Dipankar Sarkar

Building for the present, planning for the future

A technology leader with over 15 years of experience pioneering solutions at the intersection of AI, robotics, and distributed systems. Recognized for architecting transformative platforms including AI agents for global supply chains, LLM-powered robotics systems, and Web3 infrastructure. Combines deep technical expertise in machine learning, distributed systems, and cloud architecture with strategic business acumen and proven leadership skills.

About me

Recent

Optimizing ARM Builds in CI/CD Pipelines: Challenges and Solutions

4 mins

Technology Software Engineering Cloud Infrastructure DevOps ARM Architecture CI/CD DevOps Software Development Build Optimization QEMU Cross-Compilation Cloud Computing Containerization Performance Tuning

Optimizing ARM Builds in CI/CD Pipelines: Challenges and Solutions #In the ever-evolving landscape of software development and deployment, the rise of ARM-based architectures has introduced new challenges to Continuous Integration and Continuous Deployment (CI/CD) pipelines.

RoboGPT: Transforming Industries and Shaping the Future of Human-Robot Collaboration

4 mins

Technology Impact Industry Innovation RoboGPT Industrial Automation Human-Robot Collaboration AI in Manufacturing Future of Work

As we approach the mid-point of 2024, it’s time to reflect on the transformative impact that RoboGPT has had across various industries since its introduction. As the former Head of AI & Platform at Orangewood Labs, I’m proud to share how our groundbreaking technology is reshaping the landscape of human-robot collaboration and setting new standards for industrial automation.

EdgeML and the Future of Robotics: Building the Next-Generation SDK and Platform

4 mins

Technology Innovation Software Development EdgeML Robotics SDK IoT Distributed Computing AI in Robotics

I’m thrilled to share insights into one of our most ambitious projects at Orangewood Labs: the development of a next-generation SDK and platform for robotics, powered by EdgeML. This initiative is set to redefine how we approach robot programming and management, bringing unprecedented levels of intelligence and efficiency to robotic systems.

AutoInspect and AutoSpray: ML-Driven Precision in Industrial Robotics

4 mins

Artificial Intelligence Industrial Innovation Machine Learning Industrial Robotics Computer Vision Automation Quality Control

As we enter 2024, I’m excited to share the remarkable progress we’ve made at Orangewood Labs with our AutoInspect and AutoSpray solutions. These innovative systems represent a significant leap forward in applying machine learning and computer vision to industrial robotics, particularly in the realms of quality control and precision manufacturing.

Revolutionizing Online Gaming: AI-Driven Matchmaking for Hike's Rush Platform

3 mins

Artificial Intelligence Gaming Technology Machine Learning Gaming Matchmaking Algorithms User Experience Python

As the leader of the Machine Learning team at Hike Limited, I spearheaded the development of an innovative AI-driven matchmaking system for Rush, Hike’s real-money gaming network. Our goal was to create a fair, engaging, and highly personalized gaming experience by automatically matching players based on their skill levels, gaming behavior, and overall user experience.