EP62: Thomas W. Ives, Lead Data Scientist: This is an incredible time to be in AI
Jun 30, 2020 ·
32m 16s
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Description
“This is a conviction and I could be wrong, but I believe that the corporations that replace humans with AI are going to regret it. It’s a bad move. But...
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“This is a conviction and I could be wrong, but I believe that the corporations that replace humans with AI are going to regret it. It’s a bad move. But the companies that use AI to remove monotony from smart individuals and then advance their abilities with training. Those are the companies that are going to win, and they'll progress humanity the best,”
This is a conversation with Thom Ives. To serve his passion to build things, Thom has continually sought, throughout his life, to grow his predictive modelling skills. He hopes to positively impact humanity with his creations, his implementations, and his teachings on the same.
In this episode, Thom talks about what he hopes to see happen in data science during his lifetime, and shares advice for new practitioners entering the field of AI. He explains why facial recognition AI can be so racially biased, and what politicians need to know about machine learning. Thom shares what changes he would like to see in educational approaches and why we need to teach our children about preparing data for models as early as possible.
show less
This is a conversation with Thom Ives. To serve his passion to build things, Thom has continually sought, throughout his life, to grow his predictive modelling skills. He hopes to positively impact humanity with his creations, his implementations, and his teachings on the same.
In this episode, Thom talks about what he hopes to see happen in data science during his lifetime, and shares advice for new practitioners entering the field of AI. He explains why facial recognition AI can be so racially biased, and what politicians need to know about machine learning. Thom shares what changes he would like to see in educational approaches and why we need to teach our children about preparing data for models as early as possible.
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Author | Richard Foster-Fletcher |
Organization | Richard Foster-Fletcher |
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