Systems | Development | Analytics | API | Testing

For many, running generative AI over massive datasets has felt out of reach due to costs and slow processing times. Others settle for traditional ML techniques that require specialized skill sets and often deliver lower-quality results. With optimized mode for BigQuery AI functions, you can now get LLM-quality results at a fraction of the cost and at BigQuery speeds. In this video, we’ll show you how BigQuery uses model distillation and embeddings to process massive datasets, reducing query latency and token consumption.

In this video, I walk through how Keploy works with Claude to make testing faster and more reliable for developers. You’ll see how to use Claude with Keploy to generate test cases for a new feature, based on your application context and API behavior. I also cover what happens when a Keploy test fails because of a breaking change, regression, or an expected product update.

"Every great invention takes time to reach its full potential. Just as the light bulb required a system to illuminate the world, artificial intelligence requires the foundation of process to reliably deliver value.".

Everyone is investing in AI, but most teams are blocked by one thing: their data isn’t ready. Data is scattered across SaaS tools, pipelines break silently, and insights are delayed. Without fresh, reliable, and centralized data, AI models, dashboards, and real-time use cases simply don’t work.

Stop your AI projects from being abandoned due to a lack of data readiness. Cloudera AI provides the tools to secure, govern, and prepare your data for production, no matter where it lives. Turbocharge your AI journey today. Contact your Cloudera representative to learn more. *Read More:* Check out our blog post on solving the AI backlog.

Multi-agent systems aren't new architecture—they're microservices evolved. Varun Jasti of AWS explains why Apache Kafka is the natural backbone for agent-to-agent communication at scale.