Edge (and Beyond) Industry Update

How do Edge and Compute and SaaS and cloud influence everything that we do? We covered topics from VMware explorer and talked a lot about Edge. That led to AI ml, which led to another topic, which led to another topic.

If you enjoy hearing about how interconnected our technology and choices are, everything from Bitcoin to edge, and cloud and government interaction, this is the podcast for you because we cover pretty much all of it and connect it together.

Remember that on September 14, we are having one of our quarterly book club meetings on the death of expertise.

Resources:
www.fiercewireless.com/wireless/telc…promised-land

Transcript: otter.ai/u/wf2OahZkgp9tzF7eJu…?utm_source=copy_url
Photo by Aksonsat Uanthoeng: www.pexels.com/photo/close-up-ph…s-on-map-1078850/

Rob’s Hot Take:

In the Cloud 2030 podcast episode from August 24th, CEO Rob Hirschfeld discusses the shift from the rental/service economy to owning production assets in the context of cloud and SaaS models. He highlights the financial commitment and decoupling of capital expenses associated with service usage, emphasizing the value of owning assets in certain scenarios. Hirschfeld encourages deliberate decision-making regarding asset ownership, stressing the importance of understanding the long-term consequences and skill-building for businesses. He invites listeners to explore these topics further in the complete August 24th Cloud 2030 conversation.

Can we regulate LLMs? Should we?

How do you regulate large language models? We look at the challenges of regulating these AI approaches and how governments and companies can approach it. We untangle how these models work, and dive into the mechanics of what information is controllable. We walk through concrete information that is a benefit to you here as our listener, and incentive for you to join us in future conversations as we continue to unravel it.

In addition, John Willis was on the panel today, and he started us off with a story about API’s, Amazon, Jeff Bezos, and O’Reilly from the warmup. So you’ll get a short bonus story by John Willis before we start.

References
ised-isde.canada.ca/site/innovation…panion-document
www.europarl.europa.eu/news/en/headl…xt=Parliament‘s%20 priority%20is%20to%20make,automation%2C%20to%20prevent%20harmful%20outcomes
www.trade.gov/market-intelligenc…i-regulations-2023
content.naic.org/cipr-topics/arti…ial-intelligence

Transcript: otter.ai/u/dBRQBFNz8d01taQ-iM…?utm_source=copy_url
Image: www.pexels.com/photo/measuring-g…tar-pick-3988555/

Rob’s Hot Take:

In a Cloud 2030 podcast episode, Rob Hirschfeld, CEO and co-founder of RackN, discussed the complexities of regulating large language models. He highlighted the stark differences in approaches between the US, focusing on model risks, and the EU, emphasizing user rights protection. Hirschfeld expressed concern about reconciling these varying perspectives, especially regarding data rights preservation and understanding the risks associated with using such models, particularly when algorithms cannot be fully validated. He invited listeners to engage in the ongoing conversation at the 2030.cloud.

LLMs adding to Technical Debt? Maintenance?

What is technical debt, and how does it apply to large language models? We dive into a really interesting conversation that goes from technical debt into system and code maintenance, which is probably a much better way to think about the challenges we have in maintaining the infrastructure systems, code, data and data lakes that we have to deal with on an everyday basis.

How do we maintain, store, track and update the LLMs themselves? How do we know and manage which model is being used when we retire a model?

References:
www.linkedin.com/pulse/how-google…h-debt-abi-noda/
devops.com/are-llms-leading-de…o-a-tech-debt-trap/

Transcript: otter.ai/u/ngUClgtMmLLKXCFalD…?utm_source=copy_url
Image: www.pexels.com/photo/anonymous-w…y-gloves-3846440/

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Rob’s Hot Take:

In the Cloud 2030 podcast episode on August 17th, Rob Hirschfeld discusses the distinction between technical debt and system maintenance costs, emphasizing the importance of understanding the ongoing effort needed to maintain and improve systems. He points out that overlooking the maintenance costs while building a system leads to technical debt. Hirschfeld raises the question of whether large language models and AI can change the equation of system maintenance, a topic yet to be explored fully in the podcast.

Data Darkages – do LLMs drive paywalls?

A coming Data Darkage is on its way, where we’re watching Reddit, Twitter and other companies take what used to be publicly available information and put it behind a paywall or gate.

Because of the way large language models are using this data and the value of the data, we are expecting to see that trend accelerate. This will have profound implications for how we think of, share, and use data in the coming years.

Transcript: otter.ai/u/e1XCyhSa9V81bgMpbo…?utm_source=copy_url
Photo by Pollianna Bonnett: www.pexels.com/photo/young-brune…e-chair-17687131/

Hashicorp BSL vs OSS License Discussion

Hashicorp made a license change into a BSL, a business license which is not open source that allows or makes code available, but instead restricts the use of Hashicorp products to people who are effectively paying customers or enterprise customers.

