Textron announced it will deliver an all-electric version of its M5 Ripsaw Robotic Combat Vehicle for experimentation.
An online app called Amica is now using artificial intelligence to help separating couples make parenting arrangements and divide their assets.
For many people, the coronavirus pandemic has put even the strongest of relationships to the test. A May survey conducted by Relationships Australia found 42% of 739 respondents experienced a negative change in their relationship with their partner under lockdown restrictions.
There has also been a surge in the number of couples seeking separation advice. The Australian government has backed the use of Amica for those in such circumstances. The chatbot uses artificial intelligence (AI) to make suggestions for how splitting couples can divide their money and property based on their circumstances.
You can buy your own robot dog.
Presenting a (comparatively) more affordable robot dog: the $10,000 Unitree A1.
In this talk, professor Bell breaks down the very foundations of AI –viewed as an inescapable and univocal technology- and opens up a space for other truths and possibilities by visiting AI’s alternative stories in the past, present and future. By doing so, she claims, we might make room for a more sustainable, safe and responsible AI, and ultimately a more human-centric one.
Genevieve Bell is a cultural anthropologist and technologist who has spent her career at the intersection between places, people and things. From growing up in indigenous communities in Australia’s outback to Silicon Valley, from Stanford University and Intel Corporation back to Australia’s only national university, she has always questioned what it means to be human in an increasingly digital world. This talk was given at a TEDx event using the TED conference format but independently organized by a local community.
Unmanned combat air vehicles have notched up kills against armored fighting vehicles all over the world. Does it mean the end of the tank?
VR Boots for gaming.
Last year I did a VR experience meant to simulate what it’s like to be at the US-Mexico border wall. The tall, foreboding wall towered above me, and as I turned from side to side there were fields of grass with some wildlife and a deceivingly harmless-looking border patrol station. I wanted to explore more, so I took a few steps toward the wall, hoping to catch a glimpse of the Mexico side through its tall metal slats.
Autonomous tractors for farming.
OSAKA — Kubota has partnered with U.S. chipmaker Nvidia to develop highly sophisticated self-driving farm tractors, the Japanese machinery maker said Tuesday.
The tractors will be equipped with Nvidia graphics processing units and artificial intelligence, coupled with cameras to instantly process collected data.
Continue reading “Kubota taps Nvidia tech for smart-farming autonomous tractors” »
An AI used to write articles was tasked to write an article convincing people that AI was not dangerous to humans. Re-sharing article by Market Watch.
With artificial intelligence (AI) tools and machine learning algorithms now making their way into a wide variety of settings, assessing their security and ensuring that they are protected against cyberattacks is of utmost importance. As most AI algorithms and models are trained on large online datasets and third-party databases, they are vulnerable to a variety of attacks, including neural Trojan attacks.
A neural Trojan attack occurs when an attacker inserts what is known as a hidden Trojan trigger or backdoor inside an AI model during its training. This trigger allows the attacker to hijack the model’s prediction at a later stage, causing it to classify data incorrectly. Detecting these attacks and mitigating their impact can be very challenging, as a targeted model typically performs well and in alignment with a developer’s expectations until the Trojan backdoor is activated.
Researchers at University of California, San Diego have recently created CLEANN, an end-to-end framework designed to protect embedded artificial neural networks from Trojan attacks. This framework, presented in a paper pre-published on arXiv and set to be presented at the 2020 IEEE/ACM International Conference on Computer-Aided Design, was found to perform better than previously developed Trojan shields and detection methods.
