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      <title>DeeperThoughts - AI &amp; Deep Learning Blog</title>
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      <description>Explore the latest advances in AI systems, deep learning architectures, and machine learning research. In-depth analysis of transformers, attention mechanisms, and neural network interpretability.</description>
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  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/the-moltbook-browsers-vision-for-human-ai-interaction</guid>
    <title>The Moltbook Browser Vision for Human-AI Interaction</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/the-moltbook-browsers-vision-for-human-ai-interaction</link>
    <description>Todays AI is transactional. We chat, then we close the window. The Moltbook is a conceptual leap forward: a persistent, private, and proactive AI partner that learns from your digital life to assist you. This article explores the vision and the immense challenges of this new HCI paradigm.</description>
    <pubDate>Sun, 08 Feb 2026 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>HCI</category><category>AI Agents</category><category>Personal AI</category><category>Privacy</category><category>Future of AI</category><category>Moltbook</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/beyond-rpa-a-technical-comparison-of-ai-agents-and-process-automation</guid>
    <title>Beyond RPA: A Technical Comparison of AI Agents and Process Automation</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/beyond-rpa-a-technical-comparison-of-ai-agents-and-process-automation</link>
    <description>Are AI Agents just glorified RPA bots? This article provides a clear technical comparison between rule-based Robotic Process Automation and goal-oriented AI Agents, breaking down their differences in adaptability, reasoning, and data handling, and exploring how they can work together.</description>
    <pubDate>Sun, 01 Feb 2026 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Agents</category><category>RPA</category><category>Intelligent Automation</category><category>LLMs</category><category>Process Automation</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/can-llms-ensure-code-correctness-formal-verification-with-ai</guid>
    <title>Can LLMs Ensure Code Correctness? Formal Verification with AI</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/can-llms-ensure-code-correctness-formal-verification-with-ai</link>
    <description>LLMs can write code, but is it correct? This article explores the intersection of probabilistic AI and the world of mathematical certainty: Formal Verification. We will examine how LLMs are becoming powerful co-pilots for writing provably correct software and ask if they can ever be trusted to reason on their own.</description>
    <pubDate>Sun, 25 Jan 2026 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Formal Verification</category><category>LLMs</category><category>AI Safety</category><category>Code Correctness</category><category>Neuro-Symbolic AI</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/building-evolving-ai-systems-with-continual-learning</guid>
    <title>Building Evolving AI Systems with Continual Learning</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/building-evolving-ai-systems-with-continual-learning</link>
    <description>Humans learn new things without forgetting the old. AI models usually cant. This article dives into Continual Learning, the quest to build evolving AI. We will explore the critical problem of catastrophic forgetting and the architectural, regularization, and replay methods designed to overcome it.</description>
    <pubDate>Sun, 18 Jan 2026 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Continual Learning</category><category>Lifelong Learning</category><category>Catastrophic Forgetting</category><category>AI Plasticity</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/federated-learning-for-privacy-preserving-model-training</guid>
    <title>Federated Learning for Privacy-Preserving Model Training</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/federated-learning-for-privacy-preserving-model-training</link>
    <description>How can we train models on sensitive data that lives on millions of devices without ever collecting it? This article dives into Federated Learning, the decentralized training paradigm that brings the model to the data. We will break down the FedAvg algorithm and explore the challenges of communication, non-IID data, and security.</description>
    <pubDate>Sun, 11 Jan 2026 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Federated Learning</category><category>Privacy</category><category>Distributed ML</category><category>AI Ethics</category><category>FedAvg</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/enhancing-language-models-with-knowledge-graphs-and-rag</guid>
    <title>Enhancing Language Models with Knowledge Graphs and RAG</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/enhancing-language-models-with-knowledge-graphs-and-rag</link>
    <description>Retrieval-Augmented Generation (RAG) grounds LLMs in external data, but what if that data had structure? This article explores Graph-RAG, an advanced architecture combining vector search with Knowledge Graphs to provide more accurate, explainable, and powerful context for LLMs.</description>
    <pubDate>Sun, 04 Jan 2026 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>RAG</category><category>Knowledge Graphs</category><category>GNN</category><category>LLMs</category><category>Information Retrieval</category><category>Explainable AI</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/modeling-complex-systems-with-multi-agent-reinforcement-learning</guid>
