LLMs

VideoRAG: Redefining Long-Context Video Comprehension

Discover VideoRAG, a framework that fuses graph-based reasoning and multi-modal retrieval to enhance LLMs' ability to understand multi-hour videos efficiently.

Agentic AI, LLMs, RAGs, Video Analysis, Vision Language Models

Video-RAG: Training-Free Retrieval for Long-Video LVLMs

Learn how Video-RAG boosts training-free and low-compute long-video understanding by pairing OCR, ASR, and open-vocabulary detection with any long-video LVLMs.

RAGs, VLMs

Object Detection and Spatial Understanding with VLMs ft. Qwen2.5-VL

What if object detection wasn't just about drawing boxes, but about having a conversation with an image? Dive deep into the world of Vision Language Models (VLMs) and see how

Computer Vision, LLMs, NLP, Vision Language Models, VLMs

Inside Sinusoidal Position Embeddings: A Sense of Order

In the groundbreaking 2017 paper “Attention Is All You Need”, Vaswani et al. introduced Sinusoidal Position Embeddings to help Transformers encode positional information, without recurrence or convolution. This elegant, non-learned

Language Models, LLMs, NLP

Inside RoPE: Rotary Magic into Position Embeddings

Self-attention, the beating heart of Transformer architectures, treats its input as an unordered set. That mathematical elegance is also a curse: without extra signals, the model has no idea which

Language Models, LLMs, NLP

FineTuning Gemma 3n for Medical VQA on ROCOv2

What if a radiologist facing a complex scan in the middle of the night could ask an AI assistant for a second opinion, right from their local workstation? This isn't

Computer Vision, Generative AI, Generative Models, LLMs, Multimodal Models, NLP, Transformer Neural Networks, Vision Language Models, Vision Transformer, VLMs

SmolLM3 Blueprint: SOTA 3B-Parameter LLM

In the evolving landscape of open-source language models, SmolLM3 emerges as a breakthrough: a 3 billion-parameter, decoder-only transformer that rivals larger 4 billion-parameter peers on many benchmarks, while natively supporting

Language Models, LLMs

Building an Agentic Browser with LangGraph: A Visual Automation and Summarization Pipeline

Developing intelligent agents, using LLMs like GPT-4o, Gemini, etc., that can perform tasks requiring multiple steps, adapt to changing information, and make decisions is a core challenge in AI development.

Agentic AI, Computer Vision, Generative AI, Generative Models, LLMs, VLMs

SigLIP 2: DeepMind’s Multilingual Vision-Language Model

SigLIP-2 represents a significant step forward in the development of multilingual vision-language encoders, bringing enhanced semantic understanding, localization, and dense feature extraction capabilities. Built on the foundations of SigLIP, this

Computer Vision, Generative AI, LLMs, NLP, VLMs

MedGemma: Google’s Medico VLM for Clinical QA, Imaging, and More

Imagine an AI co-pilot for every clinician, capable of understanding both complex medical images and dense clinical text. That's the promise of MedGemma, Google's new Vision-Language Model specifically trained for

Generative AI, LLMs, Vision Language Models, VLMs

Getting Started with Qwen3 – The Thinking Expert

Discover Qwen3, Alibaba’s open-source thinking LLM. Switch between fast replies and chain-of-thought reasoning with 128 K context, and MoE efficiency. Learn how to use and Fine Tune.

Generative AI, Language Models, LLMs, NLP

Unsloth: A Guide from Basics to Fine-Tuning Vision Models

Unsloth has emerged as a game-changer in the world of large language model (LLM) fine-tuning, addressing what has long been a resource-intensive and technically complex challenge. Adapting models like LLaMA,

Generative Models, LLMs, Model Optimization