Living brain cells enable machine learning computations
A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously carried out by artificial systems. By integrating cultured neuronal networks into a machine learning framework, the team showed that these biological systems can generate complex time-series signals, marking a significant step forward in both neuroscience and bio-inspired computing.
The rapid advancement of artificial intelligence (AI) and machine learning systems has increased the demand for new hardware components that could speed up data analysis while consuming less power. As machine learning algorithms draw inspiration from biological neural networks, some engineers have been working on hardware that also mimics the…
Recent AI advances enable modeling of weather forecasting 4-5 magnitudes faster than traditional computing methods. The brightest leaders, researchers and developers in climate science, high performance computing and AI will discuss such technology breakthroughs — and how they can help foster a greener Earth — at NVIDIA GTC. The virtual…