    <title>Modeling Complex Systems with Multi-Agent Reinforcement Learning</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/modeling-complex-systems-with-multi-agent-reinforcement-learning</link>
    <description>When multiple AI agents interact, chaos can ensue—or brilliant, emergent strategies can arise. This article explores Multi-Agent Reinforcement Learning (MARL), the challenges of non-stationarity, the power of Centralized Training with Decentralized Execution (CTDE), and how MARL is used to model complex real-world systems.</description>
    <pubDate>Sun, 28 Dec 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>MARL</category><category>Reinforcement Learning</category><category>AI Agents</category><category>Complex Systems</category><category>Emergent Behavior</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/data-poisoning-a-critical-threat-to-foundational-ai-models</guid>
    <title>Data Poisoning a Critical Threat to Foundational AI Models</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/data-poisoning-a-critical-threat-to-foundational-ai-models</link>
    <description>Foundational models are trained on web-scale data, but what if that data is hiding poison? This article explores the mechanics of data poisoning attacks, how they create stealthy backdoors in AI models, and why they pose a critical threat to the entire AI supply chain.</description>
    <pubDate>Sun, 21 Dec 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Security</category><category>Data Poisoning</category><category>Adversarial Attacks</category><category>Backdoors</category><category>LLM Security</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/efficient-ai-at-the-edge-with-on-device-architectures</guid>
    <title>Efficient AI at the Edge with On-Device Architectures</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/efficient-ai-at-the-edge-with-on-device-architectures</link>
    <description>Beyond the cloud, the next AI revolution is on-device. This article breaks down the architectural strategies (like MobileNets), compression techniques (quantization, pruning), and compiler magic required to run powerful AI models under the tight constraints of edge devices.</description>
    <pubDate>Sun, 14 Dec 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Edge AI</category><category>On-Device AI</category><category>MobileNet</category><category>Quantization</category><category>Pruning</category><category>Optimization</category><category>TFLite</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/the-scalable-architecture-of-mixture-of-experts-models</guid>
    <title>The Scalable Architecture of Mixture-of-Experts Models</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/the-scalable-architecture-of-mixture-of-experts-models</link>
    <description>A deep dive into Mixture-of-Experts (MoE), the architecture powering models like Mixtral. Explore how MoE enables massive parameter counts with a fraction of the computational cost through sparse, conditional computation, and the role of gating networks and load balancing.</description>
    <pubDate>Sun, 07 Dec 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Mixture of Experts</category><category>MoE</category><category>LLMs</category><category>Scaling</category><category>Deep Learning</category><category>Architecture</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/the-ai-compiler-bridges-models-and-hardware</guid>
    <title>The AI Compiler Bridges Models and Hardware</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/the-ai-compiler-bridges-models-and-hardware</link>
    <description>We celebrate the AI models, but not the unsung heroes that make them run fast. This article dives into the world of AI compilers like TVM and MLIR, explaining how they translate high-level model graphs into optimized code for diverse hardware targets through techniques like operator fusion, tiling, and even ML-driven auto-tuning.</description>
    <pubDate>Sun, 30 Nov 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Compiler</category><category>MLIR</category><category>TVM</category><category>Deep Learning</category><category>Optimization</category><category>Hardware</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/graph-neural-networks</guid>
    <title>Graph Neural Networks</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/graph-neural-networks</link>
    <description>From social networks to molecular structures, much of the worlds most valuable data is not in tables or sequences, but in interconnected graphs. This article dives into how Graph Neural Networks (GNNs) work, what makes them unique, and why they are becoming an indispensable tool in modern AI.</description>
    <pubDate>Sun, 23 Nov 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>GNN</category><category>Deep Learning</category><category>multimodality</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/state-space-models</guid>
    <title>From Transformers to State Space Models</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/state-space-models</link>
    <description>For years, the Transformer has been the undisputed king of AI architectures. But a new contender has emerged: the State Space Model (SSM). This article dives into the mechanics of SSMs like Mamba, explaining how they combine the strengths of RNNs and CNNs to process sequences with linear-time complexity, potentially revolutionizing long-context reasoning and model efficiency.</description>
    <pubDate>Sat, 15 Nov 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Architectures</category><category>LLMs</category><category>Transformers</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/ai-agents-and-autonomous-systems</guid>
    <title>Are AI Agents truly autonomous systems or better executors?</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/ai-agents-and-autonomous-systems</link>
