Shutterstock strengthens partnership with Meta

Shutterstock strengthens partnership with Meta

Shutterstock, the top global creative platform for media companies and disruptive brands, will support Meta’s ongoing AI investment. The strengthened partnership demonstrates both firms’ dedication to leading AI innovation and the influence of Shutterstock’s vast content catalogue.

Shutterstock is the ideal partner for industry leaders investing in developing new experiences powered by AI because of its industry-leading library of high-quality content, focus on bringing new creative offerings to market, and expertise in creating a scaled ecosystem that pays and connects contributors to creators.

Meta intends to use these datasets to develop, train, and assess its machine-learning skills by utilizing Shutterstock’s library of millions of photos, videos, and songs.

“AI has the potential to drive an explosion of creativity,” said Paul Hennessy, Chief Executive Officer at Shutterstock.

“Shutterstock is expanding our long-standing relationship with Meta, which follows our partnerships with OpenAI and LG AI Research announced last year, to reinforce our mission to invest in technology that brings creative ideas to life faster. We want to automate the busy work required to complete creative projects and help creators understand how their work resonates. Our content will remain at the heart of these advancements on and off our platform, and we will continue to shape the future of generative AI in an ethical and artist-centric way,” he added.

Shutterstock-Meta partnership at the forefront of technology

Shutterstock’s larger strategic vision aims to be at the forefront of technology, design, content, and innovation. This expanded partnership with Meta is a component of that goal.

As one of the first businesses to compensate artists for their work in developing machine learning models, Shutterstock has established itself as a reliable business partner for those entering the market by ensuring the ethical production and licensing of content through an open IP transfer.


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