Category Archives: Machine Learning

Lean In Data Science

How do we apply the principles of lean to data science and data engineering? We discuss this broadly into using AI and machine learning more generally.

This is a topic that we had discussed over the summer and wanted to come back to six months later because so much has changed and transformed in the industry. What does agile lean process control look like in an infrastructure automation platform? How can we make these very difficult and challenging components of data and data management, more agile, more lean?

I think you will get a lot out of this conversation considering our current hypercharged AI ml and LM environment.

Transcript: otter.ai/u/1ZuALgSXcPw-bIf2GO…?utm_source=copy_url
DALL-E Prompt: please create a picture of a very large truck stuck under a low bridge. please label the truck as ai and the bridge as lean

AI And Technical Debt

We dig into a topic written about by Eric Norlin or SK ventures about technical debt and AI. In this episode, we discuss the consequences of generative AI could be radically transforming the way in which we generate code and deal with code that has been generated in technical debt.

We explore some fascinating concepts about how fast we can iterate, how we change the dynamics of building software, building automation, and the expertise required to architect systems. This leads pretty far down in the path towards disruptive thinking, and how this could reshape the entire industry.

Source: skventures.substack.com/p/societys-te…and-softwares
Transcript: otter.ai/u/MEtVkoNnZeCu0JHa30…?utm_source=copy_url
Image: www.pexels.com/photo/piggy-bank-…a-flower-4886900/

Rob’s Hot Take:

In a discussion on the Cloud 2030 podcast, CEO and co-founder of RackN, Rob Hirschfeld, highlighted the changing landscape of expertise in emerging technologies like AI. With the cost to build and iterate dropping significantly, expertise is no longer primarily applied during the building process, but integrated into design and testing sequences. The advent of generative AI has the potential to revolutionize how we design and build automation, software code, and technical systems, necessitating a redefinition of expertise in this rapidly evolving field.

Metadata Architecture

Every time we look at data analytics and data systems, the idea of having a way to manage control and explain the data is actually as important as the data itself. This episode is all about metadata, specifically, metadata related to data analytics analysis, Big Data computation, sort of the data lake metadata problem.

Today we discuss the challenges of data management, but also the potential of understanding so much more about how data is used. If you are an IT professional or a data professional, you will find this conversation about how we’re going to draw inferences, manage and control all of that data that were collected fascinating.

Transcript: otter.ai/u/dFF6CfBYOMR3QFydae…?utm_source=copy_url
Image: www.pexels.com/photo/woman-stand…-mirrors-6208385/

Machine Learning in Operations

Today’s episode is about how to trust machine learning in operations. This is a really serious issue because the attraction of machine learning is strong, but does not translate into operations.

Why doesn’t it translate? Because operations is a closed loop process where we constantly get feedback and have to adapt and adjust. That makes it difficult to train models and hope that they work. This discussion gets into why that’s the case and what we can do about it.

Then we explore scenarios for machine learning and AI in operations.

Transcript: otter.ai/u/UBjf5IVnKvebTfQgW1xlneZdjOU
Photo: www.pexels.com/photo/high-angle-…of-robot-2599244/

Rob Lalonde on HPC in the Cloud, Machine Learning and Autonomous Cars

Joining us this week is Rob Lalonde, VP & General Manager, Navops at Univa.

About Univa

Univa is the leading independent provider of software-defined computing infrastructure and workload orchestration solutions.

Univa’s intelligent cluster management software increases efficiency while accelerating enterprise migration to hybrid clouds. We help hundreds of companies to manage thousands of applications and run billions of tasks every day.

Dave McCrory on Data Gravity, Data Inertia, and Edge

In this week’s podcast, we speak with Dave McCrory, VP of Engineering for Machine Learning at GE Digital. He focuses on several interesting topics:

• Data Gravity Overview
• Data “Training” – Monetization – Application Usage in Edge
• Multi-Tenancy in Edge?