    <description>Beyond simple chatbots, the next evolution in AI is the rise of autonomous agents. This article explores the architecture of modern AI agents, breaking down the core components of planning, tool use, and memory that allow them to execute complex, multi-step tasks and move us closer to truly autonomous AI systems.</description>
    <pubDate>Sat, 08 Nov 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Agents</category><category>Automation</category><category>LLMs</category><category>RAG</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/machine-unlearning</guid>
    <title>Machine Unlearning: Teaching AI to Forget</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/machine-unlearning</link>
    <description>What happens when you need to remove copyrighted data or a user&#39;s private information from a trained AI model? The emerging field of Machine Unlearning provides techniques to make models &#39;forget&#39; specific data without a costly full retrain. This article explores the methods, challenges, and importance of teaching AI to forget.</description>
    <pubDate>Fri, 31 Oct 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Security</category><category>Interpretability</category><category>MLOps</category><category>Machine Unlearning</category><category>Privacy</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/physics-informed-neural-networks</guid>
    <title>Physics-Informed Neural Networks: What, Why, and How</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/physics-informed-neural-networks</link>
    <description>Physics-Informed Neural Networks (PINNs) are a groundbreaking class of models that merge these two worlds, creating neural networks that are constrained by the laws of physics. This article explores how PINNs work, why they are revolutionizing scientific computing, and what their future holds.</description>
    <pubDate>Thu, 23 Oct 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Generative AI</category><category>Interpretability</category><category>Scientific Computing</category>
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  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/visualizing-model-predictions-attention-maps-gradcam</guid>
    <title>Interpreting Vision Models with Grad-CAM and Attention Maps</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/visualizing-model-predictions-attention-maps-gradcam</link>
    <description>Why did my model classify this image as a &#39;cat&#39;? This article dives deep into two key visualization techniques—Grad-CAM for CNNs and Attention Maps for Transformers—to answer that question. We explore the mechanics of how these maps are made, what influences them, and how they serve as powerful tools for debugging model biases and testing robustness.</description>
    <pubDate>Thu, 16 Oct 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category></></category><category>Computer Vision</category><category>Interpretability</category><category>ViT</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/introduction-to-explainable-ai</guid>
    <title>An Introduction to Explainable AI Methods</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/introduction-to-explainable-ai</link>
    <description>Deep learning models are often &#39;black boxes,&#39; making them difficult to trust. This article introduces the field of Explainable AI (XAI) and provides a comprehensive overview of five key post-hoc explanation methods: Occlusion Analysis, Saliency Maps, Grad-CAM, LIME, and SHAP. We explore how each technique works and its role in making AI more transparent.</description>
    <pubDate>Wed, 08 Oct 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Security</category><category>Interpretability</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/multimodal-ai-architectures</guid>
    <title>Architectures of Multimodal AI: Fusing Vision, Language, and Beyond</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/multimodal-ai-architectures</link>
    <description>Modern AI is moving beyond single-purpose models to systems that understand text, images, and audio simultaneously. This article explores the core architectural patterns—from early and late fusion to the sophisticated cross-attention mechanisms and joint embedding spaces—that enable multimodal AI to perceive the world in a more holistic way.</description>
    <pubDate>Tue, 30 Sep 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Attention</category><category>Computer Vision</category><category>Generative AI</category><category>LLMs</category><category>Multimodality</category>
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  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/is-your-llm-lying-to-you</guid>
    <title>Is Your LLM Lying to You?</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/is-your-llm-lying-to-you</link>
    <description>Why even the smartest AI models sometimes prefer to please you rather than tell the truth — and how to fight back.</description>
    <pubDate>Wed, 24 Sep 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Security</category><category>LLMs</category><category>RAG</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/h-infinity-filter-enhanced-cnnlstm</guid>
    <title>Bridging Control Systems and AI: The H∞ Filter Enhanced CNN-LSTM</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/h-infinity-filter-enhanced-cnnlstm</link>
    <description>In this article, I explore a novel deep learning architecture from a recent publication of mine that integrates the H∞ filter from control theory into a CNN-LSTM framework to enhance robustness against noise and class imbalance in arrhythmia detection from heart sound recordings. Our approach achieves state-of-the-art performance on the PhysioNet CinC Challenge 2016 dataset, demonstrating its potential for scalable and reliable cardiac screening.</description>
