Chris Agarwal

  Large Concept Models (LCMs) are emerging as the next big thing, promising to take AI understanding to a whole new level. While Large Language Models (LLMs) process text token by token, LCMs work with entire concepts. Concepts represent higher-level ideas or actions. This allows for more nuanced comprehension and content generation. Imagine an AI that truly grasps the meaning behind your words, not just the words themselves! Key differences I've noticed: 1. LLMs excel at pattern recognition and text generation, ideal for tasks like summarization, chatbots etc. 2. LCMs shine in hierarchical reasoning and handling complex, long-form content. 3. LLMs require extensive training for new languages or modalities. 4. LCMs inherently support multiple languages and modalities out of the box. 5. Still looking for concrete research on this but LCMs may be less susceptible to hallucination! My take? LCMs are set to be game-changers in fields requiring deep conceptual understanding - think a...

Heard the term  'Founder’s mindset'  but always wondered what it actually means? This playbook from Sam Altman beautifully captures the startup journey. Great weekend read for anyone working in a company with a founder’s mindset. Check it out   here

This weekend, I decided to put 𝗩𝗶𝗯𝗲 𝗰𝗼𝗱𝗶𝗻𝗴 to the test. Using a 𝗚𝗲𝗻 𝗔𝗜 tool that shall rename unnamed as this is not a sponsored post, I created a prototype for a simple 𝗚𝗲𝗿𝗺𝗮𝗻 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗴𝗮𝗺𝗲 𝗳𝗼𝗿 𝗸𝗶𝗱𝘀 - and the results were cool! 🎮✨ Here’s why I think vibe coding is a game-changer for Solution Architects and innovators: • 𝗥𝗮𝗽𝗶𝗱 𝗣𝗿𝗼𝘁𝗼𝘁𝘆𝗽𝗶𝗻𝗴: Got an idea? Build it in hours, not weeks. Perfect for early pre-sales discussions when your product is still in development. • 𝗖𝗼𝗻𝗰𝗲𝗽𝘁 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 and Interactive Design: Quickly test ideas without diving into complex codebases. Also, think functional UI prototypes vs static mocks! • 𝗔𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆: Whether you're a seasoned coder or just starting out, vibe coding makes development approachable and fun. The process was seamless: I described my idea in plain English (AKA Prompt!), watched the Agent generate the code, tweaked it based on my needs, and voilà—a work...