – not a terminator! Whether it's used for good or bad depends on what we use it for," said Oren Etzioni, CEO of the Allen Institute for AI. "Many people are susceptible to misinformation about machine learning. I love what Monte is trying to do with ML Minutes – recognizing the amazing work ML practitioners and researchers are doing to benefit society, and presenting it in a format that is genuinely engaging and fun for both the listener and the guest."
"I'm excited to be a part of this new endeavor," said Tom Mitchell, Professor of Machine Learning at Carnegie Mellon University. "It's not easy to present machine learning in a way that's both accessible and accurate, but Monte's the rare person who can do both. It was a real pleasure to participate -- and fun to come up with 60-second answers to each question. I'm looking forward to seeing where this goes!"
ML Minutes is now available wherever you get your podcasts (Spotify, Apple, Google, Stitcher, Overcast, Amazon, and more). For more information on the podcast and a calendar of upcoming guests, visit mlminutes.com.
About Splice Machine
Splice Machine is the only scale-out SQL database with built-in machine learning. Splice Machine slashes software, infrastructure and people costs by combining operational workloads (OLTP), analytical workloads (OLAP), and machine learning (MLOps) into one seamless Kubernetes-powered architecture. Enterprises build new intelligent applications on the Splice Machine RDBMS, extend existing applications with AI, and modernize their applications in the cloud with virtually no rewrites. Companies can offload data from more expensive RDBMS systems easily and get the most efficient path to operational AI. Splice Machine is available as a fully-managed cloud service on AWS, Azure, and GCP and is also available on-premise. Learn more at www.splicemachine.com.
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