Name: Azure Machine Learning by Eat Sleep Code Podcast in IntelVerse
Duration: 30 min 35 s
Description: On this episode of Eat Sleep Code, guest Jennifer Marsman talks about Azure Machine Learning and how Microsoft is bringing AI to the masses.

IntelVerse

In this podcast Michael Stiefel spoke with David Blank-Edelman about the relationship between software architecture and site reliability engineering. Site reliability engineering can give architecture vital feedback about how the system actually behaves in production. Architects and designers can then learn from their failures to improve their ability to build systems that can evolve, gracefully degrade, and, at the right time, be taken out of production.

Reliability, just like latency, throughput, and durability, is an emergent property of a system. Hence the search for a root cause for a failure is counter-productive, and is not likely to produce a reliable system.  One often has to look for what went right, as opposed to what went wrong. Software reliability engineers and architects need to embrace a mutual curiosity of how a system really works and fails in the real world.

Read a transcript of this interview: http://bit.ly/4n63xuC

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Transcript

Looking for Root Causes is a False Path: A Conversation with David Blank-Edelman

Magdalena Picariello reframes how we think about AI, moving the conversation from algorithms and metrics to business impact and outcomes. She champions evaluation systems that don't just measure accuracy but also demonstrate real-world business value, and advocates for iterative development with continuous feedback to build optimal applications.

Read a transcript of this interview: http://bit.ly/4oqUIMv

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Upcoming Events:

QCon San Francisco 2025 (November 17-21, 2025)
Get practical inspiration and best practices on emerging software trends directly from senior software developers at early adopter companies.
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QCon AI New York 2025 (December 16-17, 2025)
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QCon London 2026 (March 16-19, 2026)
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The InfoQ Podcasts: 
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If You Can’t Test It, Don’t Deploy It: The New Rule of AI Development?

Jenish Shah, a back-end engineer focused on distributed systems at Netflix, provides more insights on how to handle failures in a distributed systems setup. He shares details on how he built a library that handles exceptions uniformly, regardless of the underlying communication protocol. 

Read a transcript of this interview: http://bit.ly/3JpmIBn

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Upcoming Events:

QCon San Francisco 2025 (November 17-21, 2025)
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QCon AI New York 2025 (December 16-17, 2025)
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QCon London 2026 (March 16-19, 2026)
https://qconlondon.com/

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Effective Error Handling: A Uniform Strategy for Heterogeneous Distributed Systems

In this podcast, Michael Stiefel spoke with Randy Shoup about how to evolve your software after a software failure, and how to improve the resilience of your software by modeling transient states using events and workflows.

Software failure is inevitable, but learning from failure, including making the necessary changes to organizational culture can make your software more resilient. One of the most important ways to do this is to search for the truth, rather than trying to seek out the guilty. The real world is asynchronous, which means that transient events are important for resilient systems because that is where failures often occur, or compensation has to take place. Workflows and events are the best way to model these systems.

Read a transcript of this interview: https://bit.ly/3Lmvd0I

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QCon London 2026 (March 16-19, 2026)
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The InfoQ Podcasts: 
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Architecture Should Model the World as It Really Is: A Conversation with Randy Shoup

Marina Moore, a security researcher and the co-chair of the security and compliance TAG of CNCF, shares her concerns about the security vulnerabilities of containers. She explains where the issues originate, providing solutions and discussing alternative routes to using micro-VMs rather than containers. Additionally, she highlights the risks associated with AI inference.

Read a transcript of this interview: https://bit.ly/4qUCcyi

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QCon San Francisco 2025 (November 17-21, 2025)
Get practical inspiration and best practices on emerging software trends directly from senior software developers at early adopter companies.
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QCon AI New York 2025 (December 16-17, 2025)
https://ai.qconferences.com/

QCon London 2026 (March 16-19, 2026)
https://qconlondon.com/

The InfoQ Podcasts: 
Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts:

- The InfoQ Podcast https://www.infoq.com/podcasts/ 
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Cloud Security Challenges in the AI Era - How Running Containers and Inference Weaken Your System

Vivek Yadav, an engineering manager from Stripe, shares his experience in building a testing system based on multi-year worth of data. He shares insights into why Apache Spark was the choice for creating such a system and how it fits in the "traditional" engineering practices.

