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Explore the process of running open-source LLMs, covering infrastructure, deployment, costs, and key learnings for effective implementation in real-world scenarios.
Explore how GenAI and data drive innovation, growth, and personalized experiences. Learn about RAG, vector embeddings, and building data foundations for AI applications.
Explore LLMs' effectiveness in detecting data anomalies, understand data quality importance, and learn practical techniques for anomaly detection using OpenAI and BigQuery.
Develop an LLM vulnerability scanner to audit and secure AI applications. Learn about LLM security risks and build a CLI tool for detecting vulnerabilities in AI systems.
Explore operational excellence for LLMs using Amazon Bedrock. Learn design principles, LLMOps, model lifecycle, customization, and architectural patterns for effective implementation and evaluation.
Explore Hono, a versatile web framework for edge computing. Learn about JavaScript runtimes, WinterCG standards, and Hono's key features like flexibility, speed, type safety, and middleware support.
Explore challenges and best practices for running databases in Kubernetes, focusing on PostgreSQL's transformative potential and the shift from availability to reliability in cloud-native environments.
Explore WebAssembly's potential to revolutionize cloud computing, from its bytecode format to its impact on multitenancy and Kubernetes integration.
Explore modern enterprise data ecosystems on cloud platforms, covering storage, organization, consumption, pipelines, and machine learning. Learn key components and AWS challenges.
Explore revolutionary "platformless" approach to enterprise software engineering, focusing on developer experience and digital delivery without platform distractions.
Learn to build and orchestrate serverless generative AI applications using AWS services like Amazon Bedrock and Step Functions. Explore integration techniques, error handling, and human feedback loops in AI workflows.
Explore event-driven architecture principles, benefits, and challenges. Learn about governance, event design, asynchronous thinking, and practical implementation strategies for building robust systems.
Explore AWS cloud-native architecture, scalability types, and best practices for efficient, auto-scaling, and serverless applications. Compare database options for optimal performance.
Explore event-driven architectures for cloud workflows, covering core concepts, patterns, and best practices. Learn when to use choreography and orchestration, and see a practical demo.
Explore cloud native concepts, GraalVM, and native image building. Learn scalability, cost reduction, and performance optimization techniques for microservices frameworks in the JVM ecosystem.
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