Back

Speaker "Ganapathi Pulipaka" Details Back

 

Topic

GPT Paper-Reader

Abstract

Generative AI has been exploding and unleashing content generation and making tremendous strides in the past few years, with researchers exploring the capabilities of machine learning models and discovering new techniques and architectures that have the potential to transform the way we create and interact with media. A range of models that can generate text, images, and music, among other things, have been developed by researchers and developers. This article will examine some of the most notable generative AI models, including their timelines and summaries. Generative AI trained on the language of data has been a catalyst in many fields, such as language processing, computer vision, and music generation, in a wide number of industries, such as healthcare and retail. 
 
In this session we'll go through various LLMs and then present a practical GPT to chunk the PDF paper into manageable sections for detailed reading and generate concise summaries for each segment. By maintaining context from previous sections within the token limit, it enhances comprehension. Before diving into the paper, you can outline specific questions in the prompt. This approach allows GPT to extract the most important information during its reading and summarizing process, leading to superior outcomes. After summarizing all parts, you will receive comprehensive answers to your inquiries based on the consolidated summaries. By default, the initialized prompt will target essential points such as: These inquiries are tailored for research articles within the computer science domain. Upon completion of the paper review, feel free to engage with the question() interface to ask further questions.

Profile

Dr. Ganapathi Pulipaka is a Chief Data Scientist at Accenture for AI strategy, architecture, application development of Machine learning, Deep Learning algorithms with experience in deep learning reinforcement learning algorithms, IoT platforms, Python, R, and TensorFlow, Big Data, IaaS, IoT, Data Science, Blockchain, Apache Hadoop, Apache Kafka, Apache Spark, Apache Storm, Apache Flink, SQL, NoSQL, Mathematics, Data Mining, Statistical Framework, SIEM with SAP Cloud Platform Integration, AWS, Azure, GCP with 9+ Years of AI Research and Development Experience and 20+ years of experience as SAP Technical Development and Integration Lead with 30 project implementations for Fortune 100 companies. He is a PostDoc Research Scholar in Machine Learning, Big Data Analytics, Robotics, and Data Science as part of Doctor of Computer Science Program from Colorado Technical University, Colorado Springs. He also holds another PhD in Business Administration, Data Analytics, and Enterprise Resource Management from California University, Irvine. He is also a bestselling author of multiple books on big data analytics, machine learning, robotics, and data science and leading contributor of machine learning articles for various publications.