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Advances in electrochromic coatings may bring us closer to environmentally friendly ways to keep inside spaces cool. Like eyeglasses that darken to provide sun protection, the optical properties of these transparent films can be tuned with electricity to block out solar heat and light. Now, researchers report demonstrating a new electrochromic film design based on metal-organic frameworks (MOFs) that quickly and reliably switch from transparent to glare-diminishing green to thermal-insulating red.

Researchers have demonstrated the ability to engineer materials that are both stiff and capable of insulating against heat. This combination of properties is extremely unusual and holds promise for a range of applications, such as the development of new thermal insulation coatings for electronic devices.

A new study may help redefine how scientists map the surface of the Moon, making the process more streamlined and precise than ever before.

A new study may help redefine how scientists map the surface of the Moon, making the process more streamlined and precise than ever before.

As a newly developed perovskite with a large amount of intrinsic oxygen vacancies, BaSc0.8W0.2O2.8 achieves high proton conduction at low and intermediate temperatures, report scientists. By the donor doping of large W6+, this material can take up more water to increase its proton concentration, as well as reduce the proton trapping through electrostatic repulsion between the dopant and proton. These findings could pave the way to the rational design of novel perovskites for protonic ceramic fuel cells (PCFCs) and electrolysis cells (PCECs).

Scientists have discovered that mycelium composites, biobased materials made from fungi and agricultural residues, can have a greater environmental impact than conventional fossil-fuel-based materials due to the high amount of electricity involved in their production.

Researchers have managed to generate propagating spin waves at the nanoscale and discovered a novel pathway to modulate and amplify them. Their discovery could pave the way for the development of dissipation free quantum information technologies. As the spin waves do not involve electric currents these chips will be free from associated losses of energy. The rapidly growing popularity of artificial intelligence comes with an increasing desire for fast and energy efficient computing devices and calls for novel ways to store and process information. The electric currents in conventional devices suffer from losses of energy and subsequent heating of the environment.

Researchers have shown that members of the public have little trouble in learning very quickly how to use a third thumb -- a controllable, prosthetic extra thumb -- to pick up and manipulate objects. The team tested the robotic device on a diverse range of participants, which they say is essential for ensuring new technologies are inclusive and can work for everyone.

Researchers have shown that members of the public have little trouble in learning very quickly how to use a third thumb -- a controllable, prosthetic extra thumb -- to pick up and manipulate objects. The team tested the robotic device on a diverse range of participants, which they say is essential for ensuring new technologies are inclusive and can work for everyone.

Calculating probabilities can be complicated, as this classic "what's behind the doors" problem shows, says Peter Rowlett

Scrap screens for a while and enjoy the real feel of Aqua, a board game where colourful tiles grow into ecosystems. It's mostly relaxing – apart from the fiendish scoring system, says Jacob Aron

The books, TV, games and more that New Scientist staff have enjoyed this week

When I heard Stephen Hawking extoll the mysteries of black holes, I knew theoretical physics was what I wanted to do. There is still so much to learn about these strange regions, says Chanda Prescod-Weinstein

Feedback wonders if previous research into 'courtship behaviours of ostriches' in the UK will be taken into account by the owner of a new ostrich farm in New Hampshire

Ponds have long been neglected by science, but we can't overlook these diverse and important nature hotspots any more, say Jeremy Biggs and Penny Williams

To understand the power – and limitations – of artificial intelligence, we need information, not hype. Alex Wilkins explores what four new books, from Ray Kurzweil, Nick Bostrom, Neil Lawrence and Shannon Vallor, offer

The El Niño climate pattern has contributed to a year of record-breaking temperatures. We must bend the curve of carbon emissions before the next one arrives

Cow udders have lots of bird-like flu virus receptors but no human-like ones, a study has found, meaning there’s no reason for the virus to evolve to become better at infecting people

Consumer-grade AI is finding its way into people’s daily lives with its ability to generate text and images and automate tasks. But astronomers need much more powerful, specialized AI. The vast amounts of observational data generated by modern telescopes and observatories defies astronomers’ efforts to extract all of its meaning.

A team of scientists is developing a new AI for astronomical data called AstroPT. They’ve presented it in a new paper titled “AstroPT: Scaling Large Observation Models for Astronomy.” The paper is available at arxiv.org, and the lead author is Michael J. Smith, a data scientist and astronomer from Aspia Space.

