AI/ML13 min read
GLM-5.2 Deep Dive: Z.ai's 744B MoE Model with 1M Context Window
An in-depth analysis of Z.ai's GLM-5.2. The 744B parameter MoE model with 1M context window, dual thinking modes, and open weights under MIT license.
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AI/ML, robotics & automation and computer vision project notes by Kukil Kashyap Borgohain
NVIDIA LocateAnything-3B: Revolutionizing Visual Grounding with Parallel Decoding
Computer Vision
Explore the architecture and real-world performance of NVIDIA's new LocateAnything-3B, featuring its groundbreaking Parallel Box Decoding for high-speed object localization.
10 min read
Read Full Article Latest Blog Posts
Explore my latest thoughts and tutorials
Automation10 min read
Building an Autonomous Agentic Blog Pipeline
Upgrading manual blogging workflow into a fully autonomous agentic pipeline, the failures encountered, and the architecture that fixed them.
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AI/ML10 min read
Gemma 4: Deep Dive into Encoder-Free Architecture and Local Agentic Capabilities
An in-depth analysis of the Gemma 4 model family, exploring its new encoder-free architecture, native tool calling, and local deployment requirements.
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Computer Vision12 min read
OpenCV 5.0: What Actually Changed and Why It Matters
OpenCV 5.0 rewrites the DNN engine, pushes ONNX coverage past 80%, runs VLMs natively, and drops the C API. A developer's take on what's real, what's promising, and where the gaps still are.
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AI/ML5 min read
From 2B to 31B: The Evolution of Google's Gemma Models
A deep dive into the architectural shifts, parameter sizes, and deployment challenges of the DeepMind Gemma family from V1 to V4.
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AI/ML13 min read
The Landscape of Small LLMs and VLMs (Under 12B)
A practical catalog of small language and vision models optimized for edge inference.
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What this blog covers
Project write-ups, technical deep dives, and working notes. Everything here was built, tested, or broken by hand.
AI & Machine Learning
LLM fine-tuning, local inference, model reviews, GenAI application architecture, and running open-weight models.
Computer Vision
Object detection, OpenCV projects, YOLO deployments, vision model training, and edge AI on constrained hardware.
Microcontrollers & IoT
ESP32 and Arduino projects, embedded AI, hardware integration, sensor wiring, and IoT application builds.
ML Fundamentals
The math and theory behind machine learning — probability, Bayesian thinking, kernel methods, and model internals explained clearly.
Automation
Workflow automation, scripting, process optimization, and developer tooling for cutting down repetitive work.
3D Printing
Ender 3 setup guides, slicer settings, bed calibration, print failure detection, and monitoring dashboards.
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