This episode is about Activepieces.com, a no-code, open-source tool that creates workflow automation. (Not a sponsored content)
The show quickly introduces the book "Demystifying Business Data Visualization" by Dr. M. Ramasubramaniam and Mr. Daniel Peter. Here is the link for full book:
Amazon.com: DEMYSTIFYING BUSINESS DATA VISUALIZATION , Ramasubramaniam , Dr. M., Peter, Mr. Daniel, eBook - Amazon.com
Amazon.in:
In this episode, we review an arXiv paper titled "MILDSUM: A NOVEL BENCHMARK DATASET FOR MULTILINGUAL SUMMARIZATION OF INDIAN LEGAL CASE JUDGMENTS" by DEBTANU DATTA , SHUBHAM SONI , RAJDEEP MUKHERJEE and SAPTARSHI GHOSH". https://arxiv.org/pdf/2310.18600
Welcome to today's episode of AI Sphere, where we'll be exploring the recent controversial topic in the world of AI -The artificial general intelligence, or AGI. AGI refers to a hypothetical AI system that possesses the ability to understand, learn, and apply knowledge across a wide range of tasks, much like human intelligence. It has sparked intense debates about its potential impact on job displacement and broadly on the society.
In this episode, we compare the performance of ChatGPT turbo 0613 with ChatGPT turbo 1106. We experiment with API based RAG system, chatting with pdfs which address the area of machine learning fairness and present qualitative results of the comparison. Enjoy listening!
In this episode, we will explore the process of fine-tuning GPT 3.5, an advanced language model. We will introduce the concepts of zero-shot, few-shot, and multi-shot learning, and discuss how they relate to fine-tuning. We will also cover the use cases for GPT 3.5 fine-tuning and the steps involved in the fine-tuning process. Fine-tuning allows developers to customize GPT 3.5 Turbo to suit different use cases, improving its performance on specialized tasks. With this podcast, you will gain a comprehensive understanding of the latest developments in AI and how to unlock its full potential.
