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Why RAG Chatbots Struggle in Production
“Our RAG chatbot worked perfectly in the POC.But once we scaled to 50,000 documents… accuracy dropped to 60%.” If you’ve worked with enterprise RAG systems, you’ve probably heard this story. And if you ask most engineers what went wrong, you’ll hear answers like: ❌ These sound smart❌ They sometimes help❌ But they miss the real… Read more
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Measuring ROI for a GenAI Initiative in Healthcare
This blog explores how to measure ROI for Generative AI (GenAI) in healthcare. It outlines key performance indicators (KPIs) related to clinical outcomes, operational efficiency, finance, and patient experience. It emphasizes the importance of clear objectives, baseline measurements, and best practices to successfully assess GenAI’s impact on healthcare organizations. Read more
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Unique Strings with Odd and Even Swapping Allowed
Introduction: In string manipulation, discovering unique strings amidst a sea of possibilities can be both challenging and rewarding. In this tutorial, we embark on a journey to unravel the secrets of identifying unique strings, armed with the power of swapping characters at odd and even indices. Join us as we delve into the depths of… Read more
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Applying SOLID Principles and Dependency Injection in Python
Introduction:In modern software development, adhering to principles and practices that promote maintainability, scalability, and reusability is crucial. Two fundamental concepts in this regard are the SOLID principles and dependency injection. In this tutorial, we’ll delve into these concepts, explaining what they are, how to apply them, and why they are essential in software development. We’ll… Read more
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Building a Regression MLP Using the Sequential API
Let’s switch to the California housing problem and tackle it using a regression neural network. For simplicity, we will use Scikit-Learn’s fetch_california_housing() function to load the data. This dataset is simpler since it contains only numerical features. There is no ocean_proximity feature, and there is no missing value. After loading the data, we split it… Read more
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Logical Computations with Neurons | Deep learning
Warren McCulloch and Walter Pitts proposed a very simple model of the biological neuron, which later became known as an artificial neuron: it has one or more binary (on/off) inputs and one binary output. The artificial neuron simply activates its output when more than a certain number of its inputs are active. McCulloch and Pitts… Read more