Unlocking the Unstructured with Generative AI: Trends, Models, and Future Directions.

Abstract: 

The exponential growth in computational power, alongside the advent of powerful GPUs and advancements in cloud computing, has ushered in a new era of generative artificial intelligence (AI), transforming the landscape of unstructured data extraction. Traditional methods such as text pattern matching, optical character recognition (OCR), and named entity recognition (NER) have been plagued by challenges related to data quality, process inefficiency, and scalability. However, the emergence of large language models (LLMs) has provided a groundbreaking solution, enabling the automated, intelligent, and context-aware extraction of structured information from the vast oceans of unstructured data that dominate the digital world. This talk delves into the innovative applications of generative AI in natural language processing and computer vision, highlighting the technologies driving this evolution, including transformer architectures, attention mechanisms, and the integration of OCR for processing scanned documents. We will also talk about future of generative AI in handling complex datasets.

Participants will gain insights into:

The fundamental challenges and solutions in unstructured data extraction.
The operational dynamics of Generative AI in extracting structured information.
Future of generative AI in unstructured data extraction
Practical insights into leveraging these technologies for real-world applications.

Designed for data scientists, AI researchers, and industry professionals, the talk aims to equip attendees with the knowledge to harness the power of Generative AI in transforming unstructured data into actionable insights, thereby driving innovation and efficiency across industries.

Session Outline:

The fundamental challenges and solutions in unstructured data extraction.
The operational dynamics of Generative AI in extracting structured information.
Future of generative AI in unstructured data extraction
Practical insights into leveraging these technologies for real-world applications.

Bio: 

Jay Mishra is a Data Solution leader and COO at Astera, a leading provider of code-free data solutions. With a career spanning over two decades, Jay has focused on achieving excellence in data architecture and software solutions. His expertise includes solution design, development, technical leadership, and product innovation, demonstrated through successful collaborations with companies like Wells Fargo, Raymond James, and Farmers Mutual. Beyond product development, Jay has excelled in driving transformative business initiatives, optimizing operations, and achieving significant financial success for organizations.

Leveraging technical acumen and strategic vision, Jay aims to empower organizations to maximize their data architecture potential and attain unparalleled financial success.

Open Data Science

 

 

 

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