Vijay Gabale

Vijay Gabale

Co-Founder and CPO

Infilect
Vijay Gabale is the Co-founder and Chief Technology and Product Officer at Infilect Inc., a pioneering force in global retail visual intelligence. Leveraging cutting-edge Image Recognition and AI technologies, Infilect aims to revolutionize the retail landscape by addressing CPG brands' complex challenges in real-time.
 
Vijay Gabale earned his PhD from IIT Bombay, specializing in wireless platforms and AI systems. He has held critical roles in prominent global technology firms such as IBM Research, distinguishing himself as both a respected technocrat and a forward-thinking leader. Among his notable accomplishments are pioneering demonstrations of the world's inaugural voice network on Zigbee in the USA, groundbreaking contributions to Deep Neural Network architecture for multi-object detection, and his keynote address at the Heidelberg Laureate Forum in Germany, advocating for the societal advantages of AI. With over 6 patents granted and 15 research publications, he continues to drive innovation at the forefront of technology.

With a wealth of experience in product development and partnerships, complemented by deep expertise in Image Recognition Technology and Artificial Intelligence, Vijay Gabale spearheads transformative innovation for CPG brands, retailers, and global distributors and merchandising firms on a large scale.

Despite their impressive capabilities, Large Language Models (LLMs) still struggle with tasks that require understanding simple, generalized concepts, things that come naturally to humans. In this talk, we’ll walk through real-world yet intuitive examples where even state-of-the-art LLMs fail to apply basic logic.

But there’s a silver lining: with minimal, domain-specific fine-tuning, these models can rapidly learn the underlying rules and dramatically improve performance on the same tasks they initially fumbled. We’ll showcase case studies across BFSI, retail, and healthcare to demonstrate this transformation in action.

Whether you’re building GenAI-powered solutions or evaluating their deployment in critical workflows, this session will offer practical insights into pushing LLMs beyond their limitations using lightweight, high-impact fine-tuning techniques. A must-attend for AI practitioners who want to turn GenAI into a precision tool, not just a powerful one.

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Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More

Managing and scaling ML workloads have never been a bigger challenge in the past. Data scientists are looking for collaboration, building, training, and re-iterating thousands of AI experiments. On the flip side ML engineers are looking for distributed training, artifact management, and automated deployment for high performance

Read More
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