tldr - powered by Generative AI

• Serverless computing is a deployment model that abstracts the way applications are deployed on infrastructure, provides auto-scaling capabilities, and has a simplified development and deployment model.
• Functions are a programming model that has a certain function signature that needs to be matched to deploy the function.
• The presentation showcases the use of Knative Serving and Eventing building blocks, CNCF Buildpacks, Tekton Pipelines, and Camel-K for processing Amsterdam city data.
• Developers can benefit from serverless concepts and still be able to deploy across multiple cloud environments.
• The demo includes a react application with a node.js backend that emits cloud events and exposes rest APIs.
• The presentation highlights the benefits of using serverless computing for event-driven applications that scale on demand and consume just the right amount of resources.
• The demo showcases the use of serverless functions for adding real-time capabilities to applications.
• The presentation emphasizes the user-friendliness of the solution, with no Dockerfiles or YAML editing required.
• The presentation includes a live demo of the solution in action.

tldr - powered by Generative AI

• AI capabilities have created new opportunities for product development
• Product development requires a level of tinkering and creativity to find the intersection between new capabilities and user needs
• Language is an AGI complete problem with a lot of potential value to be unlocked
• Models are becoming more accessible and less brittle, making them easier to use for product development
• Startups have an opportunity to build new products that don't fit neatly into existing categories
• Incumbents face challenges in adopting generative AI technology due to reputational risk and the potential for offensive content
• The emergence of AI capabilities is not a joke and may be bad news for startups
• The moat for startups may be in the application or workflow rather than the model itself

tldr - powered by Generative AI

• Foundation models are already impacting human beings and will likely power more than one third of AI in the Enterprise by 2025
• There are different types of Foundation models, including general purpose, domain-specific, and enterprise-specific models
• Human-centered design is a central principle at IBM research and involves considering the different personas that will interact with AI systems
• Efficiency and resource efficiency are important areas of innovation in the creation of large models
• Enhancing representations with reasoning capabilities is a future goal for AI

tldr - powered by Generative AI

• Deutsche Telekom faced challenges in implementing Kubernetes at scale and speed in a complex on-prem environment on bare metal.
• Legacy network and network legacy were some of their biggest enemies.
• They reimagined and implemented a network fabric for on-prem bare metal Kubernetes cloud that supports their internal Cluster-as-a-Service offering.
• Their cloud is hosting clusters where some of their most demanding applications like 5G core are running.
• They are building an internal GitHub Kubernetes cluster-as-a-service platform almost exclusively using open source components.
• They want to reliably build Kubernetes clusters with well-defined APIs for their customers and integrate network functions into the platform.
• They work upstream first and want to work with the community to build and contribute back.
• They use BGP and IP fabrics to manage network traffic flow.