Many economists say the problem reflects a jobs mismatch that could defy government solutions for years.
The Microsoft founder has called time on Amazon’s business as we know it—saying A.I. will make the e-commerce giant obsolete.
Billionaire philanthropist Gates added the developer destined to win the artificial intelligence race will be the one which manages to create a personal agent that can perform certain tasks to save users time.
“Whoever wins the personal agent, that’s the big thing, because you will never go to a search site again, you will never go to a productivity site, you’ll never go to Amazon again,” he explained.
Pichai thinks A.I. is “too important not to regulate well,” while Altman suggested a body like the IAEA is needed to coordinate regulatory efforts.
The Meta chief has drawn up plans for Instagram to introduce a Twitter competitor that would allow users to share text, per reports last week. Zuckerberg is reportedly already going out of his way to get high-profile influencers onboard.
This is not the first time Zuckerberg has taken a leaf out of his rivals’ books. In the span of almost two decades, he has been able to create – and keep intact – his $630 billion social-media empire by copying ideas from plucky upstarts building competing social networks.
Musk’s new Twitter CEO Linda Yaccarino seems ready for the challenge from Zuckerberg, but if she and Musk are really serious about turning Twitter into a money-making machine, they may need to do some brazen copycatting of their own.
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After more than a decade of work by researchers in France and Switzerland, a paralysed man has regained the ability to walk naturally using only his thoughts.
Whether sitting or hanging, the surface of a protein-containing droplet changes as the water escapes, an effect researchers link to the pull of gravity.
A curved “laser wakefield accelerator” could boost the acceleration potential of a multistage version of this device.
Laser wakefield accelerators (LWFAs) use laser-generated plasmas to accelerate electrons to high energies. The devices are significantly smaller than radio-frequency-based particle accelerators—centimeters versus hundreds of meters—making them less expensive, more efficient alternatives. But researchers still need to demonstrate that LWFAs can achieve particle energies that match those of their conventional counterparts. Now Xinzhe Zhu from Shanghai Jiao Tong University and colleagues have brought that goal a step closer, demonstrating a method for linking multiple LWFAs in a way that would boost their acceleration potential [1].
In an LWFA, charged particles reach relativistic speeds by surfing a wave of plasma created by a powerful laser. The particle energy achievable with a single LWFA is limited to a few GeV for two reasons: the particle bunch and the plasma wave quickly fall out of sync, and the laser energy dissipates with distance. Routing particles through multiple connected LWFAs would overcome these problems. But current techniques for combining LWFAs require refocusing the beam at each connection, lowering the efficiency of the process.
A quantum repeater based on trapped ions allows the transmission of entangled, telecom-wavelength photons over 50 km.
Communication networks have transformed our society over the past half century, and we can scarcely imagine our daily lives without them. Recent advances in the emergent field of quantum technologies have exhilarated scientists about the possibility of linking quantum devices in networks. Long-distance quantum communication portends functionality that is beyond the reach of classical networks [1]. To make full use of entanglement and other quantum effects, quantum networks exchange signals at the level of single photons. As a result, attenuation in fiber is the dominant source of error in these systems. Photon loss, however, can be remedied using a set of intermediate network nodes, called quantum repeaters, which create a direct entangled connection between distant network nodes [2].
A study of drops falling on a thin liquid film finds that splash behavior depends on film thickness—a result that could impact our understanding of stalagmite formation.
The recent advent of generative models, computational tools that can generate new texts or images based on the data they are trained on, opened interesting new possibilities for the creative industries. For example, they allow artists and digital content creators to easily produce realistic media content that integrates elements of different images or videos.
Inspired by these recent advances, researchers at Stanford University, UC Berkeley and Adobe Research have developed a new model that can realistically insert specific humans into different scenes, for instance showing them as they exercise in the gym, watch a sunset on the beach, and so on.
Their proposed architecture, which is based on a class of generative models known as diffusion models, was introduced in a paper pre-published on the arXiv server and set to be presented at the Conference on Computer Vision and Pattern Recognition (CVPR) 2023 in Vancouver this June.