    <pubDate>Tue, 16 Sep 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Audio Processing</category><category>CNNs</category><category>Computer Vision</category><category>Healthcare</category><category>LSTM</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/promptlock-the-ai-malware</guid>
    <title>PromptLock: How LLMs Are Being Weaponized for AI Malware</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/promptlock-the-ai-malware</link>
    <description>ESET Research uncovered PromptLock — the first ransomware powered by a local LLM. Instead of shipping fixed code, it generates malicious scripts on the fly, making every attack unique and harder to detect. Capable of scanning, exfiltrating, and encrypting files across platforms, PromptLock poses a significant threat to organizations. Read more about how it builds and attacks - prompt by prompt</description>
    <pubDate>Sun, 07 Sep 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Security</category><category>Developer Tools</category><category>Generative AI</category><category>LLMs</category>
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  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/langchain</guid>
    <title>Building a RAG Pipeline using LangChain and Chroma</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/langchain</link>
    <description>Ever wondered how chatbots like customer support assistants instantly pull up the right product manual page or FAQ? From setup to deployment, lets explore how you can transform raw data into a powerful, domain-aware chatbot in just a few lines of code using Langchain and Chroma to build a Retrieval-Augmented Generation (RAG) pipeline.</description>
    <pubDate>Sat, 30 Aug 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category></></category><category>AI Efficiency</category><category>Developer Tools</category><category>LLMs</category><category>MLOps</category><category>RAG</category>
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  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/retrieval-augmented-generation</guid>
    <title>Feeding Your Data to LLMs Using Retrieval Augmented Generation (RAG)</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/retrieval-augmented-generation</link>
    <description>Large language models dont actually “know” everything—they just predict. Retrieval-Augmented Generation (RAG) changes the game by letting them pull in real knowledge, in real time. Curious how? This blog unpacks RAG, its mechanics, and why it might be the future of intelligent AI systems.</description>
    <pubDate>Thu, 21 Aug 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category></></category><category>AI Efficiency</category><category>Generative AI</category><category>LLMs</category><category>Optimization</category><category>RAG</category>
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  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/the-ai-video-revolution-with-veo3</guid>
    <title>The AI Video Revolution with Veo3 and Latent Diffusion</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/the-ai-video-revolution-with-veo3</link>
    <description>AI video generation is transforming the way we create visual content. Models like Veo 3 can turn simple text prompts into lifelike, dynamic videos, opening new possibilities for storytelling, education, and entertainment. But how exactly do these AI models generate realistic motion and visuals from just a few lines of text?</description>
    <pubDate>Mon, 11 Aug 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Computer Vision</category><category>Developer Tools</category><category>Generative AI</category><category>Video Generation</category>
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  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/how-do-llms-solve-math-equations</guid>
    <title>How do LLMs solve Math Equations?</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/how-do-llms-solve-math-equations</link>
    <description>Large Language Models like GPT-4 and Gemini werent built as calculators, but can now solve many math problems. They work by recognizing and reproducing patterns, not by “understanding” math in a human sense, so errors and hallucinations still occur. This blog explores how LLMs handle math and the challenges they face.</description>
    <pubDate>Sun, 03 Aug 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category></></category><category>AI Efficiency</category><category>Generative AI</category><category>Interpretability</category><category>LLMs</category><category>Optimization</category>
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  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/deploying-ai-in-agriculture</guid>
    <title>Deploying AI in Agriculture: How we built a Semi-Supervised ViT pipeline for ICAR</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/deploying-ai-in-agriculture</link>
    <description>What if deep learning could empower farmers to diagnose crop diseases in the field using nothing more than a smartphone? This article explores the  implementation of our project, built under a joint ICAR–NITK collaboration, and how Semi-Supervised learning, Vision Transformers, and ONNX deployment was used to create a diagnostic model that achieved 95.7% accuracy—ready for real-world use in the field.</description>
    <pubDate>Sat, 26 Jul 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category></></category><category>Automation</category><category>Computer Vision</category><category>MLOps</category><category>ONNX</category><category>Semi-Supervised Learning</category><category>ViT</category>
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    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/setting-up-an-mcp-server</guid>
