3 h. ago Machine learning precisely predicts material characteristics for high

In the lab, perovskite solar cells show high efficiency in converting solar energy into electricity. In combination with silicon solar cells, they could play a role in the next generation of photovoltaic systems. Now researchers at KIT have demonstrated that machine learning is a crucial tool for improving the data analysis needed for commercial fabrication of perovskite solar cells. They present their results in Energy & Environmental Science.

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5 d. ago AI pioneers scoop Turing Award for reinforcement learning work

Two trailblazing computer scientists have won the 2024 Turing Award for their work in reinforcement learning, a discipline in which machines learn through a reward-based trial-and-error approach that lets them adapt within constrained or dynamic environments. Andrew G. Barto, a professor emeritus at the University of Massachusetts Amherst; and Richard S. Sutton, a professor at […] © 2024 TechCrunch. All rights reserved. For personal use only.

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6 d. ago New AI model detects toxic online comments with 87% accuracy

Computer scientists have developed a powerful machine learning model that can detect toxic social media comments with remarkable accuracy, paving the way for safer digital interactions.

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6 d. ago New AI model achieves 87% accuracy in detecting toxic online comments

Computer scientists have developed a powerful machine learning model that can detect toxic social media comments with remarkable accuracy, paving the way for safer digital interactions.

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7 d. ago Engineers create more effective burner to reduce methane emissions

Researchers at Southwest Research Institute (SwRI) and the University of Michigan (U-M) have published a new study showing an advanced new methane flare burner, created with additive manufacturing and machine learning, eliminates 98% of methane vented during oil production. The burner was designed by U-M engineering researchers and tested at SwRI.

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2 w. ago Figure’s humanoid robot takes voice orders to help around the house

Figure founder and CEO Brett Adcock Thursday revealed a new machine learning model for humanoid robots. The news, which arrives two weeks after Adcock announced the Bay Area robotics firm’s decision to step away from an OpenAI collaboration, is centered around Helix, a “generalist” Vision-Language-Action (VLA) model. VLAs are a new phenomenon for robotics, leveraging […] © 2024 TechCrunch. All rights reserved. For personal use only.

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2 w. ago Spore.Bio raises $23M to apply machine learning to microbiology testing

Recalls in the food and beverage industry due to contamination incidents can have catastrophic effects. Not only do companies have to pay fines and damages, but the impacts on the brand’s reputation can be long-lasting. That’s why Spore.Bio, a Paris-based deeptech startup, is trying to reinvent microbiology testing to avoid the next PR crisis in […] © 2024 TechCrunch. All rights reserved. For personal use only.

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2 w. ago Machine learning accelerates discovery of membranes to filter PFAS from water

Someday, your drinking water could be completely free of toxic "forever chemicals." These chemicals, called PFAS (per- and polyfluoroalkyl substances), are found in common household items like makeup, nonstick cookware, dental floss, batteries, and food packaging. PFAS permeate the soil, water, food, and air, and they can remain in the environment for millennia. Once inside the human body, PFAS can persist for years, suppressing the immune system and increasing cancer risk.

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3 w. ago Machine learning transforms mini biohybrid ray design, doubling swimming efficiency

A new study shows an application of machine-learning directed optimization (ML-DO) that efficiently searches for high-performance design configurations in the context of biohybrid robots. Applying a machine learning approach, the researchers created mini biohybrid rays made of cardiomyocytes (heart muscle cells) and rubber with a wingspan of about 10 mm that are approximately two times more efficient at swimming than those recently developed under a conventional biomimetic approach.

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3 w. ago AI model deciphers the code in proteins that tells them where to go

Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.

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3 w. ago How machine learning can boost accuracy of solar power forecasts

As solar energy plays an increasing role in the global power supply, ensuring accurate forecasts of photovoltaic (PV) power generation is critical for balancing energy demand and supply.

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4 w. ago Machine learning method improves semiconductor band gap predictions

Imagine you're cooking. You're trying to develop a unique flavor by mixing spices you've never combined before. Predicting how this will turn out could be tricky. You want to create something delicious, but it could end up tasting awful: a waste of time and ingredients.

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