Telehealth Sites Put Addiction Patient Data at Risk
New research found pervasive use of tracking tech on substance-abuse-focused health care websites, potentially endangering users in a post-Roe world.
The Stereotype of the Woke Teen Is ‘Tárring’ Art
An archetype culled from the depths of social media seems to be short-circuiting screenwriters’ creativity.
‘Pentiment’ May Be 2022’s Best Game You’ve Never Heard Of
A crash course in 16th-century German history? Sold!
20 Best Viral TikTok Gifts We Found, and Love (2022)
We tried out the gadgets that kept showing up in our feeds. Here are the ones that deserve the hype—and would make awesome presents.
Skin-like electronics could monitor your health continuously
New wearable electronics paired with artificial intelligence could transform screening for health problems.
A low-cost robot ready for any obstacle
Researchers have designed a robotic system that enables a low-cost and relatively small legged robot to climb and descend stairs nearly its height; traverse rocky, slippery, uneven, steep and varied terrain; walk across gaps; scale rocks and curbs; and even operate in the dark.
A low-cost robot ready for any obstacle
This little robot can go almost anywhere.
Smart home hubs leave users vulnerable to hackers
Machine learning programs mean even encrypted information can give cybercriminals insight into your daily habits.
Research ushers in a ‘new frontier’ in tackling global poverty
With electricity comes prosperity, right? The answer might seem obvious—that electricity is key to economic growth and other societal benefits like better health. But in the world’s most impoverished regions, where resources to improve livelihoods are scarce, it’s not clear how much better off people are when they have access to electrical power.
Elastic Weight Consolidation Improves the Robustness of Self-Supervised Learning Methods under Transfer
This paper was accepted at the workshop “Self-Supervised Learning – Theory and Practice” at NeurIPS 2022. Self-supervised representation learning (SSL) methods provide an effective label-free initial condition for fine-tuning downstream tasks. However, in numerous realistic scenarios, the downstream task might be biased with respect to the target label distribution. This in turn moves the learned …