Episode 11: Machine Learning Realities and Opportunities with Jeremy Barnes (Part 1)
Everyone’s talking about machine learning and how it can be applied to solving some of today’s top business problems. CTOs know that it’s becoming an imperative for building successful software products. But is it really the answer and, if so, how can companies overcome the many execution gaps that exist? In this first episode of a two-part series, Georgian Partners’ Madalin Mihailescu talks with Jeremy Barnes, the Founder and CEO of Datacratic to get some unique perspectives about both the technological and business sides of machine learning. You’ll hear about: Jeremy’s definition of machine learning (5:42) The other areas of pattern recognition fall under machine learning (6:46) Why businesses should care about machine learning (9:17) How machine learning is evolving as a tool for solving business problems (12:45) Realistic applications for machine learning today versus expectations (13:39) The complexities of applying machine learning (16:27) The current state for ensuring model quality in production (19:16) Incorporating safeguards into systems (21:12)
The Georgian Impact Podcast | AI, ML & More · Georgian
Audio is streamed directly from the publisher (episodes.castos.com) as published in their RSS feed. Play Podcasts does not host this file. Rights-holders can request removal through the copyright & takedown page.
Show Notes
Everyone’s talking about machine learning and how it can be applied to solving some of today’s top business problems. CTOs know that it’s becoming an imperative for building successful software products. But is it really the answer and, if so, how can companies overcome the many execution gaps that exist? In this first episode of a two-part series, Georgian Partners’ Madalin Mihailescu talks with Jeremy Barnes, the Founder and CEO of Datacratic to get some unique perspectives about both the technological and business sides of machine learning.
You’ll hear about:
- Jeremy’s definition of machine learning (5:42)
- The other areas of pattern recognition fall under machine learning (6:46)
- Why businesses should care about machine learning (9:17)
- How machine learning is evolving as a tool for solving business problems (12:45)
- Realistic applications for machine learning today versus expectations (13:39)
- The complexities of applying machine learning (16:27)
- The current state for ensuring model quality in production (19:16)
- Incorporating safeguards into systems (21:12)