cloud2030

How can companies, enterprises and individuals become more innovative? We investigate the idea of innovation and disruption and continue past where we were with the three horizons model in our previous discussions. Today’s podcast focuses on breaking this apart into adapting an agile disruption, the use of standardization and the cognitive dissonance of innovation, even digging down into distinguishing between inventions and applications. Transcript: https://otter.ai/u/XCidE-0xG7zNmIC7FKEwRrJsPi4?utm_source=copy_url DALL-E Prompt: a factor of rubber chickens getting stretching and upgraded into cybertoys

Let's celebrate the work that we've done as a community in the Cloud2030 group this year, and talk about some really exciting things we have planned for next year for 2024. It's remarkable to look back on how this podcast has evolved from a meeting place during COVID, as a place where we could have those hallway tracks that we had been missing, into something that is really discussing technology at the forefront. The forefront of not just tech, but actually of the human and business implications of that technology. Transcript: https://otter.ai/u/d4Rq_a_tdyihTp5EyzOsnRbQ8jg?utm_source=copy_url Image by DALL-E

This is our annual year review and prediction episode and it is a doozy. We talk through what has been an incredibly busy year in Open Source, cloud repre, repatriation, AI, ML, chatGPT. We laid down some really interesting insights and then looked forward not just into 2024 but two years of predictions and trends that we see happening. We cover what we think will be shaking, shaping and shaking the market. References https://basecamp.com/cloud-exit https://world.hey.com/dhh/the-big-cloud-exit-faq-20274010 Transcript: https://otter.ai/u/13Wdve1WQVCPjXtsf8QnJtg6r0M?utm_source=copy_url DALL-E Prompt: futeristic graphic of a hall of mirrors with 2023 turning into 2024 and the cast of the wizard of oz

How do we apply the principles of lean to data science and data engineering? We discuss this broadly into using AI and machine learning more generally. This is a topic that we had discussed over the summer and wanted to come back to six months later because so much has changed and transformed in the industry. What does agile lean process control look like in an infrastructure automation platform? How can we make these very difficult and challenging components of data and data management, more agile, more lean? I think you will get a lot out of this conversation considering our current hypercharged AI ml and LM environment. Transcript: https://otter.ai/u/1ZuALgSXcPw-bIf2GOumDFZH0UU?utm_source=copy_url DALL-E Prompt: please create a picture of a very large truck stuck under a low bridge. please label the truck as ai and the bridge as lean

If you haven’t had a chance to join in on our book groups, I strongly recommend you take a look at the upcoming books we are reading! Today we discussed Data Science and Context, which is a relatively academic book by a series of doctors, PhDs, Specter, Norvig, Wiggins and Wing. The book gets into some really fascinating analysis techniques, addressing both the practical and ethical implications of data science applications. We discuss the biases inherent in the book, the things that are missing and potentially disruptive to the core assumptions of the book. So even if you haven't read this book, I think you will find the discussion fascinating. This week I'm keeping our warm up discussion about open AI in the podcast. So you will get about 10 minutes of bonus content before the book group discussion as a warm up and it is very related. Our conversations about what has been going on with open AI, their board and Q* are directly related to the concluding ideas in our discussion about Data Science and Context. Transcript: https://otter.ai/u/qYBKNhDBKqaghEaxE-I-mz6xDvg?utm_source=copy_url Image: Data Science In Context cover

How can digital identity be used to build better trust and systems in our daily transactions? There are really significant challenges and consequences to having a national guaranteed identity - a single identity provider. Knowing who you're interacting with, in every form, in every situation is not as simple as you might think. There's a lot of analogues to physical identity that are worth considering. What would it mean for us to not have privacy? Does identity mean we don't have privacy in our interactions? Who can we trust and what authority do they have? Transcript: https://otter.ai/u/o_43fyGjxu24Ur5rpzzy_D6aZCI?utm_source=copy_url Image by Dall-e prompte: a cartoon like image of a humanoid robot looking into a mirror and seeing a masked pirate version of itself

What incidental, or accidental, surveillance state is being created by all of the video and listening devices that are now embedded in our world? Today we talk through the ramifications of those networks being in private hands in which companies can actually review, analyze and monetize data from these systems. For example - autonomous vehicle cameras and delivery van cameras. This episode discusses the ramifications of this example and more. References: https://arstechnica.com/tech-policy/2023/11/five-big-carmakers-beat-lawsuits-alleging-infotainment-systems-invade-privacy/ https://www.vzbv.de/en/court-prohibits-linkedins-data-privacy-infringements https://last-chance-for-eidas.org/ Transcript: https://otter.ai/u/NszGAX95R70ydlW_fJcbDKAXwTM?utm_source=copy_url Image by Dall-e prompt: "1950s era cartoon of an autonomous car with a lot of cameras spying on people"

What is innovation? Today we continue this discussion, specifically drilling into the three horizons model for creating growth and value. We spend a lot of time talking about how companies innovate using that model, what it means and what are examples of it? How does that spark take place? We bridge you further down the innovation learning process in this meeting. Transcript: https://otter.ai/u/He9h2NVxazKMDN9a13TcurXsqXU?utm_source=copy_url Image by Dall-E prompt “please create a close up picture of a flock of birds navigating between three different horizons. the birds are smart and know which why they need to go”

We dive deep into the technical subject of governance and policy enforcement, including the tools, techniques and processes that you need to be aware of to do a good job with policy and governance enforcement. We cover how to get started, what to think about, what to be aware of, and chip away at your governance and policy challenges including developer development portals, infrastructure pipelines and DevSecOps. Transcript: https://otter.ai/u/ND90jKHwbklUBOAwT1XkgEo2pbs?utm_source=copy_url Image by Dall-E prompt “please make a carton that shows a regulator who is managing cloud and IT assets using impractical tools”

We dive into the dynamics of open source projects and monetization today, specifically starting around the TerraForm and open tofu split. That topic is one that we love to chew over and potentially over analyze, but today’s discussion is different. We go into how ecosystems are built both in open and proprietary and cloud systems, and look at sort of a historical perspective on what makes a project successful from an ecosystem perspective. We also dive into why some projects work like that, and why some projects don't. Today’s episode gives a new take on some of the dynamics going on in the open source communities through the lens of what happened with Open Tofu and TerraForm. Transcript: https://otter.ai/u/ONDvgS9yGMrSN-bXMTy9KMC-XPs?utm_source=copy_url Photo by James Wheeler: https://www.pexels.com/photo/lake-pebbles-under-body-of-water-1574181/