Academia.edu Innovation, Technology & Agility

How is your team integrating AI and ML into the product development process, and what specific improvements have you seen as a result?

Many engineers use AI-powered coding assistants to speed up our development time. We have also used AI tools to quickly analyze and label data allowing us to perform analyses that uncover key business insights or fine-tune and deploy ML models much more rapidly than we could before.

What strategies are you employing to ensure that your systems and processes keep up with the rapid advancements in AI and ML?

At Academia.edu, we are always constantly building and learning. Engineers are encouraged to take time to explore, learn and keep up to date on the latest developments in AI/ML. 

We also have a very strong demo culture at Academia.edu where we are encouraged to take time to build small-scale demos of promising new technologies we find to validate the promise of those technologies. Many of our most exciting products and features started as small-scale demos an engineer built after learning about how a new technology could be applied at Academia.edu.

Can you share some examples of how AI/ML has directly contributed to enhancing your product line or accelerating time-to-market?

We have used AI/ML to build advanced search tools that allow researchers to search among millions of academic papers to identify papers and data. We also use AI to identify key researchers to invite to publish in our academic journals. Additionally, we use AI/ML to power reading recommendations that ensure our users can stay up to date on the latest research.