episode-header-image

Jan 2023

49m 50s

Machine learning at small organizations

Practical AI LLC

About this episode

Up next

Narrative intelligence and the human advantage

As AI reshapes how we work, create, and think about our roles, staying adaptable means understanding not just the technology, but our own stories and identities. Reed Frerichs joins Daniel and Chris to explore narrative intelligence, storytelling, leadership, and personal growth ... Show More

Open models and the future of Physical AI with NVIDIA

As AI moves beyond the cloud and into robots, vehicles, and other physical systems, new approaches to models, simulation, and inference are emerging. Daniel and Chris are joined by Ming-Yu Liu, Vice President of Cosmos Lab at NVIDIA, who shares his perspective on open models, wor ... Show More

From AGENTS.md to Enterprise Deployment

AI agents are moving beyond laptops and prototypes and into enterprise environments where security, compliance, scalability, and reliability matter. Nick Kuhn from VMware Tanzu Platform joins Daniel and Chris to discuss what changes (and what doesn’t) when deploying agents alongs ... Show More

Recommended Episodes

Machine Learning In The Enterprise

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Machine learning is a class of technologies that promise to revolutionize business. Unfortunately, it can be difficult to identify and execute on ways that it can be used in large companies. Kevin Dewalt founded Prolego ... Show More

Declarative Machine Learning Without The Operational Overhead Using Continual

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Building, scaling, and maintaining the operational components of a machine learning workflow are all hard problems. Add the work of creating the model itself, and it’s not surprising that a majority of companies th ... Show More

73: Using AI at Work for Small Business Adoption and Team Alignment with Maria Elena Duron

Chris Daigle sits down with Maria Elena Duron, fractional Chief AI Officer and marketing strategist, to explore how small and mid-sized businesses can successfully adopt AI without overwhelming their teams. Maria shares her experience helping businesses bridge the gap between awa ... Show More

TinyML: Bringing machine learning to the edge

When we think about machine learning today we often think in terms of immense scale — large language models that require huge amounts of computational power, for example. But one of the most interesting innovations in machine learning right now is actually happening on a really s ... Show More

Transformational Training and Innovation

What Does It Really Mean To Do MLOps And What Is The Data Engineer's Role?

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Putting machine learning models into production and keeping them there requires investing in well-managed systems to manage the full lifecycle of data cleaning, training, deployment and monitoring. This requires a repeat ... Show More

MLOps + DevOps + Kubernetes with Annie Talvasto

<p>Machine learning models need updating - what's the reliable way to do it? While in Romania, Richard sat down with Annie Talvasto to talk about her work helping to build DevOps practices around machine learning: Building repeatable processes for data ingestions, cleaning, organ ... Show More

#509: Pain in the SaaS: How to Select the Right Tech for Your Firm, with Britt Lorish

Zack talks with legal tech expert Britt Lorish about the process of selecting and managing technology in large and small law firms. Listen in as they talk about typical pain points, common setups, and how process documentation is the first step you know you need to take but don’t ... Show More