Lifeboat Foundation: Safeguarding Humanity
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Category: robotics/AI – Page 1,895

Quantum computing, for its parts, replaces the traditional 1 and 0 computer binary system with a system that calculates the chances of 1 and 0—meaning that it could have both 1 and 0 at the same time, but with different probabilities. “This enables the computing of certain aspects far faster and in a more efficient manner. The computing time could be 1,000 or 10,000 times faster,” said Lupa. When combined with artificial intelligence, machines could learn on their own with the speed of quantum computing, he stated.

At the moment, only massive quantum computers exist, while quantum communications are still at the proof of concept stage. Quantum radars have made some progress. But all of this is expected to change.

“In the end, it will be a revolution,” said Lupa. “But it will not happen tomorrow. When these things become accessible to everyone, then it will be revolutionary.”

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A new blood test that can detect methylation of DNA can accurately predict whether a person has any one of 50 cancers and where the tumour is growing.

The California-based healthcare company Grail, which developed the test, owns a large database of methylation patterns in cancerous and non-cancerous cell-free DNA. From that repository, a machine learning program was developed to analyse blood samples. The algorithm identified methylation changes that are classified as cancerous or non-cancerous, and it could even pinpoint the tissue of origin before the onset of symptoms.

Validation of the test was carried out by researchers from the US at the Mayo Clinic, Cleveland Clinic and Harvard medical school, working with colleagues at the Francis Crick Institute and University College London in the UK. In all, more than 15,000 volunteers from over 140 clinics in North America took part, and their samples revealed that this ‘liquid biopsy’ had a 0.7% false positive rate for cancer detection. The test was also able to predict the tissue that the cancer originated in with more than 90% accuracy. It performed best on 12 of the most common cancers, including ones that are most lethal and have no established screening paradigms such as pancreatic and ovarian cancers.

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Alongside the news that Boston Dynamics is going to let its robot dog, Spot, out of its laboratory for the first time, the company has released a new video of Atlas, its spectacular bipedal robot that’s previously been seen doing everything from parkour to backflips. In this latest video, Atlas does a small gymnastics routine, consisting of a number of somersaults, a short handstand, a 360-degree spinning jump, and even a balletic split leap.

What’s most impressive is seeing Atlas tie all these moves together into one pretty cohesive routine. In the video’s description, Boston Dynamics says that it’s using a “model predictive controller” to blend from one maneuver to the next. Presumably each somersault gives the robot a fair amount of forward momentum, but at no point in the video does it seem to lose its balance as a result. Amazingly, Atlas is able to roll gracefully along its back without any of its machinery getting squashed or tangled.

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Cancer is one of humanity’s leading killers, and the main reason for that is it’s often hard to detect until it’s too late. But that might be about to change. Researchers have developed a new type of AI-powered blood test that can accurately detect over 50 different types of cancer and even identify where it is in the body.

There are just so many types of cancer that it’s virtually impossible to keep an eye out for all of them through routine tests. Instead, the disease usually isn’t detected until doctors begin specifically looking for it, after a patient experiences symptoms. And in many cases, by then it can be too late.

Ideally, there would be a routine test patients can undergo that would flag any type of cancer that may be budding in the body, giving treatment the best shot of being successful. And that’s just what the new study is working towards.

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An artificial intelligence can accurately translate thoughts into sentences, at least for a limited vocabulary of 250 words. The system may bring us a step closer to restoring speech to people who have lost the ability because of paralysis.

Joseph Makin at the University of California, San Francisco, and his colleagues used deep learning algorithms to study the brain signals of four women as they spoke. The women, who all have epilepsy, already had electrodes attached to their brains to monitor seizures.

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“We are not there yet but we think this could be the basis of a speech prosthesis,” said Dr Joseph Makin, co-author of the research from the University of California, San Francisco.

Writing in the journal Nature Neuroscience, Makin and colleagues reveal how they developed their system by recruiting four participants who had electrode arrays implanted in their brain to monitor epileptic seizures.

These participants were asked to read aloud from 50 set sentences multiple times, including “Tina Turner is a pop singer”, and “Those thieves stole 30 jewels”. The team tracked their neural activity while they were speaking.

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