Making AI Better at Learning

According to MIT Technology Review, researchers are working to enable ‘Less than one’ learning technology into artificial intelligence. 

Machine learning typically requires tons of examples. To get an AI model to recognize a horse, you need to show it thousands of images of horses. This is what makes the technology computationally expensive—and very different from human learning. 

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AI Still Needs Training To Understand Us

While artificial intelligence (AI) continues making headlines and breaking barriers that were thought to be impossible a decade ago, humans are now looking at it with both awe and fear. This is understandable because no one can allow their work to be taken away or to be replaced in places where they have for years looked for their daily bread. When people hear that companies are building AI-powered assistants to help in different tasks, they get afraid that AI is close to becoming independent of humans. The questions that they often ask are; Is AI close to matching human intelligence? Are we close to the fictional Skynet predicted in the Terminator? Is AI smart in its own and will it take positions long occupied by humans?

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AI is Getting Closer to Understanding Humans

Artificial intelligence (AI) is one of the leading (if not the leading) topics of conversation these days. The recent advances in AI have made it even more than before and are now closer to reality than you might imagine. Until the last decade, computers were not as sophisticated at producing sentences that make sense. They could not compete with humans in many aspects and humans seem irreplaceable in areas such as language. However, the past few years has changed the narrative completely. The field of natural language processing (NLP) has advanced significantly and machines are now competing humans and are even showing signs of understanding human language.

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