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Scientific ingenuity means cameras keep on getting smaller and smaller, and the latest to appear is not only incredibly tiny – the same size as a grain of salt – it’s also able to produce images of much better quality than a lot of other ultra-compact cameras.

Using a technology known as a metasurface, which is covered with 1.6 million cylindrical posts, the camera is able to capture full-color photos that are as good as images snapped by conventional lenses some half a million times bigger than this particular camera.

And the super-small contraption has the potential to be helpful in a whole range of scenarios, from helping miniature soft robots explore the world, to giving experts a better idea of what’s going on deep inside the human body.

Prof Stuart Russell, founder of the Center for Human-Compatible Artificial Intelligence, at the University of California, Berkeley, is giving this year’s Reith Lectures.

He said: Because I think it’s really important and really urgent.

And the reason it’s urgent is because the weapons that we have been talking about for the last six years or seven years are now starting to be manufactured and sold.

So in 2017, for example, we produced a movie called Slaughterbots about a small quadcopter about 3in [8cm] in diameter that carries an explosive charge and can kill people by getting close enough to them to blow up.

We showed this first at diplomatic meetings in Geneva and I remember the Russian ambassador basically sneering and sniffing and saying: “Well, you know, this is just science fiction, we don’t have to worry about these things for 25 or 30 years.”

I explained what my robotics colleagues had said, which is that no, they could put a weapon like this together in a few months with a few graduate students.

And in the following month, so three weeks later, the Turkish manufacturer STM [Savunma Teknolojileri Mühendislik ve Ticaret AŞ] actually announced the Kargu drone, which is basically a slightly larger version of the Slaughterbot.

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Artificial Intelligence is changing our lives. We can see the evolution of AI almost in every industry like finance, healthcare, education, transportation, and more. The best examples of Artificial Intelligence are Self-Driven Cars, Google Assistant/Siri/Alexa, Product Recommendations, Chatbots, Facebook Image Recognition, GPS, Pandora, BLUE RIVER, and Plantix.

Company received over 20,000 applications, and our client has decided to suspend the request collection. It will take up to 12 month to make the decision. Details: https://promo-bot.ai/media/humanoid_project/ Last week the manufacturer company of Promobot robots was seeking a face for a humanoid robot-assistant which will work in hotels, shopping malls and other crowded places. The company was ready to pay out to somebody willing to transfer the rights to use one’s face forever.

As of Monday, it appears that Promobot has stopped accepting applications for the opportunity. Additionally, further details regarding the project seem to have been removed from their site.

“The Promobot company wants to say thanks to everyone who responded to participation in the project. Today we have received over 20,000 applications and our client has decided to suspend the request collection… Those who didn’t have time to submit an application, please no worries, we are having more projects upcoming. Subscribe to our Instagram and stay tuned.” explained an update on the Promobot website.

On Friday, Alibaba Cloud announced in a social media post that its DAMO Academy has successfully developed a 3D stacked In-Memory Computing (IMC) chip.

Alibaba Cloud claims this is a breakthrough that can help overcome the von Neumann bottleneck, a limitation on throughput caused by the standard personal computer architecture. It meets the needs of artificial intelligence (AI) and other scenarios for high bandwidth, high capacity memory and extreme computing power. In the specific AI scenario tested by Alibaba, the performance of the chip is improved by more than 10 times.

With the outbreak of AI applications, the shortcomings of the existing computer system architecture are gradually revealed. The main problems are that, on the one hand, processing data brings huge energy consumption. Under the traditional architecture, the power consumption required for data transmission from memory unit to computing unit is about 200 times of that of computing itself, so the real energy consumption and time used for computing are very low.