Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...

The second approach uses generative AI to produce data. Modern generative models are trained on vast amounts of data and can ...

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...

The study demonstrates machine learning's role in predicting compressive strength of rice husk ash concrete, aiding the shift ...

A machine-learning breakthrough could lift the veil on Earth’s early history—and supercharge the search for alien life ...

AI bias is not merely a technical flaw – it is a reflection of the human decisions and governance structures that shape ...

They built four models through which it could distinguish things with biological antecedents from things which lacked them.

While mind-controlled prosthetics still rely on expensive amplifiers & electrode arrays, a 16-year-old has built a functional ...

Though AI models have been trained to emit the correct answer and to recognize that "2 + 2 = 5" might be a reference to the ...

Research led by Rutgers engineers has shown how artificial intelligence (AI) can solve two of the biggest challenges in ...

Five federally funded AI institutes provide a backbone for agriculture-focused AI research. The grand challenge facing global agriculture today is the need to increase food production to feed a ...

MES is transforming into the intelligence core of digital manufacturing, orchestrating every aspect of the shop floor.