Lifeboat Foundation

Imagine returning home from your evening walk or gym to the aroma of freshly cooked kadhai paneer or chicken curry, which instantly reminds you of home. Now, what if you were to know that it was no human that lovingly prepared this piping hot and delicious meal, but rather, a machine?

From booking cabs to ordering food right at your doorstep, technology makes human lives easy. So it’s about time it saves humans from having to cook after a long tiring day at work, or at times when you’re just not in the mood to enter the kitchen.

The NOSH device, developed by the Euphotic Labs, was conceived by Yatin Varachhia, co-founder of the Bengaluru-based startup. The 34-year-old says the inspiration to build a device stemmed from his struggle of having good food.

It took Nicolas Neubert seven hours to make it his living room.

It sounds far-fetched, but researchers are trying to recreate subjective experience in AIs, even if disagreement over what consciousness is will make it difficult to test.

By Thomas Lewton

An important, but lesser known, neurotransmitter is at the heart of our constant negative thinking.

Aging process slows when older mice share circulatory system of young; the longer the animals shared circulatory systems, the more durable the benefits.

Beware of CherryBlos: the new Android malware that’s out to steal your cryptocurrency!

A legitimate Windows search feature is being exploited by unknown malicious actors to download arbitrary payloads from remote servers and compromise targeted systems with remote access trojans such as AsyncRAT and Remcos RAT.

The novel attack technique, per Trellix, takes advantage of the “search-ms:” URI protocol handler, which offers the ability for applications and HTML links to launch custom local searches on a device, and the “search:” application protocol, a mechanism for calling the desktop search application on Windows.

“Attackers are directing users to websites that exploit the ‘search-ms’ functionality using JavaScript hosted on the page,” security researchers Mathanraj Thangaraju and Sijo Jacob said in a Thursday write-up. “This technique has even been extended to HTML attachments, expanding the attack surface.”

Not surprisingly, the Intelligence Community (IC), Department of Defense (DoD), and first responders at the Department of Homeland Security (DHS) and other agencies are also interested in wearable electronics. With its Smart Electrically Powered and Networked Textile Systems (SMART ePANTS) program, the Intelligence Advanced Research Projects Activity (IARPA) is delivering the largest single investment ever made¹ to make Advanced Smart Textiles² (AST) a reality.

According to SMART ePANTS Program Manager, Dr. Dawson Cagle, developing clothing with sensor systems that can record audio, video, and geolocation data would significantly improve the capabilities of IC, DoD, DHS staff, and others working in dangerous or high-stress environments, such as crime scenes and arms control inspections. Dr. Cagle also asserted that ASTs could collect information one doesn’t notice, which would increase job effectiveness.

Researchers from the Tokyo University of Science recently published a study in the journal Artificial Life and Robotics where they explored how machine learning can help detect deception.

Machine learning is a subset of artificial intelligence (AI) that involves the use of algorithms and statistical models to enable computers to learn and improve from experience without being explicitly programmed. In other words, it is a method of teaching computers to perform specific tasks by learning from data, patterns, and examples, rather than relying on pre-defined rules.

Detecting deception can be important in various situations, like questioning crime victims or suspects and interviewing patients with mental health issues. Sometimes, human interviewers might struggle to ask the right questions or spot deception accurately.