Would be more impressive if it was attached to a humanoid robot body.
A robot can hold a squash, pumpkin or melon in one hand, while it is peeled by the other.
By Alex Wilkins
Would be more impressive if it was attached to a humanoid robot body.
A robot can hold a squash, pumpkin or melon in one hand, while it is peeled by the other.
By Alex Wilkins
Electrically powered artificial muscle fibers (EAMFs) are emerging as a revolutionary power source for advanced robotics and wearable devices. Renowned for their exceptional mechanical properties, integration flexibility, and functional versatility, EAMFs are at the forefront of cutting-edge innovation.
A recent review article on this topic was published online in the National Science Review (“Emerging Innovations in Electrically Powered Artificial Muscle Fibers”).
Schematic of electrically powered artificial muscle fibers categorized from the mechanism, material components, and configurations, as well as their application fields. (Image: Science China Press)
It seems that Silicon Valley giants, AAA game developers, and other companies desperately clinging to the AI trend and trying to integrate the technology into any product they own will soon have to rethink their marketing strategies, as a new study conducted by researchers from Washington State University indicates that using terms like “AI” or “artificial intelligence” in product descriptions can negatively impact sales.
To explore the impact of including “AI” in goods and service descriptions on consumers’ purchase intentions, the team conducted six experiments and surveyed over a thousand people, discovering that the use of these terms decreases purchase intention and lowers emotional trust, leading to what any company fears the most – diminishing sales numbers.
Furthermore, the researchers found that putting artificial intelligence in the spotlight can be even more detrimental when it comes to high-risk products – those consumers typically think twice about buying, such as expensive gadgets and medical services – compared to low-risk items, primarily because of the greater likelihood of incurring monetary losses or facing health risks.
In Light: Science & Applications journal UCLA researchers introduce an innovative design for diffractive deep neural networks (D2NNs). This new architecture, termed Pyramid-D2NN (P-D2NN), achieves unidirectional image magnification and demagnification, significantly reducing the number of diffractive features required.
Everyone thinks they know but no one can agree. And that’s a problem.
Focus on good things: creative activities:
Neura’s 4NE-1 is a humanoid robot capable of carrying out multiple daily and industrial chores, according to the company.