Category Archives: Artificial Intelligence

Digital Twins + AI = WOW

How can the intersection of generative AI machine learning and artificial intelligence be applied to environments using digital twins? Today we discuss digital twins and artificial intelligence.

How can we improve the simulations, the systems, the interactions that we build? How can we correctly model complex components of everything from cars to pumps in ways that allow us to then build on top and build more intelligent systems.

We come up with some grounded examples.

Mentioned: projectarrow.ca/
Transcript: otter.ai/u/A79s08jpJ4-UPyT313…?utm_source=copy_url
Image:www.pexels.com/photo/two-bernese…on-floor-9040438/

Rob’s Hot Take:

In the Cloud 2030 podcast episode on digital twins and AI, Rob Hirschfeld discusses the potential of using digital twins in handling real-world disasters, citing the recent train derailment in Ohio as an example. The concept involves quickly creating a digital twin of a disaster space to enable robots to learn, adapt, and efficiently mitigate the situation. Hirschfeld emphasizes the unprecedented opportunities for improving environmental interactions, responding to crises, and highlights the sophistication of ideas discussed in the episode. He encourages listeners to explore the full conversation on digital twins and AI at the2030.cloud.

Meta Data, Dark Data and Intent

https://soundcloud.com/user-410091210/meta-data-dark-data-and-intent

Data comes from many different places, sources, and ways. Some data we call dark data, which is data not accessible to you, and all of it relevant. Today we talk about metadata as part of the governance control management exposure of data.

An important layer beyond the data itself is the governance intent, how people access it, and how you combine data. We discuss exactly what that is, but still only touch the surface.

References:
yago-knowledge.org
en.wikipedia.org/wiki/Ontology

Transcript: otter.ai/u/rP_4gi-iDont0r2CaZ…?utm_source=copy_url
Image: www.pexels.com/photo/apples-and-…n-books-14098062/

Rob’s Hot Take:

In the Cloud 2030 Podcast episode on metadata and building a data control plane, Rob Hirschfeld emphasizes the challenge of controlling data egress due to its diverse sources and destinations. He contends that rather than attempting to create a locked box for all data, the focus should be on embedding information, particularly metadata, to control data consumption. Hirschfeld envisions a distributed system for a data control plane, involving multiple parties managing and providing consistent rules for data use, acknowledging the complexity of data storage across various locations. He encourages listeners to explore the insightful February 2nd episode and engage in ongoing conversations at the2030.cloud.

PCIv4, NFT, Metaverse, and CRypto! Oh My!

What is the intersection between augmented and virtual reality?

In today’s episode, we discuss changes in payment systems, Metaverse, NFTs and micro payments. All of which have to do with PCI and how we handle process payments.

We had a fascinating conversation about how all of these technologies intersect, and how one can drive another.

Transcript: otter.ai/u/Jbj52Opa37Vwmci1myBC7LsSXtY
Image: www.pexels.com/photo/selective-f…-figurine-362685/

Cloud2030PCIPaymentsMetaverseCryptoNFTAR/VRMicropaymentsRipple

Rob’s Hot Take:

In the May 17th DevOps Lunch and Learn, Rob Hirschfeld discusses the use of Jenkins and other CI/CD pipeline tools in day two operations, emphasizing the missing discussions around operational requirements, tooling, and integrations in common day two patterns. The conversation reveals the tendency in operations to avoid discussing or sharing common practices, even when widely used, due to embarrassment or perception of it being the wrong approach. The episode explores how acknowledging and addressing these patterns is crucial for building effective day two operations, offering valuable insights for those interested in DevOps, infrastructure, and automation. Join the ongoing discussions at the2030.cloud to delve deeper into these critical topics.

WTF My MFA is MIA

How do authorization systems need to be built and made resilient for distributed infrastructure? We discuss how having a single centralized authorization system is incredibly fragile compared to distributed edge infrastructure.

Everything we build has some element of distributed component tree and resiliency in it, and we need to make sure that the authorization systems are included in that analysis.

We explored how you can make MFA more resilient and how you can improve the security of authentication by building additional layers of trust based on behaviors.

Transcript: otter.ai/u/KTg3WSqSKuswLIypoBwD4HyMzcA
Image: www.pexels.com/photo/hand-holdin…sh-drive-5474298/

Rob’s Hot Take:

In the April 28th Cloud 2030 Podcast, Rob Hirschfeld delves into the challenges of implementing two-factor authentication (2FA) in distributed infrastructures with centralized authentication. The critical problem revolves around creating resilient systems that don’t solely rely on external factors for authentication, considering the potential impact on every service and component in the infrastructure. The discussion emphasizes the importance of behavioral analysis in authentication, scrutinizing user behavior to ensure trustworthiness, especially in scenarios where full authentication is not available. The full conversation explores these aspects in depth, providing valuable insights for building resilient infrastructure. Join future discussions at the2030.cloud.

Serverless vs Digital Twins

We discussed the intersection of serverless and digital twinning. These two concepts are really tightly intermingled!

We discarded the idea of a central single serverless hub managing everything; instead, we think sites would actually have a mesh of serverless, interconnected event processing and stream processing systems. This approach is much more function dependent, but really opens up a lot of interesting discussions and possibilities.

We also discussed how to manage all of this meshed, serverless subscription modeling eventing, and digital twinning.

Transcript: otter.ai/u/FWW3CwG6gMX0N06QXp9C-pZd-s8
Image: www.pexels.com/photo/two-young-g…-sweater-9532902/

Cloud2030ServerlessCloudDigital TwinsModelsAI/MLEvent ProcessingDistributed SystemsEdge

Rob’s Hot Take:

Rob Hirschfeld, CEO and co-founder of RackN and host of the Cloud 2030 roundtable discussions, shares insights from the January 13th discussion on serverless and digital twinning. He emphasizes the significant overlap between modeling data through digital twinning and building serverless systems that subscribe to events for action, transformation, and control. Hirschfeld underscores the need for a joint discussion on these topics, highlighting that a sustainable serverless system requires a reliable model, and a useful digital twin system must connect inputs and outputs to the real world. Interested listeners are invited to explore the full episode at the2030.cloud for a comprehensive discussion on these critical industry aspects.

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/

Edge Impact of Digital Twins

We talk about Digital Twins and the Edge with Simon Crosby from Swim.AI. They are literally building digital twins in edge locations so he has a lot to share.

We work to expand and understand how Simon’s experience translates into general cases and what we’re seeing in the edge. The systems that we’re trying to build are at the intersection of models and “connectedness” of all the components for the edge.

These designs don’t fit traditional models and it is what makes edge unique. Edge is not a single application, but a connected system that going to have to emerge to make all this work together.

Transcript: otter.ai/u/-uFSclONwRhhc4QlFywiSJAIF10
Photo by Dmitriy Ganin from Pexels [ID 7538096]