With a unique visual and code-free approach to labeling images and training computer vision deep learning models, Platform.ai accelerates the path to computer vision for both AI experts and domain experts who know nothing about AI. The company, headquartered in San Francisco, was founded in 2017 by AI product visionary Arshak Navruzyan and deep learning guru Jeremy Howard.
Jeremy first showed the power of Platform.ai in a 2015 TEDx Talk, where he built a model in 15 minutes that can classify over a million unlabeled points to 99% accuracy (something that previously could take days or weeks). Our motivation was to build an application that non-technical people can use to train computer vision models, and would accelerate the process for those trained in AI.
An extensive amount of research work has gone into platform including leveraging human perception, active learning, transfer from pre-trained nets, and noise-resilient training. We want to use the labeler's time in the most productive way and have the model learn from every aspect of the human interaction.
We believe this approach is broadly applicable to many industry use cases including autonomous driving, facial recognition, defense, product recommendations, medical imaging diagnostics, industrial quality control, etc. and that platform.ai can significantly accelerate the development of models in all these areas by providing pre-trained networks and allowing collaboration among domain experts.
Want to build a tool that is accelerating the worldwide adoption of computer vision?
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