Multiple Australian projects are on the cutting edge of neurotech breakthroughs and man-machine interfaces – raising questions of security and privacy for human minds.
On Saturday, Chinese scholars unveiled a preliminary proposal draft in Beijing that could potentially shape the nation’s forthcoming artificial intelligence (AI) law.
The proposal draft pays attention to the development issues of industrial practice in the three areas of data, computing power and algorithms, Zhao Jingwu, an associate professor from BeiHang University Law School, told the Global Times.
Zhao said that the proposal also introduces the AI insurance system that encourages the intervention of the insurance market through policy incentives, exploring insurance products suitable for the AI industry. In addition, it proposes the enhancement of citizens’ digital literacy, aiming to prevent and control the security risks of the technology from the user end.
Long-wavelength infrared (LWIR) imaging holds critical significance across many applications, from consumer electronics to defense and national security. It finds applications in night vision, remote sensing, and long-range imaging. However, the conventional refractive lenses employed in these imaging systems are bulky and heavy, which is undesirable for almost all applications. Compounding this issue is the fact that many LWIR refractive lenses are crafted from expensive and limited-supply materials, such as germanium.
The Los Angeles Police Department is warning residents that burglars are using WiFi jammers to easily disarm “connected” surveillance cameras and alarms that are available for cheap on marketplaces like Amazon.
As LA-based news station KTLA5 reports, tech-savvy burglars have been using WiFi jammers, which are small devices that can confuse and overload wireless devices with traffic, to enter homes without setting off alarms — a worrying demonstration of just how easily affordable home security devices from the likes of Ring and Eufy can be disarmed.
As Tom’s Hardware reported last month, instances of WiFi jammers being used by criminals go back several years. Jammers are not only easily available to purchase online, they’re also pretty cheap and can go for as little as $40.
How will that situation change development teams? A common ratio of developers to testers is three to one. At a big bank with 40,000 software engineers, 10,000 might do security, reliability, and quality control. But the AI effect is like squeezing a balloon so it expands on the other side. The coding productivity jump is offset by a dramatic increase in cycles spent on testing.
How Development Teams Can Get Ahead
For software teams, the pressure is on to adapt. Companies that want to stay ahead of the game should first get a handle on a long-time adversary: toil.
Quantum computers, which can solve several complex problems exponentially faster than classical computers, are expected to improve artificial intelligence (AI) applications deployed in devices like autonomous vehicles; however, just like their predecessors, quantum computers are vulnerable to adversarial attacks.
A team of University of Texas at Dallas researchers and an industry collaborator have developed an approach to give quantum computers an extra layer of protection against such attacks. Their solution, Quantum Noise Injection for Adversarial Defense (QNAD), counteracts the impact of attacks designed to disrupt inference—AI’s ability to make decisions or solve tasks.
The team will present research that demonstrates the method at the IEEE International Symposium on Hardware Oriented Security and Trust held May 6–9 in Washington, D.C.
A global race to build powerful computer chips that are essential for the next generation of artificial intelligence (AI) tools could have a major impact on global politics and security.
The US is currently leading the race in the design of these chips, also known as semiconductors. But most of the manufacturing is carried out in Taiwan. The debate has been fueled by the call by Sam Altman, CEO of ChatGPT’s developer OpenAI, for a US$5 trillion to US$7 trillion (£3.9 trillion to £5.5 trillion) global investment to produce more powerful chips for the next generation of AI platforms.
The amount of money Altman called for is more than the chip industry has spent in total since it began. Whatever the facts about those numbers, overall projections for the AI market are mind blowing. The data analytics company GlobalData forecasts that the market will be worth US$909 billion by 2030.
MIT engineers developed a tag that can reveal with near-perfect accuracy whether an item is real or fake. The key is in the glue on the back of the tag.
A few years ago, MIT researchers invented a cryptographic ID tag that is several times smaller and significantly cheaper than the traditional radio frequency tags (RFIDs) that are often affixed to products to verify their authenticity.
This tiny tag, which offers improved security over RFIDs, utilizes terahertz waves, which are smaller and have much higher frequencies than radio waves. But this terahertz tag shared a major security vulnerability with traditional RFIDs: A counterfeiter could peel the tag off a genuine item and reattach it to a fake, and the authentication system would be none the wiser.
A security researcher has discovered an unsecured database on the internet containing millions of two-factor authentication security codes. Here’s what you need to know.
The Rebellionaire Road Rally has made its way down to Austin, TX. This time we’re joined by Farzad (@farzyness) to test out Tesla FSD v12 on the streets of the greater Austin area. This is part 2 of the journey with Farzad joining in the car adding helpful commentary.
#Tesla #rebellionaire.
