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Humanity’s days are numbered, Artificial Intelligence (AI) will cause mass extinction, warns Stephen Hawking

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Scientist Stephen Hawking giving his views on the danger of Artificial Intelligence (AI)
Scientist Stephen Hawking giving his views on the danger of Artificial Intelligence (AI)

London, Nov 3: Earth is becoming too small and humanity is bound to self-destruct, with Artificial Intelligence (AI) replacing us as the dominant being on the planet, according to scientist Stephen Hawking.

Professor Hawking says that our time on Earth is numbered after we passed the point of “no return”.

The theoretical physicist says that developments in AI have been so great that the machines will one day be more dominant than human beings, express.co.uk reported.

He told Wired Magazine: “I fear that Artificial Intelligence (AI) may replace humans altogether. If people design computer viruses, someone will design AI that improves and replicates itself.

“This will be a new form of life that outperforms humans.”

Hawking, 75, said that humans need to leave Earth if we are to continue as a species.

He said a new space programme should be humanity’s top priority “with a view to eventually colonising suitable planets for human habitation”.

This will allow us to leave Earth and colonise another planet to ensure our survival, otherwise there will be “serious consequences”.

Professor Hawking added: “I believe we have reached the point of no return. Our earth is becoming too small for us, global population is increasing at an alarming rate and we are in danger of self-destructing.”

Last year, at the opening of Cambridge University’s artificial intelligence centre, Professor Hawking said that AI could either be the best or worst invention humanity has ever made.

“This will be a new form of life that outperforms humans.”

“The potential benefits of creating intelligence are huge. We cannot predict what we might achieve, when our own minds are amplified by Artificial Intelligence (AI).

“Perhaps with the tools of this new technological revolution, we will be able to undo some of the damage done to the natural world by the last one – industrialisation.

“And surely we will aim to finally eradicate disease and poverty. Every aspect of our lives will be transformed, In short, success in creating AI, could be the biggest event in the history of our civilisation.

“But it could also be the last, unless we learn how to avoid the risks. Alongside the benefits, AI will also bring dangers, like powerful autonomous weapons, or new ways for the few to oppress the many.” (IANS)

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Artificial Intelligence to Play a Critical Role in Diagnosing Breast Cancer Quickly

"We had about 80 per cent accuracy rate. We will continue to refine the algorithm by using more real-world images as inputs,” Oberai said

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Cancer, Patients, Invasive
The treatments kill healthy cells as well as cancerous ones, and the side effects are legendary. Pixabay

Breast ultrasound elastography is an emerging imaging technique that provides information about a potential breast lesion and researchers have identified the critical role AI can play in making this technique more efficient and accurate.

Using more precise information about the characteristics of a cancerous versus non-cancerous breast lesion, this methodology using Artificial Intelligence (AI) has demonstrated more accuracy compared to traditional modes of imaging.

In the study published in the journal Computer Methods in Applied Mechanics and Engineering, Indian-origin researchers Dhruv Patel and Assad Oberai from the University of Southern California showed that it is possible to train a machine to interpret real-world images using synthetic data and streamline the steps to diagnosis.

In the case of breast ultrasound elastography, once an image of the affected area is taken, it is analysed to determine displacements inside the tissue. Using this data and the physical laws of mechanics, the spatial distribution of mechanical properties, like its stiffness, is determined.

In the study, researchers sought to determine if they could skip the most complicated steps of this workflow.

Cancer
Cancer Ribbon. Pixabay

For this, the researchers used about 12,000 synthetic images to train their Machine Learning algorithm. This process was similar to how photo identification software works, i.e learning through repeated inputs on how to recognize a particular person in an image, or how our brain learns to classify a cat versus a dog.

Through enough examples, the algorithm was able to glean different features inherent to a benign tumour versus a malignant tumour and make the correct determination.

Also Read- Over 16 Million Accounts of Indian Influencers on Instagram are Fake

The researchers achieved nearly 100 per cent classification accuracy on synthetic images. Once the algorithm was trained, they tested it on real-world images to determine how accurate it could be in providing a diagnosis, measuring these results against biopsy-confirmed diagnoses associated with these images.

“We had about 80 per cent accuracy rate. We will continue to refine the algorithm by using more real-world images as inputs,” Oberai said. (IANS)