17 min listen
837: Why AI Training Datasets Should Resemble an Assembly Line
837: Why AI Training Datasets Should Resemble an Assembly Line
ratings:
Length:
26 minutes
Released:
Apr 24, 2019
Format:
Podcast episode
Description
A recent Deloitte survey found that 76 percent of executives believe AI will substantially transform their companies within the next three years, and MIT Sloan Management Review saw that 91% of all enterprises interviewed expect AI to deliver new business growth by 2023 in their recent study. With AI now considered critical to success, companies can be quick to jump on the AI bandwagon. While AI can save time and money while improving efficiency, organizations need to ensure they’re ready to add AI to their business strategy in 2019. I invited Nathaniel Gates, CEO, and co-founder of Alegion, to discuss what steps businesses can take to be AI-ready in 2019, including: Obtaining trustworthy, high-quality data required to effectively power AI initiatives – enlisting a solution to clean up, classify and label training data Being transparent with employees on AI impacts to the company Defining AI goals and ensuring you have the right data to support it Conducting cost/benefit analyses to ensure AI projects are worth your company’s investment
Released:
Apr 24, 2019
Format:
Podcast episode
Titles in the series (100)
753: The Startup Solving Big Problems in the Music and Media Industry: Qwire, the Music-for-Picture Licensing and Cue Sheet Reporting Software Firm, Receives $2M+ in Funding by The Tech Talks Daily Podcast