Real Digital Transformation

What You Need to Know about AI Architecture

Apr 3, 2024

David Linthicum, a thought leader in AI architecture, discusses important aspects of AI architecture with Thomas Erl, covering topics like AI system integration, clean data importance, API management, model explainability, and trust in cloud automation features for data hygiene.

23:08

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David Linthicum

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Quick takeaways

Generative AI is still early in the cloud, led by Microsoft, Google, and AWS.

AI architecture includes data management, model development, and model management for effective integration.

Deep dives

The Current State of AI in the Cloud

The current state of AI in the cloud, particularly generative AI, is described as still early days despite the incredible capabilities available. Companies like Microsoft lead in generative AI developments, with others like Google and AWS also investing in their tools to catch up. While there is a lot of hype around generative AI, actual implementation and investment in transformative systems are predicted to be a few years away due to challenges like data training and system integration.

Data Quality is Crucial in Training Models

00:44

Maintaining Control and Governance in AI Systems

01:17

Introduction

4min

AI System Architecture and Integration in Organizations

9min

Managing API Behavior in Evolving AI Systems

2min

The Importance of Model Explainability in AI Systems

6min

Assessing Trust in Cloud Automation Features for Data Hygiene

2min

As AI becomes an increasingly prominent part of the IT mainstream and as organizations are faced with integrating AI systems with their IT enterprises, there is a growing need for IT professionals to understand the technology and architecture that underlies AI implementations. Thought leader David Linthicum discussses with Thomas Erl the important aspects of AI architecture, and how to best prepare for AI adoption.

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Real Digital Transformation

What You Need to Know about AI Architecture

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

The Current State of AI in the Cloud

Technology Architecture of AI Systems

Explainability and Model Evolvement

Data Quality is Crucial in Training Models

Maintaining Control and Governance in AI Systems

Remember Everything You Learn from Podcasts