Automated bug fixing has evolved from simple template-based approaches to sophisticated AI systems powered by LLMs, agents, agentless, and RAG paradigms.
AI agents streamline workflows by autonomously processing claims, detecting fraud, ensuring compliance, and enhancing decision-making with real-time insights.
CSS variables revolutionize the theming of apps by allowing theme changes in real time. This makes them suitable for modern apps having features like data visualization.
The journey of a cloud incident that transformed fragile Liberty microservices into a resilient, self-healing system that scales effortlessly under load.
API management as code is a declarative approach to managing APIs at scale, providing benefits like automation, consistency, collaboration, and scalability.
Materialized views enhance data streaming by improving incremental computation, enabling efficient retrieval and calculation of aggregated or pre-processed data.
A data culture fosters data and AI use to improve decision-making, drive innovation, build trust, and ensure organizational success through collaboration.
In this article, learn about AI in agile product teams, gain insights from deep research, and explore what it means for your practice as an agile practitioner.
We will explore the importance of eXplanation in fraud detection models and learn how it can help to understand different patterns of fraud in our system.
Loss functions measure how wrong an AI's predictions are. Different loss functions are used for different types of problems (regression or classification).