Commercial customers will have to get their wallets ready to keep receiving security updates for Windows 10.
Assisted by quantum physics and machine learning, researchers have developed a transparent window coating that lets in visible light but blocks heat-producing UV and infrared. The coating not only reduces room temperature but also the energy consumption related to cooling, regardless of where the sun is in the sky.
Windows are great. They provide views of the park you live across from or the bird-filled tree outside your office. But, windows can also be not-so-great. Letting in light (and the view) is one thing, but with light comes heat, especially in the hotter months.
On hot days, up to 87% of heat gain in our homes is through windows. UV radiation from sunlight passes easily through glass, heating up the room and increasing the likelihood that you need to turn on the air-con or else forgo any light (and, again, that view) by closing the curtains or lowering the blinds. However, researchers at the University of Notre Dame have developed a window coating that blocks heat-producing UV and infrared light while allowing visible light in, reducing both room temperature and cooling energy consumption.
GPT-4 is already better at changing people’s minds than the average human is, according to new research. The gap widens the more it knows about us – and once it can see us in real time, AI seems likely to become an unprecedented persuasion machine.
We don’t tend to like thinking of ourselves as being particularly easy to manipulate, but history would appear to show that there are few things more powerful than the ability to sway people to align with your view of things. As Yuval Noah Harari points out in Sapiens, his potted history of humankind, “shared fictions” like money, religion, nation states, laws and social norms form the fundamental backbones of human society. The ability to assemble around ideas and co-operate in groups much bigger than our local tribes is one of our most potent advantages over the animal kingdom.
But ideas are mushy. We aren’t born with them, they get into our heads from somewhere, and they can often be changed. Those that can change people’s minds at scale can achieve incredible things, or even reshape our societies – for better and for much worse.
Some amount of chatbot hallucination is inevitable. But there are ways to minimize it.
The SpaceX Falcon 9 launch of 21 Starlink satellites from Vandenberg Space Force Base climbs into the atmosphere over Southern California at dusk, April 6, 2024.
Remarkable advance in protein engineering wherein Huddy et al.
A study describes an approach using designed building blocks that are far more regular in geometry than natural proteins to construct modular multicomponent protein assemblies.
Engineering the tunability of protein assembly in response to pH changes within a narrow range is challenging. Here the authors report the de novo computational design of pH-responsive protein filaments that exhibit rapid, precise, tunable and reversible assembly and disassembly triggered by small pH changes.
Using observations made with the Gran Telescopio Canarias (GTC) a study led from the Instituto de Astrofísica de Canarias (IAC) and the Universidad Complutense de Madrid (UCM) has confirmed that the asteroid 2023 FW14, discovered last year, is accompanying the red planet in its journey round the sun, ahead of Mars and in the same orbit.
With this new member, the group of Trojans that accompany Mars has increased in number to 17. But it shows differences in its orbit and chemical composition which may indicate that it is a captured asteroid, of a primitive type. The results are published in Astronomy & Astrophysics.
A team from the Instituto de Astrofísica de Canarias (IAC) and the Universidad Complutense de Madrid (UCM) has observed and described for the first time the object 2023 FW14, a Trojan asteroid that shares its orbit with Mars. After Jupiter, the red planet has the largest number of known Trojans, totaling 17 with this new identification.
In our current age of artificial intelligence, computers can generate their own “art” by way of diffusion models, iteratively adding structure to a noisy initial state until a clear image or video emerges.
Diffusion models have suddenly grabbed a seat at everyone’s table: Enter a few words and experience instantaneous, dopamine-spiking dreamscapes at the intersection of reality and fantasy. Behind the scenes, it involves a complex, time-intensive process requiring numerous iterations for the algorithm to perfect the image.
MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) researchers have introduced a new framework that simplifies the multi-step process of traditional diffusion models into a single step, addressing previous limitations. This is done through a type of teacher-student model: teaching a new computer model to mimic the behavior of more complicated, original models that generate images.
On Friday 5 April, at 6.25 p.m., the LHC Engineer-in-Charge at the CERN Control Centre (CCC) announced that stable beams were back in the Large Hadron Collider, marking the official start of the 2024 physics data-taking season. The third year of LHC Run 3 promises six months of 13.6 TeV proton collisions at an even higher luminosity than before, meaning more collisions for the experiments to take data from. This will be followed by a period of lead ion collisions in October.
Before the LHC could restart, each accelerator in the CERN complex had to be prepared for another year of physics data taking. Beginning with Linac4, which welcomed its first beam two months ago, each accelerator has gone through a phase of beam commissioning in which it is gradually set up and optimised to be able to control all aspects of the beam, from its energy and intensity to its size and stability. During this phase researchers also test the accelerator’s performance and address any issues before it is used for physics. Following Linac4, which contains the source of protons for the beam, each accelerator was commissioned in turn: the Proton Synchrotron Booster, the Proton Synchrotron, the Super Proton Synchrotron, and finally the LHC from 8 March until 5 April. The whole complex is now ready for data taking.
Back to the CCC. While stable beams are the goal, the CCC engineers must first take several steps to achieve them. First, they must inject the beams into the LHC from the previous accelerators in the chain. Then begins the ramp-up process, which involves increasing the beam energy up to the nominal energy of 6.8 TeV. The next step – shown as “flat top” on LHC Page 1 – is where the energy in the beams is consistent, but they’re not quite ready yet. In order to achieve stable beams, the circulating beams must then be “squeezed” and adjusted using the LHC magnets. This involves making the beams narrower and more centred on their paths, and therefore more likely to produce a high number of collisions in the detectors. Only after the squeezing and adjustment has been completed can stable beams be declared and the experiments around the LHC begin their data taking.