Astronomers are facing a growing deluge of data, which will expand enormously when the Vera Rubin Observatory (VRO) comes online in 2025. The VRO has the world’s largest camera, and each of its images could fill 1500 large-screen TVs. During its ten-year mission, the VRO will generate about 0.5 exabytes of data, which is about 50,000 times more data than is contained in the USA’s Library of Congress.

The VRO’s need for multiple sites to handle all of its data is a testament to the enormous volume of data it will generate. Without effective AI, that data will be stuck in a bottleneck. Image Credit: NOIRLab.

Other telescopes with enormous mirrors are also approaching first light. The Giant Magellan Telescope, the Thirty Meter Telescope, and the European Extremely Large Telescope combined will generate an overwhelming amount of data.

Having data that can’t be processed is the same as not having the data at all. It’s basically inert and has no meaning until it’s processed somehow. “When you have too much data, and you don’t have the technology to process it, it’s like having no data,” said Cecilia Garraffo, a computational astrophysicist at the Harvard-Smithsonian Center for Astrophysics.

This is where AstroPT comes in.

AstroPT stands for Astro Pretrained Transformer, where a transformer is a particular type of AI. Transformers can change or transform an input sequence into an output sequence. AI needs to be trained, and AstroPT has been trained on 8.6 million 512 x 512-pixel images from the DESI Legacy Survey Data Release 8. DESI is the Dark Energy Spectroscopic Instrument. DESI studies the effect of Dark Energy by capturing the optical spectra from tens of millions of galaxies and quasars.

AstroPT and similar AI deal with ‘tokens.’ Tokens are visual elements in a larger image that contain meaning. By breaking images down into tokens, an AI can understand the larger meaning of an image. AstroPT can transform individual tokens into coherent output.

AstroPT has been trained on visual tokens. The idea is to teach the AI to predict the next token. The more thoroughly it’s been trained to do that, the better it will perform.

“We demonstrated that simple generative autoregressive models can learn scientifically useful information when pre-trained on the surrogate task of predicting the next 16 × 16 pixel patch in a sequence of galaxy image patches,” the authors write. In this scheme, each image patch is a token.

This image illustrates how the authors trained AstroPT to predict the next token in a ‘spiralised’ sequence of galaxy image patches. It shows the token feed order. “As the galaxies are in the centre of each postage stamp, this set up allows us to seamlessly pretrain and run inference on differently sized galaxy postage stamps,” the authors explain. Image Credit: Smith et al. 2024.

One of the obstacles to training AI like AstroPT concerns what AI scientists call the ‘token crisis.’ To be effective, AI needs to be trained on a large number of quality tokens. In a 2023 paper, a separate team of researchers explained that a lack of tokens can limit the effectiveness of some AI, such as LLMs or Large Language Models. “State-of-the-art LLMs require vast amounts of internet-scale text data for pre-training,” the wrote. “Unfortunately, … the growth rate of high-quality text data on the internet is much
slower than the growth rate of data required by LLMs.”

AstroPT faces the same problem: a dearth of quality tokens to train on. Like other AI, it uses LOMs or Large Observation Models. The team says their results so far suggest that AstroPT can solve the token crisis by using data from observations. “This is a promising result that suggests that data taken from the observational sciences would complement data from other domains when used to pre-train a single multimodal LOM, and so points towards the use of observational data as one solution to the ‘token crisis’.”

AI developers are eager to find solutions to the token crisis and other AI challenges.

Without better AI, a data processing bottleneck will prevent astronomers and astrophysicists from making discoveries from the vast quantities of data that will soon arrive. Can AstroPT help?

The authors are hoping that it can, but it needs much more development. They say they’re open to collaborating with others to strengthen AstroPT. To aid that, they followed “current leading community models” as closely as possible. They call it an “open to all project.”

“We took these decisions in the belief that collaborative community development paves the fastest route towards realising an open source web-scale large observation model,” they write.

“We warmly invite potential collaborators to join us,” they conclude.

It’ll be interesting to see how AI developers will keep up with the vast amount of astronomical data coming our way.

The post Astronomy Generates Mountains of Data. That’s Perfect for AI appeared first on Universe Today.

People who have had a recent vaccine against tetanus appear to be less likely to develop Parkinson’s disease, suggesting that the bacterial infection is involved in the condition