Read a transcript of this interview: https://bit.ly/4o08NjD

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QCon AI New York 2025 (December 16-17, 2025)
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QCon London 2026 (March 16-19, 2026)
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https://qconlondon.com/

QCon AI Boston 2026 (June 1-2, 2026)
Learn how real teams are accelerating the entire software lifecycle with AI.
https://boston.qcon.ai


The InfoQ Podcasts: 
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How to Use Apache Spark to Craft a Multi-Year Data Regression Testing and Simulations Framework

In this episode, QCon AI New York 2025 Chair Wes Reisz speaks with Reken CEO and Google Trust & Safety founder Shuman Ghosemajumder about the erosion of digital trust. They explore how deepfakes and automated social engineering are scaling cybercrime. Shuman argues defenders must move beyond default trust, utilizing behavioral telemetry and game theory to counter attacks that simulate human behavior.

Read a transcript of this interview: https://bit.ly/4p7zX9z

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QCon AI New York 2025 (December 16-17, 2025)
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QCon AI Boston 2026 (June 1-2, 2026)
Learn how real teams are accelerating the entire software lifecycle with AI.
https://boston.qcon.ai


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GenAI Security: Defending Against Deepfakes and Automated Social Engineering

Gabriele Columbro, managing director of the Linux Foundation Europe, discusses the differences in the open-source landscape between Europe, China and the US. Stressing that the open-source landscape is the last favorable ground for global innovation in the current geo-political landscape.

Read a transcript of this interview: https://bit.ly/4rFIhPu

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QCon AI New York 2025 (December 16-17, 2025) - SOLD OUT!
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https://qconlondon.com/

QCon AI Boston 2026 (June 1-2, 2026)
Learn how real teams are accelerating the entire software lifecycle with AI.
https://boston.qcon.ai


The InfoQ Podcasts: 
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Bridging the Open Source Gap: From Funding Paradoxes to Digital Sovereignty

QCon AI New York Chair Wes Reisz talks with LinkedIn’s Karthik Ramgopal and Prince Valluri about enabling AI agents at enterprise scale. They discuss how platform teams orchestrate secure, multi-agentic systems, the role of MCP, the use of foreground and background agents, improving developer experience, and reducing toil.

Read a transcript of this interview: https://bit.ly/4prPukO

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https://qconlondon.com/

QCon AI Boston 2026 (June 1-2, 2026)
Learn how real teams are accelerating the entire software lifecycle with AI.
https://boston.qcon.ai


The InfoQ Podcasts: 
Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts:

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Platform Engineering for AI: Scaling Agents and MCP at LinkedIn

Will McGugan, the maker of Textual and Rich frameworks, speaks about the reasoning of developing the two two libraries and the lesson learned. Also, he shares light on Toad, his current project, which he envisions being a more visually appealing way of interacting with agentic LLMs through command line. 

Read a transcript of this interview: https://bit.ly/4j1MtFq

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QCon London 2026 (March 16-19, 2026)
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https://qconlondon.com/

QCon AI Boston 2026 (June 1-2, 2026)
Learn how real teams are accelerating the entire software lifecycle with AI.
https://boston.qcon.ai


The InfoQ Podcasts: 
Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts:

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Building a More Appealing CLI for Agentic LLMs Based on Learnings from the Textual Framework

On this episode of Eat Sleep Code, guest Jennifer Marsman talks about Azure Machine Learning and how Microsoft is bringing AI to the masses.

Developer Network

Azure Machine Learning

In this episode of the O’Reilly Data Show, I spoke with Danny Bickson, co-founder and VP at Dato, and the principal organizer of the Data Science Summit (full disclosure: I’m a member of the conference organizing committee). Among machine learning students and practitioners, recommender systems have become somewhat of a canonical use case and application. One of the early and popular building blocks was GraphLab’s collaborative filtering toolkit, a library originally written and maintained by Bickson. He has continued to keep tabs on the latest developments in recommenders and continues to help organize workshops on related topics throughout the world.

Building and Deploying Large-Scale Machine Learning Applications

In this episode of the Data Show, I spoke with Parvez Ahammad, who leads the data science and machine learning efforts at Instart Logic. He has applied machine learning in a variety of domains, most recently to computational neuroscience and security. Along the way, he has assembled and managed teams of data scientists and has had to grapple with issues like explainability and interpretability, ethics, insufficient amount of labeled data, and adversaries who target machine learning models. As more companies deploy machine learning models into products, it’s important to remember there are many other factors that come into play aside from raw performance metrics.

Building Machine Learning Solutions That Can Withstand Adversarial Attacks

In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer and legal engineer at Immuta, a company building data management tools tuned for data science. Burt and cybersecurity pioneer Daniel Geer recently released a must-read white paper (“Flat Light”) that provides a great framework for how to think about information security in the age of big data and AI. They list important changes to the information landscape and offer suggestions on how to alleviate some of the new risks introduced by the rise of machine learning and AI.

