By
Debra KaufmanJanuary 13, 2021
During a CES 2021 panel moderated by The Female Quotient chief executive Shelley Zalis, AI industry executives probed issues related to gender and racial bias in artificial intelligence. Google head of product inclusion Annie Jean-Baptiste, SureStart founder and chief executive Dr. Taniya Mishra and ResMed senior director of health economics and outcomes research Kimberly Sterling described the parameters of such bias. At Google, Jean-Baptiste noted that, “the most important thing we need to remember is that inclusion inputs lead to inclusion outputs.” Continue reading CES: Panel Examines Issues of Gender and Racial Bias in AI
By
Debra KaufmanAugust 21, 2020
On August 1, security research firm Comparitech, led by Bob Diachenko, discovered a massive data leak of nearly 235 million Instagram, TikTok and YouTube user profiles. The leak was due to an unsecured database, which is quickly becoming a widespread cause of similar breaches. An audit of the dark web found about 15 billion stolen logins from 100,000 such unsecured database breaches. The data leak discovered by Diachenko and his team was spread across several datasets, including two of 100 million each of Instagram users. Continue reading Unsecured Databases Leak 235 Million Social Media Profiles
By
Debra KaufmanJune 29, 2018
Google researchers have created a machine learning system that adds color to black & white videos, and can also choose which specific objects, people and pets receive the color treatment. The technology is based on what’s called a convolutional neural network, which is architecturally suited for object tracking and video stabilization. Meanwhile, Nvidia has debuted an algorithm that slows down video, without the jitters, after it’s been captured, by using a neural network to create “in between” frames required for smooth motion. Continue reading Google, Nvidia Train Neural Networks to Post-Process Video
By
Debra KaufmanApril 26, 2018
Nvidia debuted a deep learning method that can edit or reconstruct an image that is missing pixels or has holes via a process called “image inpainting.” The model can handle holes of “any shape, size, location or distance from image borders,” and could be integrated in photo editing software to remove undesirable imagery and replace it with a realistic digital image – instantly and with great accuracy. Previous AI-based approaches focused on rectangular regions in the image’s center and required post processing. Continue reading Nvidia’s New AI Method Can Reconstruct an Image in Seconds