    <title>How to Set Up an MCP Server for Multi-Agent AI Systems</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/setting-up-an-mcp-server</link>
    <description>Learn how to set up a lightweight MCP (Model Context Protocol) server to enable context sharing across AI agents like ChatGPT. This article walks through the core concepts and includes practical code examples to help you build context-aware, multi-agent AI systems.</description>
    <pubDate>Sun, 20 Jul 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category></></category><category>AI Agents</category><category>Automation</category><category>Developer Tools</category><category>Generative AI</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/llm-vulnerabilities</guid>
    <title>LLM Vulnerabilities: From Hidden Threats to Secure Deployments</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/llm-vulnerabilities</link>
    <description>Large Language Models (LLMs) are revolutionizing AI applications across industries. But with their power comes a growing list of security risks—prompt injection, data leakage, and model manipulation. As these threats evolve, one question remains: are we doing enough to protect our AI systems against these threats, and what more can we do?</description>
    <pubDate>Sun, 13 Jul 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Security</category><category>Developer Tools</category><category>LLMs</category><category>MLOps</category><category>Optimization</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/visual-perception-through-vision-transformers</guid>
    <title>Visual Perception through Vision Transformers</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/visual-perception-through-vision-transformers</link>
    <description>Vision Transformers (ViTs) have transformed the way machines process and understand images, replacing convolutions with self-attention. At the heart of this shift lies the question: how do these models “see”? This article explores the internal workings of ViTs, focusing on attention heads, patch embeddings, and interpretability techniques that help us decode how these models perceive the visual world.</description>
    <pubDate>Sun, 06 Jul 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>Attention</category><category>Computer Vision</category><category>Generative AI</category><category>Interpretability</category><category>ViT</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/rise-of-code-llms-and-vibe-coding</guid>
    <title>Is Cursor the End for Programmers? The Rise of Code-LLMs and Vibe Coding</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/rise-of-code-llms-and-vibe-coding</link>
    <description>As Cursor transforms how developers write code, we are witnessing the emergence of &quot;Vibe Coding&quot;—a new paradigm where programmers work through intuition and intent rather than explicit syntax. But how are these CodeLLMs different from traditional LLM architectures, and are we really losing the essence of what made us programmers in the first place?</description>
    <pubDate>Mon, 30 Jun 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>LLMs</category><category>Generative AI</category><category>Developer Tools</category><category>NLP</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/small-language-models</guid>
    <title>Is Bigger Always Better? Rethinking AI Scaling Laws through Small Language Models</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/small-language-models</link>
    <description>Exploring how 1B-parameter small language models can outperform 405B giants through clever compute allocation, test-time scaling, and innovative training strategies. Is bigger really always better in the AI world?</description>
    <pubDate>Mon, 23 Jun 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>AI Efficiency</category><category>Generative AI</category><category>LLMs</category><category>Optimization</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/generative-adversarial-networks</guid>
    <title>Why GANs Fool Us So Well—Until They Fail</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/generative-adversarial-networks</link>
    <description>Ever came across reels on Instagram that show Queen Elizabeth breakdancing and wondered how they look so uncannily real? In a world where AI can create art, faces, and even deepfakes from scratch, GANs stand at the center. But how does AI really generate images that even humans can’t tell are fake?</description>
    <pubDate>Mon, 16 Jun 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>CNNs</category><category>Computer Vision</category><category>Generative AI</category>
  </item>

  <item>
    <guid>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/beyond-attention</guid>
    <title>Beyond Attention—A Dive into the Interpretability of Self Attention Heads in modern LLMs</title>
    <link>https://www.deeper-thoughts-blog.rohithshinoj.com/blog/beyond-attention</link>
    <description>New capabilities of Large Language Models like GPT, LLaMA, Claude, and Grok are emerging almost every day, and at the heart of these powerful models lies the multi-head self-attention mechanism—the secret behind their impressive reasoning and language skills. This article takes a closer look at how these attention heads work together under the hood to create the tools we rely on and admire today.</description>
    <pubDate>Tue, 10 Jun 2025 00:00:00 GMT</pubDate>
    <author>rohithshinoj@gmail.com (Rohith Shinoj Kumar)</author>
    <category>LLMs</category><category>Attention</category><category>NLP</category><category>Transformers</category><category>Generative AI</category><category>Interpretability</category>
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