The Cloudcast

Exploring legal issues arising from digital transformation in various industries, including ride sharing, monetary systems, and AI. Open source licensing and generative AI models impact liability, property ownership, and fair use. New technologies and diverse data sets raise questions about accuracy, liability, and consequences. Incorporating legal aspects and frameworks in digital transformation initiatives is crucial, involving legal experts from the outset.

Joe Duffy, CEO of PulumiCorp, discusses the evolution of infrastructure as code, challenges of multi-cloud, and the use of generative AI in Ops. They also touch on standardizing IaC, changes in license for open-source projects, and resources for learning IaC.

Exploring the push for people to return to the office and the impact of AI on labor. Discussing the advantages and challenges of remote work, as well as the ongoing labor-versus-management battle. Examining the benefits of working in an office, such as collaboration and visibility. Emphasizing the importance of considering both labor and management perspectives.

The podcast discusses barriers to entry for AI & ML, the challenges of implementing models into production applications, the complexity of integrating generative AI, the use of off-the-shelf models vs training from scratch, and OctoML as a platform for model deployment.

Challenges Enterprises face with AI, from data and GPU location to biases and privacy. How AI will impact businesses and the IT industry. Different perspectives on enterprise AI and old AI. The evolution of AI and its democratization. Concerns about misinformation and bias in AI.

Yaniv Ben Hemo, Founder/CEO at Memphis Dev, discusses Memphis Cloud, an alternative architecture for delivering streaming data. He explains why a streaming alternative like Memphis is needed, the differences between a broker and a streaming stack, and the challenges with existing tools like Kafka. The podcast also explores the shift from batch processing to real-time streaming in data processing.

Explore AWS's future position in the evolving cloud market and their readiness to cross the chasm. Discuss their dominance, wide range of services, and significant investments. Evaluate their differentiation, innovation pace, and partnership strategy. Examine potential challenges and transformations ahead, including new leadership and market dynamics.

Gaetan Castelein (@gaetcast, VP Marketing at @tectonai) talks about the complexities of building AI models, features and deploying AI into production for real-time applications. SHOW: 745CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwNEW TO CLOUD? CHECK OUT - "CLOUDCAST BASICS"SHOW SPONSORS:AWS Insiders is an edgy, entertaining podcast about the services and future of cloud computing at AWS. Listen to AWS Insiders in your favorite podcast player. Cloudfix HomepageFind "Breaking Analysis Podcast with Dave Vellante" on Apple, Google and SpotifyKeep up to data with Enterprise Tech with theCUBEReduce the complexities of protecting your workloads and applications in a multi-cloud environment. Panoptica provides comprehensive cloud workload protection integrated with API security to protect the entire application lifecycle.  Learn more about Panoptica at panoptica.appSHOW NOTES:Tecton (homepage)State of Applied Machine Learning 2023 ReportHello Fresh adopts Tecton - Good article on features and feature storesWhat is real-time machine learning?Feature Platform vs. Feature StoreTopic 1 - Welcome to the show. Tell us a little bit about your backgroundTopic 2 - Let’s start with some terminology. A lot of our listeners might be relatively new to Machine Learning. I’m still coming up to speed and I actually spent more time than usual just wrapping my head around the concepts and terms and piecing them all together. What is a feature? Why is it important? How many features does ChatGPT 3 have or ChatGPT4?Topic 3 - How is a feature different from a model? Both are needed, why?Topic 4 - I’ve always wondered exactly what a data scientist does. Is this where the term Feature Engineering comes into play? Who turns the data into features and picks the appropriate model? Topic 5 - Early Machine Learning was analytical ML (offline/batch), correct? How is that different from operational ML (online/batch) and real-time ML?Topic 6 - Now that we have all that out of the way. What is a Feature Platform? How does it integrate into an organization’s existing Devops workflows and/or CI/CD pipelines? (Features as Code) How is it different from a Feature Store?Topic 7 - How do you know if the features + model yield a good result? How is prediction accuracy typically measured?FEEDBACK?Email: show at the cloudcast dot netTwitter: @thecloudcastnet

If every company has become a software company, is it still easy to be a profitable software company? Lots of things are changing around the economics of software.SHOW: 744CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwCHECK OUT OUR NEW PODCAST - "CLOUDCAST BASICS"SHOW SPONSORS:Datadog Application Monitoring: Modern Application Performance MonitoringGet started monitoring service dependencies to eliminate latency and errors and enhance your users app experience with a free 14 day Datadog trial. Listeners of The Cloudcast will also receive a free Datadog T-shirt.CloudZero – Cloud Cost Visibility and Savings​​CloudZero provides immediate and ongoing savings with 100% visibility into your total cloud spendSHOW NOTES:Hashicorp adopts Business Source LicenseNew Relic to be acquiredDatadog Consumption TrendsCloud Giants Q2 TrendsHugging Face adds new licensingThe open source licensing war is overBEING A SOFTWARE COMPANY - JUST BUILD A MOATAre we sure every company wants to become a software company?Lots of software licensing changes in the newsMaking money as a software business, at scale, is difficultPEOPLE DON’T LIKE MOATS AROUND THEIR SOFTWAREOpen source is good for collaborationOpen source could be good for marketingSoftware margins attract VCsOpen source mostly hates software marginsWhat happens to all the software companies funded by VCs over the last 3 yrs?FEEDBACK?Email: show at the cloudcast dot netTwitter: @thecloudcastnet

API security trends and breaches are discussed. The guest, Filip Verloy, talks about his background in API security. Common problems faced by organizations and the role of APIs in breaches are explored. The chapter on AIML in API security is also highlighted.