![]() ![]() ![]() ![]() “Even though this may slow down the team a little bit, we need to be very thoughtful,” she said.įor example, the company puts articles generated by AI through an evaluation pipeline. While there is always a tension between running fast and running together, she explained, the company tries to keep those checks and balances, especially when it comes to responsible AI. Xu also emphasized that LinkedIn realizes that there are areas in the generative AI process that need to be done centrally. “Because of our collaborative culture, we encouraged different teams to share resources,” she said, so that they could quickly develop in a time when the number of developers who could access certain generative AI models was limited due to capacity. “We passed on learnings from team to team about quotas, access, prompting patterns and other best practices, so that they could better help one another,” she added. “We provided education at different levels, such as company-wide meetings, lunch-and-learn sessions and deeper education for those more heavily involved in AI development and R&D,” she said.īeing collaborative was also a big part of integrating and supporting generative AI. In addition, all LinkedIn employees needed to develop a better understanding of how large language models work, said Xu, including how to do prompt engineering, and what potential problems and limitations the models have. The company also brought together engineers for LinkedIn’s largest-ever internal Hackathon, featuring thousands of participants. That exploration was boosted by creating the LinkedIn Gateway, which allows access to OpenAI models and open-source models from Hugging Face, as well as offering LinkedIn’s Generative AI Playground, which allows engineers to explore Linkedin data with the advanced generative AI models from OpenAI and other sources. Xu said that her team early on prioritized an engineering philosophy “rooted in exploration over building a mature final product.” The maturity for the right features and experiences would occur over time, she explained, but the exploration was encouraged by putting generative AI technology in the hands of every engineer and product manager who was interested. >Follow VentureBeat’s ongoing generative AI coverage<< LinkedIn prioritized an engineering philosophy ![]()
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