Researchers developed an easy-to-use tool that enables an AI practitioner to find data that suits the purpose of their model, which could improve accuracy and reduce bias.
AI agents could soon become indistinguishable from humans online. Could “personhood credentials” protect people against digital imposters?
Researchers have developed a security solution for power-hungry AI models that offers protection against two common attacks.
Doctoral student and recent MAD Design Fellow Jonathan Zong SM ’20 discusses a proposed framework to map how individuals can say “no” to technology misuses.
The ambient light sensors responsible for smart devices’ brightness adjustments can capture images of touch interactions like swiping and tapping for hackers.
Speranza system brings hope to users that the package they download is functional software, not malware.
With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.
The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.
Researchers use synthetic data to improve a model’s ability to grasp conceptual information, which could enhance automatic captioning and question-answering systems.
Researchers create a privacy technique that protects sensitive data while maintaining a machine-learning model’s performance.
The system analyzes the likelihood that an attacker could thwart a certain security scheme to steal secret information.
Cloud security and video forensics software have been transitioned to end users.
New research enables users to search for information without revealing their queries, based on a method that is 30 times faster than comparable prior techniques.
Models trained on synthetic data can be more accurate than other models in some cases, which could eliminate some privacy, copyright, and ethical concerns from using real data.
A new technique enables AI models to continually learn from new data on intelligent edge devices like smartphones and sensors, reducing energy costs and privacy risks.