Compile the right research team
Assuming it’s your organization’s priority to do innovative AI research, the first step is to hire one or two researchers. At Unbabel, we did this early by hiring Ph. D.s and getting started quickly with research for a product that hadn’t been developed yet. Some researchers will build from scratch, and others will take your data and find a pre-existing model that fits your needs.
From there, you’ll need to hire research engineers or machine learning operations professionals. Research is only a small part of using AI in production. Research engineers will then release your research into production, monitor your model’s results, and refine it if it stops predicting well (or otherwise is not operating as planned). Often they’ll use automation to simplify monitoring and deployment procedures as opposed to doing everything manually.
None of this falls within the scope of a research scientist — they’re most used to working with the data sets and models in training. That said, researchers and engineers will need to work together in a continuous feedback loop to refine and retrain models based on actual performance in inference.
Choose the problems you want to solve
The CSET research cited above shows that 85% of AI labs in North America and Europe do basic AI research, and less than 15% focus on development. The rest of the world is different: Most labs in other countries, such as India and Israel, focus on growth.