If you’re embedding or repackaging the software or competing with Hashicorp, you are prohibited from using it. We spent this podcast looking into why, how, and what implications there were, as well as historical precedents.

References
www.runtime.news/hashicorp-closes-a-door/
opentf.org
blog.gruntwork.io/the-future-of-te…pen-ab0b9ba65bca
spacelift.io/blog/spacelift-lat…t-on-hashicorp-bsl
ir.hashicorp.com/news-releases/ne…results-fiscal-0
www.hashicorp.com/license-faq#comp…uct-bsl-coverage
www.linkedin.com/posts/rhirschfel…7665233920-MxcP/

Photo by BİLAL KARADAĞ: www.pexels.com/photo/yk-1-17939409/
Transcript: otter.ai/u/ZjTzZZiYh_dXri3rSk…?utm_source=copy_url

Data + Operations = DataOps

We talk about DataOps, but if you’re expecting this to be DevOps for data – you are mistaken. Today we talk about engineering data through the idea of data stewardship or how you manage and control the data.

Beyond permissions and access into the costs and how things are stewarded, how logs are handled, who controls how much access and how quickly people have access, where you’re putting the data to improve its effectiveness, and more. There is so much going on above the infrastructure, but below that actual analytics, this conversation will open your mind to a whole layer of challenges related to governing and managing data.

Transcript: otter.ai/u/SDaRomv41JtQYM7a6C…?utm_source=copy_url
Photo by Taryn Elliott: www.pexels.com/photo/person-hold…g-on-top-4099125/

Book Discussion: Investments Unlimited

This is the second installment of our book group, which is a discussion about Investments Unlimited. We have one of our authors, and a great all around DevOps enthusiast, John Willis, on the call with us.

As you might expect, while we talk about the book and John gives a lot of background and details about the book, we treat it with the classic cloud2030 style, and bring in AI, large language and advanced DevOps.

We take the topics of the book to the next level, and frame it in the moment of the year, looking beyond and into how the concepts of compliance, validation, team coordination and risk assessment are incorporated into the coming AI and how it changes in our landscape.

Sources
Book www.amazon.com/Investments-Unlim…tal/dp/1950508536
techstrong.ai/aiops/the-rise-of-shadow-ai/
guidehouse.com/insights/financia…-lines-of-defense

Transcript: otter.ai/u/uC9c3xJS4oATQx7BrY…?utm_source=copy_url

Can ChatGPT do DevOps?

We use ChatGPT to live create DevOps, automation, Ansible, TerraForm, Python, and interact with different clouds to get advice on how to set up clouds.

This discussion includes a screen share session, so if you’re listening to this audio there will be times when we are talking about something you can’t see but I do make a point of working to explain what we’re doing. There’s also a video of the screen share session if you prefer.

Video: youtu.be/hU7pUDfliGk
Transcript: otter.ai/u/MPvT7SP0FCSe02asm8…?utm_source=copy_url
Image: www.pexels.com/photo/pink-backgr…ch-bubble-1111369

Cloud2030DevOpsChatGPTLLMGenerative DevOpsCloudAutomation

Leading And Selling Decisions in Enterprises

What does it take to make a good decision? We discuss an interesting take on this as we integrate the topic of how to sell into situations, and selling is the ultimate drive in a decision.

Our conversation mixes the challenges of making decisions as a leader with the challenges of selling into organizations where people have to make a decision to choose your product. It also includes tips on how to frame decisions, how to position decisions, and more.

If you engage in projects and selling them to your boss, supervisor, company, peers, reports, etc – you need to be able to understand why it is important to move forward and make a decision or change. If you’re not able to sell, you’re not well equipped for being a leader.

Transcript: otter.ai/u/1SRbrNbmISOgTUyV2X…?utm_source=copy_url
Image: www.pexels.com/photo/man-looking…tage-car-3056057/

Generative Coding & DevOps Challenges

What can we expect generative AI to generate and is it going to produce good code? Today we talk about Gluecon and generative DevOps and the different concepts and capabilities around it. What impact is it going to have on developers? How do we control that?

Today’s discussion was in preparation for our session on June 13, where we’re going to group program GPT to see what type of DevOps coding skills we can prompt. We talked about the necessity of prompting in this session and covered some tips to help you think about how to be a better prompt engineer, a skill set that everybody’s going to need to have in the next months if not years.

Transcript: otter.ai/u/lsye_htH0-wksAOrqg…?utm_source=copy_url
Image: www.pexels.com/photo/man-welding…ow-frame-2965260/