Empowering industry with world-class AIML research tools and fostering innovation for real-world impact
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"AIML Shop has been a fantastic opportunity to productize research and put new technolgy out there for users. With bold programs like this, AIML Engineering can take bigger steps to sustainable funding models and create a lasting impact with the technical excellence and synergies available here at the AIML."
AnyTrack provides a powerful way of generating labeled data in the wild at scale. Thereby, it democratizes the domain of data collection to a plethora of machine learning-driven computer vision applications via its novel self-supervision technique.
Segmesh transforms 3D surface understanding, accelerating innovation in VR/AR, autonomous systems, and design with its advanced parsing technology. It simplifies complex 3D data manipulation, opening new horizons for creative and technical applications across industries.
Class Tree enables hierarchical classification and achieves better performance than the traditional flat classifiers for problems that need fine grained classifications.
NoisyLabels elevates machine learning accuracy by mastering the art of learning from imperfect data, making AI models more resilient and effective across critical sectors like healthcare and autonomous technology. It transforms data noise into a strategic advantage, ensuring robust performance in real-world applications.
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AIML Shop mission
The AIML Shop program is designed to enhance the global impact of AIML's world-class research by making advanced tools, such as machine learning models and software solutions, more accessible and reliable for industry adoption. This effort not only promotes the practical application of research but also supports AIML researchers and engineers in expanding their entrepreneurship skills and creating a track record of product development.
By fostering entrepreneurialism within the research community, AIML Shop aims to create a sustainable revenue stream that rewards innovation, supports future commercialization efforts, and solidifies AIML's position as a leader in translating academic research into real-world solutions.
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