Reality Defender
About Reality Defender
Reality Defender provides accurate, multi-modal AI-generated media detection solutions to enable enterprises and governments to identify and prevent fraud, disinformation, and harmful deepfakes in real time.
A Y Combinator graduate, Comcast NBCUniversal LIFT Labs alumni, and backed by DCVC , Reality Defender is tdhe first company to pioneer multi-modal and multi-model detection of AI-generated media. Our web app and platform-agnostic API built by our research-forward team ensures that our customers can swiftly and securely mitigate fraud and cybersecurity risks in real time with a frictionless, robust solution. Youtube: Reality Defender Wins RSA Most Innovative Startup Why we stand out: Our best-in-class accuracy
is derived from our sole, research-backed mission and use of multiple models per modality
We can
detect AI-generated fraud and disinformation in near- or real time
across all modalities including audio, video, image, and text.
Our platform is
designed for ease of use , featuring a versatile API that integrates seamlessly with any system, an intuitive drag-and-drop web application for quick ad hoc analysis, and platform-agnostic real-time audio detection tailored for call center deployments.
Were
privacy first , ensuring the strongest standards of compliance and keeping customer data away from the training of our detection models.
Role and Responsibilities
Investigate new methods for generative image/video detection
Collaborate with researchers in the team
Perform research of deepfake image/video detection
Write up results of research for internal reports and submission to academic journals/workshops
Independently implement and evaluate ideas on modern deep learning stack - Python, PyTorch, and GPU-enabled cloud compute, like AWS/GCP
About You
PhD student in a relevant technical field
Experience in computer vision
Proficient in Python and in building deep learning models with PyTorch.
Published peer-reviewed research papers in reputable computer vision venues, e.g. CVPR, ICCV, NeurIPS
Team player with a positive attitude and good communication skills.
Excited about our line of work
Reality Defender provides accurate, multi-modal AI-generated media detection solutions to enable enterprises and governments to identify and prevent fraud, disinformation, and harmful deepfakes in real time.
A Y Combinator graduate, Comcast NBCUniversal LIFT Labs alumni, and backed by DCVC , Reality Defender is tdhe first company to pioneer multi-modal and multi-model detection of AI-generated media. Our web app and platform-agnostic API built by our research-forward team ensures that our customers can swiftly and securely mitigate fraud and cybersecurity risks in real time with a frictionless, robust solution. Youtube: Reality Defender Wins RSA Most Innovative Startup Why we stand out: Our best-in-class accuracy
is derived from our sole, research-backed mission and use of multiple models per modality
We can
detect AI-generated fraud and disinformation in near- or real time
across all modalities including audio, video, image, and text.
Our platform is
designed for ease of use , featuring a versatile API that integrates seamlessly with any system, an intuitive drag-and-drop web application for quick ad hoc analysis, and platform-agnostic real-time audio detection tailored for call center deployments.
Were
privacy first , ensuring the strongest standards of compliance and keeping customer data away from the training of our detection models.
Role and Responsibilities
Investigate new methods for generative image/video detection
Collaborate with researchers in the team
Perform research of deepfake image/video detection
Write up results of research for internal reports and submission to academic journals/workshops
Independently implement and evaluate ideas on modern deep learning stack - Python, PyTorch, and GPU-enabled cloud compute, like AWS/GCP
About You
PhD student in a relevant technical field
Experience in computer vision
Proficient in Python and in building deep learning models with PyTorch.
Published peer-reviewed research papers in reputable computer vision venues, e.g. CVPR, ICCV, NeurIPS
Team player with a positive attitude and good communication skills.
Excited about our line of work