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Sam Charrington (@samcharrington, Host of TWIML & AI Podcast) talks about AI & ML trends in 2020, frameworks to understand usage patterns, hot new technology to explore, how long projects take to succeed, and the inherent bias built into every AI & ML model.
SHOW: 437
SHOW SPONSOR LINKS:
CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotw
SHOW NOTES:
Topic 1 - Welcome back to the show. Let’s start with the broad set of TWIML activities that you’re working on these days.
Topic 2 - You focus on AI & ML every week, across a lot of different domains and usages. It’s a broad scope. If you had to focus it on Enterprise/Business leaders, how do you structure a conversation around how to align business opportunity and technology choices?
Topic 3 - What are some of the most commonly used technologies being deployed around AI/ML systems? Any big shifts over the last couple of years?
Topic 4 - You’ve been around Cloud Computing and DevOps communities, which required companies to go through some people/process change to achieve success. What are the people/process changes that you typically see with AI/ML environments?
Topic 5 - If somebody asked you how they can put a timeline on when they’ll see value around their AI/ML, is that a realistic ask? What are the factors that go into achieving success in AI/ML projects?
Topic 6 - What are some of the interesting usages of AI/ML that you’ve seen in use recently?
Topic 7 - There has been quite a bit of discussion recently about bias in AI/ML algorithms. Can you explain what this means and how it could impact the system’s decision making?
FEEDBACK?
By Massive Studios4.6
147147 ratings
Sam Charrington (@samcharrington, Host of TWIML & AI Podcast) talks about AI & ML trends in 2020, frameworks to understand usage patterns, hot new technology to explore, how long projects take to succeed, and the inherent bias built into every AI & ML model.
SHOW: 437
SHOW SPONSOR LINKS:
CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotw
SHOW NOTES:
Topic 1 - Welcome back to the show. Let’s start with the broad set of TWIML activities that you’re working on these days.
Topic 2 - You focus on AI & ML every week, across a lot of different domains and usages. It’s a broad scope. If you had to focus it on Enterprise/Business leaders, how do you structure a conversation around how to align business opportunity and technology choices?
Topic 3 - What are some of the most commonly used technologies being deployed around AI/ML systems? Any big shifts over the last couple of years?
Topic 4 - You’ve been around Cloud Computing and DevOps communities, which required companies to go through some people/process change to achieve success. What are the people/process changes that you typically see with AI/ML environments?
Topic 5 - If somebody asked you how they can put a timeline on when they’ll see value around their AI/ML, is that a realistic ask? What are the factors that go into achieving success in AI/ML projects?
Topic 6 - What are some of the interesting usages of AI/ML that you’ve seen in use recently?
Topic 7 - There has been quite a bit of discussion recently about bias in AI/ML algorithms. Can you explain what this means and how it could impact the system’s decision making?
FEEDBACK?

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