Open-Source AI: Hope or Hype?
Author(s): Subhadip Saha Originally published on Towards AI. How a personal moment with an “open” model made me question everything about freedom, trust, and the future of intelligence It was 2:47 a.m., and I was sitting alone at my desk, bathed in …
Building ReAct agents with Memory using LangGraph
Author(s): Aayushi_Sharma Originally published on Towards AI. “How do AI agents decide when to think, when to act, and when to stop?” Welcome to the world of ReAct Agents — powerful AI workflows that combine reasoning and actions. If you’ve ever wondered …
Build Smarter Agentic AI Apps with Pydantic: A Beginner’s Guide
Author(s): Aayushi_Sharma Originally published on Towards AI. Introduction Maybe you’re working with user data, building an API, or connecting different parts of a program — whatever the case, bad data can break your code. pydanticThis guide explains how Pydantic can be utilized …
Experiential Chain of Thought (E-CoT): A Framework for Self-Improving Reasoning via Segmented Experience Memory
Author(s): Marc Lopez Originally published on Towards AI. How AI can learn from its own successes and failures to reason more effectively. Large Language Models (LLMs) have shown an incredible ability to reason, largely thanks to techniques like Chain of Thought (CoT) …
Machine Bullshit: Why AI Systems Care More About Sounding Good Than Being Right
Author(s): MKWriteshere Originally published on Towards AI. Scientists just proved that making AI more helpful also makes it more deceptive — and the results are shocking Your AI assistant just told you that “studies suggest this laptop may provide enhanced performance benefits …
The Creativity Trap: Why AI Brainstorms Might Be Limiting Your Ideas
Author(s): Mayank Bohra Originally published on Towards AI. We all hoped AI would bring endless new ideas. It might be doing the exact opposite. I remember when most people agreed on one of the best ways to use generative AI: brainstorming. Everyone, …
Putting Guardrails on AI: How Businesses Can Implement AI Responsibly
Author(s): Marc Lopez Originally published on Towards AI. Putting Guardrails on AI: How Businesses Can Implement AI Responsibly Artificial Intelligence is revolutionizing how businesses operate automating tasks, driving insights, and powering customer experiences. But with great power comes great responsibility. Without proper …
Dot Product Thinking: How LLMs Multiply Tokens, But Miss Meaning
Author(s): Ajay Deewan Originally published on Towards AI. The math behind how machines complete our sentences — and why that still isn’t understanding When ChatGPT completes your sentence better than your closest friend, what is actually happening? Precision guides prediction. Presence gives …
Build Your Own AI Assistant with RAG: A Practical Guide for GenAI Engineers
Author(s): Aayushi_Sharma Originally published on Towards AI. Build Your Own AI Assistant with RAG: A Practical Guide for GenAI Engineers “How can I make ChatGPT answer questions from my own documents?” If you’ve ever wondered that, you’re in the right place. Welcome …
LangGraph 101: What Every AI Engineer Should Know
Author(s): Aayushi_Sharma Originally published on Towards AI. 💡 “Ever wondered how an AI assistant can decide what to do next, like a human?” Behind the scenes, most LLM apps follow a linear flow — input in, output out. But real-world tasks aren’t …
Fine-Tuning Qwen3 with Reasoning using Unsloth
Author(s): Gaurav Shrivastav Originally published on Towards AI. Custom fine tune your Qwen3 model with reasoning using the Unsloth framework with full code I’ve been exploring the Qwen3 family of language models recently, and they’ve certainly made waves with their impressive performance …
Introduction to Multimodality With LLaVA
Author(s): Marcello Politi Originally published on Towards AI. Learn how to implement multimodal AI on low-resource hardware In the last couple of years, I have worked mainly with large language models, training, fine-tuning, prompting and so on, since this was highly requested …
Leaked Grok 4 Prompts Reveal How AI Companies Build Ideology Engines
Author(s): MKWriteshere Originally published on Towards AI. A deep dive into leaked system instructions reveals how reinforcement learning, X integration, and selective benchmarking create AI models that shape public opinion while claiming neutrality. You ask an AI about the Israel-Palestine conflict, expecting …
The AI Control Wars: Why Claude4 Needs 24,000 Tokens to Say Hello
Author(s): MKWriteshere Originally published on Towards AI. One model uses a novel-length instruction manual. Another uses 20 lines. The difference reveals the future of artificial intelligence. 24,000 tokens of hidden behavioral programming versus 20 lines of simple principles. Two AI systems. Two …
Why Your Agents Fail: It's not the Data, it's the Context
Author(s): Saleh Alkhalifa Originally published on Towards AI. Unlocking Smarter AI with Business Logic AI Agents are truly the latest “buzz” in tech circles. From developers, to product owners, to business leaders and even executives, everyone is suddenly talking about autonomous AI …
Recent Posts
