People can trust each other because they understand how the human mind works, can predict people’s behavior, and assume that most people have a moral sense. None of these things are true of AI.
A tsetse fly (Glossina sp) in the Udzungwa Mountains National Park, Tanzania.
Minden Pictures/Alamy
In the future, our computer may be able to produce long-term forecasts in areas such as climate change, bushfires and financial markets – while being cheaper and more accessible than supercomputers.
You can’t see inside any opaque box, but the color black adds an air of mystery.
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Metaphorical black boxes shield the inner workings of AIs, which protect software developers’ intellectual property. They also make it hard to understand how the AIs work – and why things go wrong.
The sky is big and full of information that AI tools can help astronomers unlock.
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Artificial intelligence tools are making waves in almost every aspect of life, and astronomy is no different. An astronomer explains the history and future of AI in understanding the universe.
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.
Our research on a recent Australian court case shows how experts and lawyers can overcome opaque AI technology. But regulators could make it even easier, by making AI companies document their systems.
An image created by DALL-E 2 in response to the prompt ‘a robot hand drawing’.
OpenAI
New software that can generate images and text on command may deliver ‘good enough’ creativity in advertising, copywriting, stock imagery and graphic design.
People can have several thousand thoughts per day, many of which can be classified as spontaneous or involuntary.
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Emotions play a key role in many types of spontaneous thoughts. Even microemotions — which are often fleeting and unconscious — can affect thoughts and influence attention.
Eliminating human guesswork can make for faster and more accurate research.
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Understanding when and how neurons die is an important part of research on neurodegenerative diseases like Lou Gehrig’s, Alzheimer’s and Parkinson’s diseases.
De novo protein design with deep learning can open new doors for medicine and many other fields.
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Using a form of artificial intelligence called deep neural networks, researchers can generate new proteins from scratch without having to consult nature.