cloud2030

Can large language models effectively supplant developers and DevOps engineers? Today we go deeper into how the models can be trained, if they can be trusted, and what is the upside or positive use case in which we really turn LLMs into the type of weighing person experts that they have the potential to be versus simply something that turns up the volume on how fast you generate code. We also talked about the downsides of that type of model and the potential upsides of how powerful using these tools as assistants could emerge to be as a key aspect here to transform and improve the outcome for work. Transcript: https://otter.ai/u/u3bArfIvx40oUXnRLtSXwAx_Iuw?utm_source=copy_url Photo by Pixabay: https://www.pexels.com/photo/aeroplane-aircraft-airplane-aviation-33224/

We recap the Google Next event and do a deep dive into the interesting topics Google was announcing at their flagship cloud event. We looked at what they were doing for AI, but also some new services offerings around what's going on with Cloud. Then we pulled back and went into generative DevOps, something we're going to be diving into more and more as we explore how to better use large language models in DevOps and automation building/ Fascinating topics and some probing questions at the very end of this discussion. Transcript: https://otter.ai/u/1l0Q6SuFHV7EIG1kBqrWM3wlOec?utm_source=copy_url Photo by Tima Miroshnichenko: https://www.pexels.com/photo/a-person-holding-a-container-full-of-money-7009477/

What’s going on from VMWare to Broadcom to HashiCorp and their license changes. We discuss current topics, even to the sad news about Kris Nova passing during a mountaineering expedition. If you'd like to catch up on the tech news, then this topic hopefully has aged well and you will enjoy it! Transcript: https://otter.ai/u/J18ecRKKwc8As_TLyChs_IdI_Ao?utm_source=copy_url Photo by Oziel Gómez: https://www.pexels.com/photo/man-wearing-gray-long-sleeved-shirt-and-brown-shorts-holding-black-dslr-camera-on-mountain-925263/

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: https://www.fiercewireless.com/wireless/telcos-and-road-digital-promised-land Transcript: https://otter.ai/u/wf2OahZkgp9tzF7eJu0-V08-8jY?utm_source=copy_url Photo by Aksonsat Uanthoeng: https://www.pexels.com/photo/close-up-photo-of-assorted-color-of-push-pins-on-map-1078850/

John Willis, panelist on the episode, shares a bonus story about APIs and Jeff Bezos. The podcast explores the challenges of regulating large language models (LLMs) and discusses the EU's AI Act, UK's adoption of EU regulations, and the National Association of Insurance Careers' realistic approach to LLM regulation. They also discuss consent, ownership, and the legality of using scraped data. The importance of data provenance, metadata management, and similarity search in traditional databases is highlighted. They delve into transforming artifacts into monetary value and invite the listener to join future discussions on regulating LLMs.

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: https://www.linkedin.com/pulse/how-google-measures-manages-tech-debt-abi-noda/ https://devops.com/are-llms-leading-devops-into-a-tech-debt-trap/ Transcript: https://otter.ai/u/ngUClgtMmLLKXCFalDxFNsNdVr4?utm_source=copy_url Image: https://www.pexels.com/photo/anonymous-worker-in-heavy-duty-gloves-3846440/

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: https://otter.ai/u/e1XCyhSa9V81bgMpbox8ujZObuo?utm_source=copy_url Photo by Pollianna Bonnett: https://www.pexels.com/photo/young-brunette-woman-with-sunglasses-crouching-on-blue-chair-17687131/

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 * https://www.runtime.news/hashicorp-closes-a-door/ * https://opentf.org * https://blog.gruntwork.io/the-future-of-terraform-must-be-open-ab0b9ba65bca * https://spacelift.io/blog/spacelift-latest-statement-on-hashicorp-bsl * https://ir.hashicorp.com/news-releases/news-release-details/hashicorp-announces-first-quarter-financial-results-fiscal-0 * https://www.hashicorp.com/license-faq#competitive-product-bsl-coverage * https://www.linkedin.com/posts/rhirschfeld_hashicorp-closes-a-door-activity-7097631727665233920-MxcP/ Photo by BİLAL KARADAĞ: https://www.pexels.com/photo/yk-1-17939409/ Transcript: https://otter.ai/u/ZjTzZZiYh_dXri3rSkjkD50GPuc?utm_source=copy_url

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: https://otter.ai/u/SDaRomv41JtQYM7a6C1Hy7cOpy8?utm_source=copy_url Photo by Taryn Elliott: https://www.pexels.com/photo/person-holding-cupcake-with-white-icing-on-top-4099125/

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 https://www.amazon.com/Investments-Unlimited-Compliance-Thriving-Digital/dp/1950508536 https://techstrong.ai/aiops/the-rise-of-shadow-ai/ https://guidehouse.com/insights/financial-services/2021/public-sector/garp-three-lines-of-defense Transcript: https://otter.ai/u/uC9c3xJS4oATQx7BrYeHAOjFHsY?utm_source=copy_url Image is book cover