We discussed their new white paper, cybersecurity (Burt was previously a special advisor at the FBI), and an exciting new Strata Data tutorial that Burt will be co-teaching in March.

How Machine Learning Impacts Information Security

Three generals are voting on whether to attack or retreat from their siege of a castle. One of the generals is corrupt and two of them are not. What happens when the corrupted general sends different answers to the other two generals?

A Byzantine fault is "a condition of a computer system, particularly distributed computing systems, where components may fail and there is imperfect information on whether a component has failed. The term takes its name from an allegory, the "Byzantine Generals' Problem", developed to describe this condition, where actors must agree on a concerted strategy to avoid catastrophic system failure, but some of the actors are unreliable."

The Byzantine Generals' Problem and associated issues in maintaining reliable distributed computing networks is illuminating for both AI alignment and modern networks we interact with like Youtube, Facebook, or Google. By exploring this space, we are shown the limits of reliable distributed computing, the safety concerns and threats in this space, and the tradeoffs we will have to make for varying degrees of efficiency or safety.

The Byzantine Generals' Problem, Poisoning, and Distributed Machine Learning with El Mahdi El Mahmdi is the ninth podcast in the AI Alignment Podcast series, hosted by Lucas Perry. El Mahdi pioneered Byzantine resilient machine learning devising a series of provably safe algorithms he recently presented at NeurIPS and ICML. Interested in theoretical biology, his work also includes the analysis of error propagation and networks applied to both neural and biomolecular networks. This particular episode was recorded at the Beneficial AGI 2019 conference in Puerto Rico. We hope that you will join in the conversations by following us or subscribing to our podcasts on Youtube, SoundCloud, iTunes, Google Play, Stitcher, or your preferred podcast site/application. You can find all the AI Alignment Podcasts here.

If you're interested in exploring the interdisciplinary nature of AI alignment, we suggest you take a look here at a preliminary landscape which begins to map this space.

Topics discussed in this episode include:

The Byzantine Generals' Problem
What this has to do with artificial intelligence and machine learning
Everyday situations where this is important
How systems and models are to update in the context of asynchrony
Why it's hard to do Byzantine resilient distributed ML.
Why this is important for long-term AI alignment
An overview of Adversarial Machine Learning and where Byzantine-resilient Machine Learning stands on the map is available in this (9min) video . A specific focus on Byzantine Fault Tolerant Machine Learning is available here (~7min)

In particular, El Mahdi argues in the first interview (and in the podcast) that technical AI safety is not only relevant for long term concerns, but is crucial in current pressing issues such as social media poisoning of public debates and misinformation propagation, both of which fall into Poisoning-resilience. Another example he likes to use is social media addiction, that could be seen as a case of (non) Safely Interruptible learning. This value misalignment is already an issue with the primitive forms of AIs that optimize our world today as they maximize our watch-time all over the internet.

The latter (Safe Interruptibility) is another technical AI safety question El Mahdi works on, in the context of Reinforcement Learning. This line of research was initially dismissed as "science fiction", in this interview (5min), El Mahdi explains why it is a realistic question that arises naturally in reinforcement learning

El Mahdi's work on Byzantine-resilient Machine Learning and other relevant topics is available on
his Google scholar profile.

The Byzantine Generals' Problem, Poisoning, and Distributed Machine Learning with El Mahdi El Mhamdi

Eat Sleep Code is the Official Telerik Podcast (Telerik by Progress). On Eat Sleep Code you'll hear from industry pros and developers just like you. Topics include all things software development and upcoming tech.

Progress believes in giving back to the developer community and we do this by writing, speaking and staying in touch with the software development community.

Founder of EPIC Knowledge Society and SPACE Creative Culture Labs. I am a Futurist and Data Scientist with Professional Mastery and Pragmatic Insights on Digital Transformation and Innovation Management with extensive credentials on Digital Enterprise Architectures, Crypto Economics, Customer Experience Design, Social Entrepreneurship Incubation, Business Model Innovation, Innovation Ecosystems, Innovation Analytics, Innovation Consulting, Social Business Networks, Academic Research Networks, Industrial Research Alliances, New Service Incubation, New Product Incubation, New Platform Innovation, High performing Teams, Cross Competency Innovation etc.

Azure Machine Learning

Eat Sleep Code Podcast

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