Artificial intelligence (AI) can help people shop, plan, and write—but not cook. It turns out humans aren’t the only ones who have a hard time following step-by-step recipes in the correct order, but new research from the Georgia Institute of Technology’s College of Computing could change that.
Danish architect Bjarke Ingels has collaborated with clothing brand Vollebak to design an entirely self-sufficient, off-grid island home in Nova Scotia, Canada.
Planned for an island within Jeddore Harbour, the house is designed to exemplify the clothing brand’s ideals and Ingels’ studio BIG’s “philosophy of hedonistic sustainability”.
“Vollebak is using technology and material innovation to create clothes that are as sustainable and resilient as they are beautiful,” said Ingels.
The arrangement of electrons in matter, known as the electronic structure, plays a crucial role in fundamental but also applied research, such as drug design and energy storage. However, the lack of a simulation technique that offers both high fidelity and scalability across different time and length scales has long been a roadblock for the progress of these technologies.
Researchers from the Center for Advanced Systems Understanding (CASUS) at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) in Görlitz, Germany, and Sandia National Laboratories in Albuquerque, New Mexico, U.S., have now pioneered a machine learning–based simulation method that supersedes traditional electronic structure simulation techniques.
Their Materials Learning Algorithms (MALA) software stack enables access to previously unattainable length scales. The work is published in the journal npj Computational Materials.
Interesting discovery! I’d love to see it in action.
A new ferroelectric polymer that efficiently converts electrical energy into mechanical strain has been developed by Penn State researchers. This material, showing potential for use in medical devices and robotics, overcomes traditional piezoelectric limitations. Researchers improved performance by creating a polymer nanocomposite, significantly reducing the necessary driving field strength, expanding potential applications.
A new type of ferroelectric polymer that is exceptionally good at converting electrical energy into mechanical strain holds promise as a high-performance motion controller or “actuator” with great potential for applications in medical devices, advanced robotics, and precision positioning systems, according to a team of international researchers led by Penn State.
Notpla has been announced as the winner of Prince William’s Earthshot Prize, in the category of ‘Build a Waste-Free World’!
Continue reading “Seaweed to Replace Plastic | Edible & Biodegradable Packaging | Notpla” »
Italian architect Gae Avitabile has designed the interior of Civico 29, a sea-inspired cocktail bar in an Italian coastal town.
FRO is effective against acne
The disc diffusion experiment results indicated that 20 μL FRO successfully suppressed CA growth, producing distinct 13 mm inhibition zones at a concentration of 100 mg/mL. FRO significantly suppressed CA-induced increases in sebum production, thereby slowing or reversing acne onset.
FRO was found to be rich in phenolic compounds, including gallic acid, kaempferol, quercetin, and fisetin. The concentration of total phenolic compounds (TPCs) averaged 118.2 mg gallic acid equivalents (GAEs) for every gram of FRO.
388 likes, — AI-GPT Insights (@aigptinsights) on Instagram: The future of Al Automations is here.
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Reservoir computing is a promising computational framework based on recurrent neural networks (RNNs), which essentially maps input data onto a high-dimensional computational space, keeping some parameters of artificial neural networks (ANNs) fixed while updating others. This framework could help to improve the performance of machine learning algorithms, while also reducing the amount of data required to adequately train them.
RNNs essentially leverage recurrent connections between their different processing units to process sequential data and make accurate predictions. While RNNs have been found to perform well on numerous tasks, optimizing their performance by identifying parameters that are most relevant to the task they will be tackling can be challenging and time-consuming.
Jason Kim and Dani S. Bassett, two researchers at University of Pennsylvania, recently introduced an alternative approach to design and program RNN-based reservoir computers, which is inspired by how programming languages work on computer hardware. This approach, published in Nature Machine Intelligence, can identify the appropriate parameters for a given network, programming its computations to optimize its performance on target problems.
That was fast.
We’ve heard plenty of rumors about Windows 12 this year. While Microsoft has yet to officially confirm it is in the works, there have been several hints pointing to its existence. One of these came at the Build 2023 developer conference in the form of a video screenshot that referred to a “next generation” of Windows. That presumably refers to Windows 12 and hopefully not a fully cloud-based Windows 11.
Microsoft has also referred to a “Next Valley Prototype Design,” said to be a codename for the next-generation of Windows.
