679: The A.I. and Machine Learning Landscape, with investor George Mathew

Generative AI, MLOps, and making smart investments in AI: This week’s episode is critical listening for AI investors and generative AI creators. AI investor George Mathew talks with host Jon Krohn about the emerging generative AI stack, the critical elements of MLOps to ensure a scalable model, and the tools developers can use for a saleable product. This episode is brought to you by Posit, the open-source data science company (posit.co), by AWS Inferentia (https://go.aws/3zWS0au), and by Anaconda, the world's most popular Python distribution (superdatascience.com/anaconda). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Venture capital’s role in the technology startup ecosystem [05:59] • How RLHF helps UI become more intuitive [12:53] • The four layers of the generative AI stack [34:16] • The risks for generative AI business founders and investors [46:50] • How MLOps drive best practices and help implementation [56:33] • The importance of PLG (Product Lead Growth) [1:04:15] • How generative AI tools will impact the labor market [1:17:34] Additional materials: www.superdatascience.com/679

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.