[DataFramed AI Series #3] GPT and Generative AI for Data Teams (with Sarah Schlobohm)
With the advances in AI products and the explosion of ChatGPT in recent months, it is becoming easier to imagine a world where AI and humans work seamlessly together—revolutionizing how we solve complex problems and transform our daily lives. This is especially the case for data professionals.
In this episode of our AI series, we speak to Sarah Schlobohm, Head of AI at Kubrick Group. Dr. Schlobohm leads the training of the next generation of machine learning engineers. With a background in finance and consulting, Sarah has a deep understanding of the intersection between business strategy, data science, and AI. Prior to her work in finance, Sarah became a chartered accountant, where she honed her skills in financial analysis and strategy. Sarah worked for one of the world’s largest banks, where she used data science to fight financial crime, making significant contributions to the industry’s efforts to combat money laundering and other illicit activities. Sarah shares her extensive knowledge on incorporating AI within data teams for maximum impact, covering a wide array of AI-related topics, including upskilling, productivity, and communication, to help data professionals understand how to integrate generative AI effectively in their daily work.
Throughout the episode, Sarah explores the challenges and risks of AI integration, touching on the balance between privacy and utility. She highlights the risks data teams can avoid when using AI products and how to approach using AI products the right way. She also covers how different roles within a data team might make use of generative AI, as well as how it might effect coding ability going forward.
Sarah also shares use cases for those in non-data teams, such as marketing, while also highlighting what to consider when using outputs from GPT models. Sarah shares the impact chatbots might have on education calling attention to the power of AI tutors in schools.
Sarah encourages people to start using AI now, considering the barrier to entry is so low, and how that might not be the case going forward. From automating mundane tasks to enabling human-AI collaboration that makes work more enjoyable, Sarah underscores the transformative power of AI in shaping the future of humanity.
Whether you’re an AI enthusiast, data professional, or someoone with an interest in either this episode will provide you with a deeper understanding of the practical aspects of AI implementation.
1 view
387
108
1 month ago 00:06:26 8
Fireducks: Ускорь Pandas в 20 раз, изменив всего одну строчку кода!!!
4 months ago 04:22:13 1
Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn)
1 year ago 04:57:59 16
Pandas & Python for Data Analysis by Example – Full Course for Beginners
1 year ago 00:40:10 1
#147 The Past, Present & Future of Generative AI—Joanne Chen, General Partner at Foundation Capital
1 year ago 00:59:20 1
#145 Why AI will Change Everything—with Former Snowflake CEO, Bob Muglia
1 year ago 00:45:04 1
#68 The Future of Responsible AI (with Maria Luciana Axente)
1 year ago 01:02:38 1
[DataFramed AI Series #4] Building AI Products with ChatGPT (with Joaquin Marques)
1 year ago 00:42:48 1
[DataFramed AI Series #3] GPT and Generative AI for Data Teams (with Sarah Schlobohm)
1 year ago 00:47:11 1
[DataFramed AI Series #2] How Organizations can Leverage ChatGPT (with Noelle Silver Russell)
1 year ago 01:00:52 1
[DataFramed AI Series #1] ChatGPT and the OpenAI Developer Ecosystem (with Logan Kilpatrick)
2 years ago 00:09:24 6
Pandas 2.0 : Everything You Need to Know
2 years ago 00:14:12 5
Polars: The Next Big Python Data Science Library... written in RUST?
2 years ago 00:38:15 1
Juan Luis- Expressive and fast dataframes in Python with polars | PyData NYC 2022
2 years ago 00:18:39 2
Polars: The Super Fast Dataframe Library for Python ... bye bye Pandas?
2 years ago 00:54:57 1
ElixirConf 2022 - Chris Grainger - The Future AI Stack
2 years ago 00:48:10 1
Основы Pandas Python | Series, DataFrame И Анализ Данных
2 years ago 00:22:17 11
, , , | БИБЛИОТЕКА PANDAS 2 | МАШИННОЕ ОБУЧЕНИЕ
2 years ago 00:34:48 25
Pandas - разбор всех основных возможностей на реальном датасете
2 years ago 00:10:45 9
Object Detection in 10 minutes with YOLOv5 & Python!
2 years ago 00:09:47 1
How To Get Started in Machine Learning and AI : A Roadmap