The Cloudcast

The Cloudcast (@cloudcastpod) is the industry's #1 Cloud Computing podcast, and the place where Cloud meets AI.  Co-hosts Aaron Delp (@aarondelp) & Brian Gracely (@bgracely) speak with technology and business leaders that are shaping the future of business. Topics will include Cloud Computing | AI | AGI | ChatGPT | Open Source | AWS | Azure | GCP | Platform Engineering | DevOps | Big Data | ML | Security | Kubernetes | AppDev | SaaS | PaaS . 

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The Cloudcast #333 - Infrastructure 3.0 for AI and ML


Aaron and Brian talk with Lenny Pruss (@lennypruss, Partner at Amplify Partners) about the evolution of application and infrastructure architectures, how AI/ML are radically changing how applications are designed, the new inputs to application systems, and how VCs are investing in companies that can augment new cloud services.

Show Links:

  • Lenny Pruss @ Amplify Partners
  • Infrastructure 3.0: Building blocks for the AI revolution
  • Software 2.0
  • Infrastructure 2.0
  • CNCF Cloud-Native Landscape
  • Google AutoML
  • AWS & Microsoft announce “Gluon”
  • AWS DeepLens
  • [PODCAST] @PodCTL - Containers | Kubernetes -  RSS Feed, iTunes, Google Play, Stitcher, TuneIn and all your favorite podcast players
  • [A CLOUD GURU] Get The Cloudcast Alexa Skill
  • [A CLOUD GURU] A Cloud Guru Membership - Start your free trial. Unlimited access to the best cloud training and new series to keep you up-to-date on all things AWS.
  • [A CLOUD GURU] FREE access to AWS Certification Exam Prep Guide - At A Cloud Guru, the #1 question received from students is "I want to pass the AWS cert exam, so where do I start?" This course is your answer.
  • [FREE] eBook from O'Reilly

Show Notes
  • Topic 1 - Welcome to the show. Tell us about your background and how you eventually got into the VC side of the business.
  • Topic 1a - Infrastructure and applications evolve in 'lock-step', so where are we today in terms of this evolution and where are we going?"
  • Topic 2 - You mention this concept of “connectivity vs. cognition” is what makes ML/AI radically different from software of previous generations. Let’s discuss what that means.
  • Topic 3 - “The result is an application that is “smart,” but exceptionally data-intensive and computationally expensive”. What are the problems this creates on today’s infrastructure?
  • Topic 4 - “For ML/AI to reach its full potential, it must graduate from the academic discipline it is today into an engineering one. What that means in practice is that there needs to be new abstractions, interfaces, systems, and tooling to make developing and deploying intelligent applications easy for developers.” - Give us some of the first steps that will make this happen.
  • Topic 5 - As a VC, you’re in the business of finding the companies that might turn this into a reality. Who are some of those companies that are on your radar?
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     February 8, 2018  31m