ML/AI Research
Hop develops novel algorithms for specific needs
Here at Hop, we use research-grade techniques from the machine learning community to build innovative products and solve real business problems.
This involves implementing and extending existing papers, and applying novel research techniques towards the proprietary data and challenges of our clients. Our researchers focus on rigor, practical performance, and thoughtful tradeoffs between principled and pragmatic.
We’ve done extensive work in computer vision, natural language processing, recommendation systems, knowledge graphs and generative AI, and are fluent in both traditional and deep-learning-based techniques.
Featured Case Study
Hop partnered with a sports and entertainment company innovating technology to track athlete performance, applying computer vision to track every limb of every player on a field. Our research and development of the 3D aspect of this technology played a key role in bringing it to the real world — it’s currently in use by a number of professional sports teams to improve performance.
Computer Vision for a Competitive Edge in Sports
For a startup at the cutting edge of innovation in the professional sports industry, we tackled the novel problem of tracking limbs in 3D, key to our client’s technology.
Looking to extend your organization’s ML/AI research capacity? Contact us to learn how Hop can help.