The New Stack Makers

Episode 319: Neo4j’s Emil Eifrem on Graph Databases, Machine Learning, and More

July 18th, 2018  |  28 mins 33 secs

ai, artificial intelligence, big data, data, databases, graph databases, graphdb, machine learning, neo4j

When it comes to machine learning and GraphDB, “We’re in the first inning of a nine-inning game,” said Emil Eifrem, CEO and founder of Neo4j.  “If you look at machine learning algorithms, they are written in graph language, or can be expressed in graph language.”

Episode 315: Paperspace Co-Founders Discuss TPUs and Cloud Deep Learning

July 10th, 2018  |  18 mins 20 secs

ai, artificial intelligence, deep learning, gpu, machine learning, paperspace, tensorflow, tensorflow processing units, tpus

It's a crowded market if you're a machine learning company. Every vendor under the sun has integrated some new-fangled AI-driven service, making the real ROI tough to spot in the jungle of buzzwords and feature creep. Paperspace is hoping to make that journey a little easier for businesses by offering Gradient, an easily manageable infrastructure platform for deep learning.

Episode 303: KubeFlow: Manage AI Workflows With Kubernetes

June 14th, 2018  |  19 mins 56 secs

ai, artificial intelligence, google, kubecon, kubecon + cloudnativecon, kubecon eu, kubeflow, kubernetes, machine learning, mesosphere

Artificial intelligence may be at the peak of its hype cycle for modern businesses, but for the IT administrator it is still a headache, requiring software and processes that may entirely outside the normal sphere of operations. But help is on the way. At Kubecon + CloudNativeCon 2018 last month, David Aronchick introduced the first working version (0.1) of Kubeflow, software that packages the most popular AI and machine learning software so it can be easily run on the Kubernetes container orchestration engine.

Episode 271: Univa's Project Tortuga and the Intersections of Kubernetes and HPC Workloads

April 9th, 2018  |  17 mins 2 secs

cloud management, deep learning, hpc, kubernetes, machine learning, navops, open source, open source software, osls, univa corporation

Rob Lalonde is vice president and general manager for Navops at the Univa Corporation. Rob and TNS Founder Alex Williams had a conversation at the Open Source Leadership conference in Sonoma, Ca. We talked quite a bit about Project Tortuga, which Susan Hall, writing for The New Stack, explained this way:

It’s a general-purpose cluster- and cloud-management framework with applications including high-performance computing (HPC), Big Data frameworks, Kubernetes and scale-out machine learning/deep learning environments.

Episode 257: The Future Of Machine Learning

February 28th, 2018  |  14 mins 4 secs

api, apis, artificial intelligence, big data, databricks, machine learning

Ali Ghodsi, CEO & CO-Founder at Databricks, has been a major influence in three big open source projects – Apache Mesos, Apache Spark and Apace Hadoop. What’s interesting about all of these three projects is that there are very successful companies around these projects. We sat down with Ghodsi to talk about these Open Source projects and machine learning.

Episode 221: Evolution Of OpenStack: Radhesh Balakrishnan

December 13th, 2017  |  20 mins 6 secs

machine learning, network functions virtualization, openstack, openstack summit sydney 2017, red hat, the new stack makers

Red Hat is one of the early backers of the OpenStack cloud and also the largest contributor to the project. They have been part of OpenStacks’ overall evolution. During the OpenStack Summit Sydney, Australia, we talked to Radhesh Balakrishnan, General Manager for OpenStack at Red Hat to understand this evolution.

Episode 219: Open Source Is The Best Insurance For The Future: Eddie Satterly Talks About IAG

December 4th, 2017  |  27 mins 58 secs

iag, machine learning, open source, openstack, openstack summit sydney 2017

IAG or Insurance Australia Group is one of the largest insurance companies in Australia. IAG has been around for more than 160 years, they obviously have a huge stack of legacy applications and infrastructure. There are over 147 core insurance systems running within the IAG group. The majority of those are mid-range mainframe systems like AS/400.

Episode 217: Joseph Sirosh Of Microsoft: How AI Can Help The Blind See

November 27th, 2017  |  20 mins 13 secs

ai, artificial intelligence, cognitive services, developers, devops, disabilities, machine learning, microsoft

Microsoft is one of the few companies who owns massive machine learning and Artificial Intelligence platforms. Microsoft is now making it easier for its customers and to leverage its AI capabilities.

At Microsoft Connect, we sat down with Joseph Sirosh, Corporate Vice President of Microsoft’s Cloud AI Platform to learn more about Microsoft’s AI technologies, including machine learning, cognitive services, the bot framework and how the company is bringing all these capabilities for developers to build applications in cloud with AI.

Episode 191: A Geek's Rap About Neural Networks

September 29th, 2017  |  2 mins 57 secs

ai, data science, machine learning, neural networks, software circus, {code}

One thing about Software Circus — performances were not just for the actors. We saw bank technologists jousting to tell their story about scale. {code} hosted what was described as the smallest cafe. It was in a shipping container. To get out, you had to work with your team to solve a host of clues. There was an oracle.

Episode 175: MapR’s Ted Dunning: The Intersection of Machine Learning and Containers

August 8th, 2017  |  38 mins 25 secs

application development, containerization, containers, developers, devops, machine learning, programming

If every application in the world could be easily containerized with an automated process, it might already have happened.  We’ve talked before in The New Stack about the many approaches to maintaining state — which, in a less esoteric, more honest-sounding world, is the same thing as “having one’s own database.”  For a stateless system, a stateful construct is a pretty neat trick.  Or at least for now, it’s your choice of several pretty neat tricks, and maybe a few more not-so-neat ones.

But machine learning is a different order of beast.  By implication, something you learn is something you retain.  If you can accept the notion that a machine can “learn” anything, then the whole notion is pointless if the machine is also capable of wiping its own slate clean with each iteration.  Not even a virtual thing can be real unless it retains the same virtues.

Hear more about Dunning’s vision for “REST for ML” in 'The Intersection Between Machine Learning and Containers,' the latest edition of The New Stack Makers podcast.