Kolmogorov-Arnold Networks: KAN You Make It Work?
Although deep learning is a very new branch of...
Facial identification and verification for consumer and security applications.
Activity recognition and threat detection across camera views.
Spatial computing, gesture recognition, and gaze estimation for headsets.
Millions of identities and clothing options to train best-in-class models.
Simulate driver and occupant behavior captured with multi-modal cameras.
Simulate edge cases and rare events to ensure the robust performance of autonomous vehicles.
Together, we’re building the future of computer vision & machine learning
Facial identification and verification for consumer and security applications.
Activity recognition and threat detection across camera views.
Spatial computing, gesture recognition, and gaze estimation for headsets.
Millions of identities and clothing options to train best-in-class models.
Simulate driver and occupant behavior captured with multi-modal cameras.
Simulate edge cases and rare events to ensure the robust performance of autonomous vehicles.
Together, we’re building the future of computer vision & machine learning
Facial identification and verification for consumer and security applications.
Activity recognition and threat detection across camera views.
Spatial computing, gesture recognition, and gaze estimation for headsets.
Millions of identities and clothing options to train best-in-class models.
Simulate driver and occupant behavior captured with multi-modal cameras.
Simulate edge cases and rare events to ensure the robust performance of autonomous vehicles.
Together, we’re building the future of computer vision & machine learning
Facial identification and verification for consumer and security applications.
Activity recognition and threat detection across camera views.
Spatial computing, gesture recognition, and gaze estimation for headsets.
Millions of identities and clothing options to train best-in-class models.
Simulate driver and occupant behavior captured with multi-modal cameras.
Simulate edge cases and rare events to ensure the robust performance of autonomous vehicles.
Together, we’re building the future of computer vision & machine learning
AI will reshape and transform many industries. However, it is currently limited by the availability of accurate and diverse labeled training data.
Synthetic data, or computer-generated image data that models the real world, has the potential to provide nearly unlimited perfectly-labeled training data to enable the development of more capable models.
From autonomous vehicles, robotics, AR/VR, and AI assistants, the use-cases of synthetic data are broad.
EXCLUSIVE REPORT
This report, conducted by Synthesis AI in conjunction with Vanson Bourne, presents findings and takeaways from a survey of 100 senior technology executives on their perceptions of synthetic data, potential benefits and barriers of implementation, and what industry leaders think it will take to continue driving the adoption of synthetic data.