Discover how AI lightens the load for Agile coaches, automating sprint prep and preserving psychological safety, with human leadership still at the core.
The Absolute Zero Reasoner diverges from traditional AI learning approaches by enabling AI to learn from scratch, without the need for pre-existing human-provided data.
Build a hands-free voice assistant with wake word detection that converts "Hey Calendar" commands into Google Calendar events using Web Speech API and AI.
AI bias stems from flawed data. It can be reduced through diverse datasets, fairness checks, transparency, and ethical guidelines to ensure AI aligns with human values.
Think of agile fine-tuning as giving your AI a feedback loop and a sprint plan. It helps models stay accurate, adapt to real-world shifts, and serve users better, faster.
Knowing when to choose a reasoning model over a more traditional LLM is essential for maximizing cost and efficiency, and delivering the required level of accuracy.
A summary of the integration of observability API and GenAI to automate preliminary incident reporting with a sample incident report from on-prem and cloud models.
Zero-day exploits hide in plain sight. Learn how AI detects them, see real-world use cases, and build your own Python threat hunter to catch anomalies fast.
We built a multilingual university chatbot using LLaMA2, SageMaker, LangChain, and Milvus with RAG for real-time answers scalable to domains like healthcare and HR.
This article delves into the concept of the Twelve-Factor Agent, an architectural pattern designed to create robust, scalable, and maintainable applications.
July 17, 2025
by Vidyasagar (Sarath Chandra) Machupalli FBCS
CORE
CORE
