Ishan Gupta @code_igx
25 🇮🇳, Hustler @RITtigers NY 🇺🇸 | RnD on Quantum AI, Superintelligence & Systems | Ex- @Broadcom @VMware linkedin.com/in/ishangupta-… New York, USA Joined May 2017-
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Exactly
I finally understand how large language models actually work After reading the 2025 textbook “Foundations of LLMs” It blew my mind and cleared up years of confusion Here’s everything i learned (in plain english):
I just built my own multi-agent deep researcher! It uses a 100% local LLM and MCP. Here's an overview of how it works: - User submits a query - Web agent searches with Bright Data MCP tool - Research agents generate insights using platform-specific tools - Response agent…
𝗔𝗜 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗼𝗮𝗱𝗺𝗮𝗽. 👇 It is created with beginners in mind but can be easily adapted if you are proficient in some of the areas already. 𝘖𝘯 𝘢 𝘩𝘪𝘨𝘩 𝘭𝘦𝘷𝘦𝘭: 𝗙𝗼𝗰𝘂𝘀 𝗼𝗻 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀 throughout the journey, but…
Everyday human conversation can be filled with intent that goes unspoken, feelings implied but never named. How can AI ever really understand that? ✨ We’re excited to share our new work MetaMind — just accepted to #NeurIPS2025 as a Spotlight paper! A thread 👇 1️⃣ Human…
This one paper might kill the AI scaling hype. While Big Tech burns billions on massive datasets, researchers just achieved state-of-the-art agent performance using 78 samples. And it makes a scary amount of sense. Here's the full breakdown:
Federation of Agents This is a neat concept to convert static multi-agent coordination into dynamic capability-driven collaboration. Good use of semantic routing, DAG, smart clustering, MQTT, and a few other techniques. Multi-agent systems are great if you build them…
Language Models that Think and Chat Better Proposes a simple RL recipe to improve small open models (eg, 8B) that rivals GPT-4o and Claude 3.7 Sonnet (thinking). Pay attention to this one, AI devs! Here are my notes:
Embodied AI: From LLMs to World Models LLMs are really just the beginning. World models are the next frontier and will unlock areas like Embodied/Physical AI. These are essential components to achieve so-called AGI. While an important piece of the puzzle, LLMs alone cannot…
SimpleFold: Folding Proteins is Simpler than You Think "we introduce SimpleFold, the first flow-matching based protein folding model that solely uses general purpose transformer blocks. Protein folding models typically employ computationally expensive modules involving…
(1/6) triton kernels are a great way to understand ML models. but tutorials are scattered the learning method for me was jst to read real, high performance code so i wrote a blog which walkthroughs the design and intuitions behind FLA's softmax attention kernel 🧵also a thread
How does HNSW actually work? 𝗛𝗶𝗲𝗿𝗮𝗿𝗰𝗵𝗶𝗰𝗮𝗹 𝗡𝗮𝘃𝗶𝗴𝗮𝗯𝗹𝗲 𝗦𝗺𝗮𝗹𝗹 𝗪𝗼𝗿𝗹𝗱 (𝗛𝗡𝗦𝗪) is the algorithm behind most modern vector databases, but the algorithm can seem pretty complex. Here's the breakdown of how it works, and why so many vector databases use…
Thinking Augmented Pre-training "we propose Thinking augmented Pre-Training (TPT), a universal methodology that augments text with automatically generated thinking trajectories. Such augmentation effectively increases the volume of the training data and makes high-quality tokens…
China just broke the multimodal curse that's been plaguing AI for years. Alibaba dropped Qwen3-Omni and it's the first model that doesn't sacrifice anything to be multimodal. Every other AI model tanks when you add vision and audio. Text performance craters. Reasoning gets…
BIG claim. Giving an LLM just 78 carefully chosen, full workflow examples makes it perform better at real agent tasks than training it with 10,000 synthetic samples. "Dramatically outperforms SOTA models: Kimi-K2-Instruct, DeepSeek-V3.1, Qwen3-235B-A22B-Instruct and GLM-4.5. "…
Google introduces Test-Time Diffusion Deep Researcher Don't sleep on diffusion models. Test-Time Diffusion Deep Researcher (TTD-DR) is a deep research agent that models research writing as a diffusion process. Instead of static reasoning or bolted-on tools, the system drafts…

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