OpenAI’s o1-preview: the First LLM That Can Answer My Questions
OpenAI’s o1-preview has been all the buzz lately. While...
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.
OpenAI’s o1-preview has been all the buzz lately. While...
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.
OpenAI’s o1-preview has been all the buzz lately. While...
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.
OpenAI’s o1-preview has been all the buzz lately. While...
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.
OpenAI’s o1-preview has been all the buzz lately. While...
Together, we’re building the future of computer vision & machine learning
At Synthesis AI, we are dedicated to the highest ethical standards in the field of artificial intelligence. We recognize the critical role that training data plays in developing AI systems. Our commitment is to provide our customers with high-quality, diverse, and representative synthetic data while upholding the following principles:
Privacy and Data Protection: We prioritize the privacy and security of individuals by ensuring that any personal or sensitive data used in the creation of synthetic data is anonymized and protected per applicable laws and regulations. To the extent that human beings are used as source material for developing synthetic datasets, we follow all applicable labor and privacy laws. Synthesis AI implements robust technical and organizational measures to safeguard data against unauthorized access, disclosure, alteration or destruction.
Fairness and Bias Mitigation: We strive to eliminate biases in synthetic data by employing inclusive methodologies during the data generation process, in collaboration with our customers. We are committed to working closely with our customers in controlling bias in machine learning models.
Transparency and Traceability: We maintain transparent practices by clearly documenting our data generation techniques, disclosing any limitations or known biases, and providing customers with insights into the synthetic data creation process. We also strive to ensure traceability by keeping records of the data generation process, methodologies and any modifications applied.
Compliance and Legal Frameworks: We adhere to all relevant legal and regulatory requirements, including copyright laws, labor laws, intellectual property rights, and data protection regulations, to ensure that our operations are conducted lawfully and responsibly.
Ethical Use of Synthetic Data: We emphasize the responsible and ethical use of synthetic data, encouraging our customers to employ the generated data for lawful and beneficial purposes while avoiding any misuse, harm, or infringement on individual rights. We promote ethical guidelines and provide guidance to our customers on responsible AI practices, ensuring that the synthetic data is used in a manner that respects privacy, diversity and the well-being of individuals and society at large.
Continuous Improvement and Innovation: We are committed to ongoing research and development to advance the quality and utility of synthetic data. We actively seek feedback from customers, partners and experts to continually improve our processes and methodologies to align with the evolving best practices and ethical standards in the industry and stay at the forefront of responsible AI innovation.
By upholding these ethical principles, we aim to foster trust, integrity, and accountability in the AI ecosystem while contributing to the advancement of ethical and responsible AI applications.