Harnessing Generative AI for Effective Digital Advertising Campaigns
Update: 2024-09-02
Description
Summary
In this episode of the AI Engineering podcast Praveen Gujar, Director of Product at LinkedIn, talks about the applications of generative AI in digital advertising. He highlights the key areas of digital advertising, including audience targeting, content creation, and ROI measurement, and delves into how generative AI is revolutionizing these aspects. Praveen shares successful case studies of generative AI in digital advertising, including campaigns by Heinz, the Barbie movie, and Maggi, and discusses the potential pitfalls and risks associated with AI-powered tools. He concludes with insights into the future of generative AI in digital advertising, highlighting the importance of cultural transformation and the synergy between human creativity and AI.
Announcements
Parting Question
The intro and outro music is from Hitman's Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/CC BY-SA 3.0
In this episode of the AI Engineering podcast Praveen Gujar, Director of Product at LinkedIn, talks about the applications of generative AI in digital advertising. He highlights the key areas of digital advertising, including audience targeting, content creation, and ROI measurement, and delves into how generative AI is revolutionizing these aspects. Praveen shares successful case studies of generative AI in digital advertising, including campaigns by Heinz, the Barbie movie, and Maggi, and discusses the potential pitfalls and risks associated with AI-powered tools. He concludes with insights into the future of generative AI in digital advertising, highlighting the importance of cultural transformation and the synergy between human creativity and AI.
Announcements
- Hello and welcome to the AI Engineering Podcast, your guide to the fast-moving world of building scalable and maintainable AI systems
- Your host is Tobias Macey and today I'm interviewing Praveen Gujar about the applications of generative AI in digital advertising
- Introduction
- How did you get involved in machine learning?
- Can you start by defining "digital advertising" for the scope of this conversation?
- What are the key elements/characteristics/goals of digital avertising?
- In the world before generative AI, what did a typical end-to-end advertising campaign workflow look like?
- What are the stages of that workflow where generative AI are proving to be most useful?
- How do the current limitations of generative AI (e.g. hallucinations, non-determinism) impact the ways in which they can be used?
- What are the stages of that workflow where generative AI are proving to be most useful?
- What are the technological and organizational systems that need to be implemented to effectively apply generative AI in public-facing applications that are so closely tied to brand/company image?
- What are the elements of user education/expectation setting that are necessary when working with marketing/advertising personnel to help avoid damage to the brands?
- What are some examples of applications for generative AI in digital advertising that have gone well?
- Any that have gone wrong?
- What are the most interesting, innovative, or unexpected ways that you have seen generative AI used in digital advertising?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on digital advertising applications of generative AI?
- When is generative AI the wrong choice?
- What are your future predictions for the use of generative AI in dgital advertising?
Parting Question
- From your perspective, what is the biggest barrier to adoption of machine learning today?
- Thank you for listening! Don't forget to check out our other shows. The Data Engineering Podcast covers the latest on modern data management. Podcast.__init__ covers the Python language, its community, and the innovative ways it is being used.
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The intro and outro music is from Hitman's Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/CC BY-SA 3.0
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