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Podcast

Taking Machine Learning on the Road with IBM and B-Plus

Development of autonomous vehicles is an excellent example of machine learning applied to industrial IoT

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Podcast

How AI Drives the Need for Next-Generation Infrastructure Architectures with Liqid

We are on the cusp of a totally new architecture for enterprise IT, and this change toward composability is being driven by applications like AI

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Podcast

Optimizing ML at the Edge for Industrial IoT with Sastry Malladi of FogHorn

Industrial cameras and sensors are generating more data than ever, and companies are increasingly moving machine learning to the edge to meet it

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Podcast

Enabling AI Applications through Datacenter Connectivity with Nvidia

AI applications typically require massive volumes of data and multiple devices within the datacenter

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Podcast

Using ML to Optimize ML with Luis Ceze of OctoML

Training and optimizing a machine learning model takes a lot of compute resources, but what if we used ML to optimize ML? Luis Ceze created Apache Tensor Virtual Machine (TVM) to optimize ML models and has now founded a company, OctoML, to leverage this technology

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Podcast

AI Needs Non-Traditional Storage Solutions with James Coomer of DDN

AI applications have large data volumes with lots of clients and conventional storage systems aren’t a good fit

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Podcast

Balancing Data Security and Data Processing with Arti Raman of Titaniam

AI and analytics needs access to massive volumes of data, but we are constantly reminded of the importance of securing data

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Podcast

Using AI to Assess Unstructured Data with Concentric

Most organizations have a vast amount of so-called unstructured data, and this poses a major risk for operations

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Podcast

AI and Analytics Are Driving a New Kind of Storage with Brad King of Scality

Big data really wasn’t all that big until modern analytics and machine learning applications appeared, but now storage solutions have to scale capacity and performance like never before

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Podcast

Building Transparency and Fighting Bias in AI with Ayodele Odubela

When it comes to AI, it’s garbage in, garbage out: A model is only as good as the data used