Targeting AI
Targeting AI
Podcast Description
Hosts Shaun Sutner, TechTarget News senior news director, and AI news writer Esther Ajao interview AI experts from the tech vendor, analyst and consultant community, academia and the arts as well as AI technology users from enterprises and advocates for data privacy and responsible use of AI. Topics are related to news events in the AI world but the episodes are intended to have a longer, more ”evergreen” run and they are in-depth and somewhat long form, aiming for 45 minutes to an hour in duration. The podcast will occasionally host guests from inside TechTarget and its Enterprise Strategy Group and Xtelligent divisions as well and also include some news-oriented episodes featuring Sutner and Ajao reviewing the news.
Podcast Insights
Content Themes
Focuses on the evolving landscape of artificial intelligence, covering key topics such as generative AI adoption in industries, ethical implications of AI, and real-world applications with episodes discussing the impact of AI in law, data strategy, and enterprise solutions.
Hosts Shaun Sutner, TechTarget News senior news director, and AI news writer Esther Ajao interview AI experts from the tech vendor, analyst and consultant community, academia and the arts as well as AI technology users from enterprises and advocates for data privacy and responsible use of AI. Topics are related to news events in the AI world but the episodes are intended to have a longer, more ”evergreen” run and they are in-depth and somewhat long form, aiming for 45 minutes to an hour in duration. The podcast will occasionally host guests from inside TechTarget and its Enterprise Strategy Group and Xtelligent divisions as well and also include some news-oriented episodes featuring Sutner and Ajao reviewing the news.
The explosion of AI in 2022 coincided with the introduction of image-generating models such as Dall-E, which were met with controversy. However, in recent years, AI companies have partnered with legacy image vendors such as Getty Images and Shutterstock. On this episode of Targeting AI, Daniel Mandell of Shutterstock explains how data licensing is changing in the age of generative AI. Mandell explains how Shutterstock has evolved from a stock content company into a data licensing partner for model training, inference and increasingly agentic workflows.
We discuss how Shutterstock approaches creator compensation, how it filters synthetic data, why inference is becoming as important as training, and why high-quality rights-cleared content still matters even as image generators improve.
Featuring: Daniel Mandell, senior vice president of data licensing and AI at Shutterstock
In this episode, we cover how:
- Shutterstock’s AI business grew from image licensing into a broader multimodal data licensing model covering video, audio, 3D, fonts and templates.
- The company now serves both model training and inference use cases, with inference becoming a major part of the business.
- Demand has shifted from broad volume requests to highly specific, niche, and metadata-rich content for real-world applications.
- Mandell says Shutterstock is not trying to be a model builder, but rather a content and data partner that helps customers solve practical AI problems.
- The company sees its role as combining stock assets with AI-generated content to offer more optionality to customers.
- Compensation for creators remains an open challenge, but Shutterstock says it is trying to ensure contributors stay part of the AI ecosystem and continue to monetize their work.
- Synthetic data is useful for edge cases, but Mandell argues models still need real rights-cleared human-made data to perform well.
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References:
And Now it Begins: Shutterstock Unveils Text-to-Image AI Platform
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