Sierra Space’s oxygen tech boosts lunar sustainability, aiding NASA’s Artemis goal for a permanent moon base and future Mars missions.
Large language models (LLMs) such as ChatGPT and Google Gemini excel at being trained on large data-sets to generate informative responses to prompts. Yi Cao, an assistant professor of accounting at the Donald G. Costello College of Business at George Mason University, and Long Chen, associate professor and area chair of accounting at Costello, are actively exploring how individual investors can use LLMs to glean market insights from the dizzying array of available data about companies.
Their new working paper, appearing in SSRN Electronic Journal and co-authored with Jennifer Wu Tucker of the University of Florida and Chi Wan of University of Massachusetts Boston, examines AI’s ability to identify “peer firms,” or product market competitors in an industry.
Cao explains the significance of selecting peers by relating this process to the real-estate market. “The capital market is similar to the real-estate market in that a firm’s value is partially determined by the value of its peers. In the real-estate market, we price a home based on the value of comparable properties in the neighborhood, or the so-called ‘comps.’ In our paper, we aim to leverage the power of LLMs to identify comps for evaluating firm value.”
As the global energy crisis intensifies and climate change accelerates, finding sustainable solutions for energy management is increasingly urgent. One promising approach is passive radiative cooling, a technology that allows objects to cool by emitting heat directly into space, requiring no additional energy.
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Mousavi, S., Seyedmirzaei, H., Shahrokhi Nejad, S. et al. Sci Rep 14, 21,936 (2024). https://doi.org/10.1038/s41598-024-73277-z.
Neurotech company Synchron has been making massive strides over the past couple of years. It’s just announced that a trial participant has used its brain-computer interface (BCI) to turn on the lights in his home, see who is at the door, and choose what to watch on the TV – hands-free and without even a voice command.
That’s thanks to Synchron’s interface translating his thoughts into commands relayed to Amazon’s Alexa service. The virtual assistant is set up on his tablet and connected to his smart home devices. The trial participant, who is living with amyotrophic lateral sclerosis (ALS) and can’t use his hands, can simply think about navigating through options displayed on the tablet to engage them.
Continue reading “Surgery-free Neuralink rival enables thought-controlled smart home” »
Lunar igneous activities including intrusive and extrusive magmatism, and their products contain significant information about the lunar interior and its thermal state. Their distribution is asymmetrical on the nearside and farside, reflecting the global lunar dichotomy. In addition to previously returned lunar samples all from nearside (Apollo, Luna, and Chang’e-5), samples from the South Pole-Aitken (SPA) basin on the farside have long been thought to hold the key to rebalancing the asymmetrical understandings of the Moon and disclosing the lunar dichotomy conundrum.
Earlier this year, the Chang’e-6 mission of the Chinese Lunar Exploration Program, successfully launched on May 3, landed on the lunar surface on June 2, and returned to the Earth on June 25 carrying a total of 1935.3g of lunar soils. It is the world’s first lunar farside sample-return mission, which landed in the south of the Apollo basin within the SPA basin on the farside. These precious samples would open a window to solve the long-standing question of lunar dichotomy, even reshape human’s knowledge of our closest neighbour. However, compared with the well-known mare volcanism surrounding the Chang’e-6 landing site, the intrusive magmatic activities have a much more obscure presence and origin, impeding future sample analyses when they are available for application.
In a recent research paper published in The Astrophysical Journal Letters, Dr Yuqi QIAN, Professor Joseph MICHALSKI and Professor Guochun ZHAO from the Department of Earth Sciences at The University of Hong Kong (HKU) and their domestic and international collaborators have comprehensively studied the intrusive magmatism of the Chang’e-6 landing site and its surroundings based on remote sensing data. The study revealed their extensive distributions and obscure nature with significant implications for the petrogenesis of lunar plutonic rocks and the Chang’e-6 mission, which will facilitate scientists’ further study of lunar farside.
In recent years, a community of researchers from various universities and institutes across Europe and the United States set out to explore the physics of micro-and nano-mechanical devices coupled to light. The initial focus of these investigations was on demonstrating and exploiting uniquely quantum effects in the interaction of light and mechanical motion, such as quantum superposition, where a mechanical oscillator occupies two places simultaneously. The scope of this work quickly broadened as it became clear that these so-called optomechanical devices would open the door to a broad range of new applications.
Hybrid Optomechanical Technologies (HOT) is a research and innovation action funded by the European Commission’s FET Proactive program that supports future and emerging technologies at an early stage. HOT is laying the foundation for a new generation of devices that bring together several nanoscale platforms in a single hybrid system. It unites researchers from thirteen leading academic groups and four major industrial companies across Europe working to bring technologies to market that exploit the combination of light and motion.
One key set of advances made in the HOT consortium involves a family of non-reciprocal optomechanical devices, including optomechanical circulators. Imagine a device that acts like a roundabout for light or microwaves, where a signal input from one port emerges from a second port, and a signal input from that second port emerges from a third one, and so on. Such a device is critical to signal processing chains in radiofrequency or optical systems, as it allows efficient distribution of information among sources and receivers and protection of fragile light sources from unwanted back-reflections. It has however proven very tricky to implement a circulator at small scales without involving strong magnetic fields to facilitate the required unidirectional flow of signals.
In recent years, these technological limitations have become far more pressing. Deep neural networks have radically expanded the limits of artificial intelligence—but they have also created a monstrous demand for computational resources, and these resources present an enormous financial and environmental burden. Training GPT-3, a text predictor so accurate that it easily tricks people into thinking its words were written by a human, costs $4.6 million and emits a sobering volume of carbon dioxide—as much as 1,300 cars, according to Boahen.
With the free time afforded by the pandemic, Boahen, who is faculty affiliate at the Wu Tsai Neurosciences Institute at Stanford and the Stanford Institute for Human-Centered AI (HAI), applied himself single mindedly to this problem. “Every 10 years, I realize some blind spot that I have or some dogma that I’ve accepted,” he says. “I call it ‘raising my consciousness.’”
This time around, raising his consciousness meant looking toward dendrites, the spindly protrusions that neurons use to detect signals, for a completely novel way of thinking about computer chips. And, as he writes in Nature, he thinks he’s figured out how to make chips so efficient that the enormous GPT-3 language prediction neural network could one day be run on a cell phone. Just as Feynman posited the “quantum supremacy” of quantum computers over traditional computers, Boahen wants to work toward a “neural supremacy.”
