AI Research
Claude Code and the Shift from Prompting to Compiling
Shift from chaotic chat loops to deterministic agentic workflows. Discover how Claude Code and MCP are transforming LLM interaction into programmable pipelines.
Author
Author: Praveen Pandey
Software engineer and AI researcher with 10 years of experience in machine learning systems and distributed computing. Writes about LLMs, agentic AI architectures, developer tooling, and open-source ML.
AI Research
Google Multimodal RAG and the Risk of Semantic Dilution
Google's Gemini API File Search update introduces native multimodal RAG, merging text and image embeddings into a single semantic space for advanced AI agents.
LLMs
Google Adds Multimodal Support to Gemini API File Search
Google's Gemini API File Search evolves into a native multimodal RAG engine, integrating Gemini Embedding 2 for unified text and visual data retrieval.
AI Research
Google’s Multimodal RAG: File Search Power and Pitfalls
Google's Gemini Embedding 2 unifies text, image, and audio into a single semantic space, revolutionizing multimodal RAG pipelines and reducing engineering overhead.
LLMs
When Failed Startups Sell Corporate Data for AI Training
Unstructured corporate archives and failed company data are becoming the new gold rush for training context-aware LLMs and agentic workflows.
AI Research
DeepMind and NVIDIA Unveil New AI Models and Robotics
Google DeepMind launches Gemini 3.1 Flash and Gemma 4, alongside NVIDIA collaborations to advance agentic workflows and embodied robotics reasoning.
AI Research
Scaling AI Agents: Compute Deals and Efficient Code
Scaling AI agents requires a dual focus on massive compute capacity and non-blocking, efficient code architectures like async/await to handle production workloads.
Google
Gemini Nano in Chrome: AI Features Deployed in Silence
Google Chrome's silent 4GB Gemini Nano model downloads raise critical concerns regarding user consent, privacy laws, and on-device AI governance.
AI Research
Chrome’s Silent 4GB AI Download Raises Ethical Questions
Google Chrome's unannounced 4GB AI model download raises critical ethical concerns regarding user consent and the hidden costs of on-device inference.
LLMs
Unsloth + NVIDIA: VRAM-Efficient Fine-Tuning in Production
Optimize LLM fine-tuning by bypassing VRAM limitations using Unsloth and NVIDIA's custom CUDA kernels for faster, memory-efficient model training.