833: The 10 Reasons AI Projects Fail, with Dr. Martin Goodson

Martin Goodson speaks to Jon Krohn about what he would add to his viral article “Ten Ways Your Data Project is Going to Fail”, why practitioners always need to be present at AI policy discussions, and Evolution AI’s breakthroughs in computer vision and NLP. This episode is brought to you by epic LinkedIn Learning instructor Keith McCormick. Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (04:25) What Evolution AI does  (11:41) How to maintain accuracy in large infrastructures (21:22) How to cultivate innovation and creativity while meeting market demands (24:27) Potential knowledge gaps for machine learning practitioners (30:57) Martin’s viral article, “Ten Ways Your Data Project is Going to Fail” (59:54) Strategies for the UK to become a key player in AI Additional materials: www.superdatascience.com/833

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.