Enthusiasm for the capabilities of artificial intelligence – and claims for the approach of humanlike prowess –has followed a boom-and-bust cycle since the middle of the 20th century.
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Articles on Artificial neural networks
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Technological approaches could help reduce the carbon impact of artificial intelligence systems.
A tangle of silver nanowires may pave the way to low-energy real-time machine learning.
Computer-based neural networks can learn to do tasks. A new type of material, called a mechanical neural network, applies similar ideas to a physical structure.
We’ve seen AI systems writing texts that are indistinguishable from human texts. Some are even rendering impressive 3D artworks from short text inputs. But it doesn’t mean they can ‘think’ like us.
The miniature brains of honeybees were able to understand the concepts of odd and even, despite only having 960,000 neurons (compared to 86 billion in humans).
The knowledge produced in designing and developing artificial neural networks may provide new insights into how our brains work.
Finding out more about how the brain works could help programmers translate thinking from the wet and squishy world of biology into all-new forms of machine learning in the digital world.
Bitcoin trading is difficult to predict, but artificial neural networks may be able to discern patterns.
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