Your AI model passes every test. It scores high on accuracy. It handles edge cases well. Then one day, it starts making bizarre mistakes — classifying spam as safe, approving fraudulent transactions, or misreading a road sign. What happened? Most likely, someone launched an adversarial attack on AI system.In this guide, you will learn what […]
Adversarial Attacks on AI Read More »
Generative AI becomes far more powerful when you stop thinking in single prompts and start thinking in systems. Instead of asking ChatGPT, Claude, or Copilot one question at a time, imagine an AI system that can plan tasks, call APIs, retain context over time, and refine its output. In other words, the shift from isolated
Advanced Applications of LLMs Read More »
To get the most out of this article, start with the first part of this series—Core Concepts of Generative AI for Developers. There we built a mental model around transformers, self-attention, positional encoding, and modern innovations like FlashAttention and Mixture of Experts. Here we go one step further: we look at how LLMs appear to
LLMs Reasoning and Prompting Read More »
LLM‑powered AI agents are transforming how we approach automation. At their core, they rely on powerful language models—but with an added layer of autonomy. This means they can break tasks into steps, make decisions, and even use external tools. They are more than simple chatbots; they are goal‑driven problem‑solvers capable of handling complex, multi‑step work. Let’s take a closer
Generative AI Foundations: Agentic AI Read More »
Whenever we build a model, we want to measure its performance—how successful is the model? However, in such fields, the word “success” can have more than one meaning. Therefore, we need to learn about differnent Model Evaluation Metrics. Classification Metrics Classification is the task of predicting the class to which input data belongs. One example
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Before starting the Sentiment Analysis Model, make sure to visit NLP Architectures – Text Classification. In that article, we explored the key steps of a Sentiment Analysis Model—from tokenization and embeddings to LSTM processing and loss optimization—providing a clear picture of how text classification and sentiment analysis work. Each stage plays a crucial role in transforming raw text into meaningful predictions, enabling models
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Understanding the architecture of NLP models matters because, even though we can now call powerful pre‑trained models with just a few lines of code, we still need to know how they are trained and what they are actually doing under the hood. This knowledge helps us choose the right type of model for a task—for example, a classification model that outputs a
NLP Architectures- Text Classification Read More »
In this tutorial, you’ll learn how to read Google Docs with Spring Boot application using google docs api. We’ll guide you through setting up OAuth 2.0, accessing the Docs API, and retrieving document data programmatically. Create a Google Cloud project In the Google Cloud console, go to menu > IAM & Admin > Create a Project.Enter Project Name and Create.
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In recent years, IntelliJ IDEA from JetBrains has rapidly emerged as the leading IDE for Java developers. According to Google, IntelliJ IDEA is currently the most popular Java IDE. A key feature that makes IntelliJ so attractive to Java developers is its capability to be extended through plugins, allowing for the creation of new functionalities.
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The single responsibility principle has a pretty straightforward definition. Every function, class, or module should have one and only one reason to change. This definition seems pretty simple. However, it might be a little bit abstract. For example, what is a reason to change? Well, in this context, a reason to change is a synonym
SOLID: Single Responsibility Principle Read More »
