667: Harnessing GPT-4 for your Commercial Advantage

GPT-4, augmenting human tasks with AI, and using GPT-4 commercially: Vin Vashishta speaks to host Jon Krohn about how to leverage GPT-4 and outperform your competitors in both speed and value. Learn how GPT-4 has outmatched its predecessors – and many skilled workers – in this latest iteration of large language models. This episode is brought to you by Pathway, the reactive data processing framework (https://pathway.com/?from=superdatascience), by Posit, the open-source data science company (https://posit.co/academy), and by epic LinkedIn Learning instructor Keith McCormick(linkedin.com/learning/instructors/keith-mccormick). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Using GPT-4 to screen for jobs [06:26] • A framework for improving systems with GPT [13:32] • Teaming, tooling and collaborating with GPT-4 [29:58] • How to accelerate data science with generative A.I. [45:36] • How to prepare for opportunities with GPT-4 [52:09] Additional materials: www.superdatascience.com/667

Om Podcasten

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.