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Google researchers have created an 'AI child' that can outperform its human-made counterparts.
The machine learns through 'reinforcement learning' which means it trains for a task, reports back to its AI 'parent' and then learns how it can do it better.
AI - Objects - People - Cars - Handbags
This particular AI recognises objects, such as people, cars, handbags and traffic lights, in real time in a video.
The creation of this AI child is proof some machine-made programmes are now more accurate than ones created by humans.
AI - Child - NASNet - Network - AutoML
The AI child, called NASNet, is controlled by a neural network called AutoML, made by Google Brain, which teaches the 'child' to do specific tasks.
The process is repeated thousands of times.
Researchers - NASNet - Cent - Accurate - Images
Eventually researchers found NASNet was 82.7 per cent accurate at predicting images correctly.
This is 1.2 per cent better than previously published results and the system is now four per cent more efficient, writes Science Alert.
Findings - Automation - AI
The findings show automation could create more AI all by themselves.
Because the system is 'open source', developers are able to expand on their programme or develop a similar version.
Researchers - Blog - Post - Developers - 'multitudes
Researchers said in a blog post they hope developers will be able to create 'multitudes of computer vision problems we have not yet imagined'.
However, such developments come with ethical problems and many people have warned of the dangers of developer super-smart AI.
End - Month - Tesla - CEO - Elon
At the end of the last month, Tesla CEO Elon Musk once again spoke about his fears over the rise of machines.
Responding to footage of a 6ft9 back-flipping robot, the Tesla CEO spoke of the need to control development of AI, or else it could be 'sweet dreams' for mankind.
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