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Now the answer is in — and not at all. Four years after the announcement of the “incredibly crazy” project to create a “speechless word” using reading technology to read ideas, Facebook is shutting down the process, claiming that consumer brain reading is still a long way off.
Mu post, Facebook has said it is banning the project and will instead consider considering a trial hand to make this possible reads manuscripts manually. “While we still believe in the short-term potential of using a head-to-head interface [brain-computer interface] technologies, we are determined to focus on the neural pathway that is closest to the market, ”the company said.
The Facebook posting process that Facebook led made it anonymous – inclusive supporting brain surgery at another hospital in California and made iconic hats that could be shot in the head – and argued fiercely for modern companies to be able to learn more about the brain. In conclusion, however, the company seems to have decided that this research will not only bring products soon.
“We have a knack for mastering these technologies,” said Mark Chevillet, a scientist and psychologist who until last year led a silent speech but recently switched positions to learn how Facebook manages elections. “That’s why we can confidently say, as a tool, a silent head-talking tool is still a long way off. It’s taking longer than we think.”
Reading minds
What makes people use computers is that companies view mind-driven software as a major factor – as important as a computer mouse, display interface, or image exchange. In addition, researchers have already shown that when they place electrons directly in the brain to capture neurons, the results are astounding. Patients with such implants are more likely to be paralyzed cleverly switch robotic arms and play video games or write through mind-correction.
Facebook’s goal was to turn the findings into a consumer-oriented technology that anyone could use, which means a hat or headband that you can wear and take off. “We never intended to produce a brain chemistry,” says Chevillet. In view of the many challenges the company has faced, Mark Zuckerberg has said that the last thing the company should do is crack skulls. “I do not want to see legal discussions on legal issues,” he said. he joked.
Instead, with the advent of brain-computer communication, there are new challenges. What would happen if modern corporations knew the public opinion? In Chile, lawmakers are also considering legislation to protect human rights brain data, freedom of choice, and privacy from professional manufacturing companies. Since Facebook has not been well-publicized, the idea of suspending the survey may be of some benefit due to the distance between the company and the concern for “neurorights.”
The Facebook project is aimed at a brainwasher that can have real ambitions; bought Oculus VR in 2014 for $ 2 billion. To get there, the company took two routes, says Chevillet. First, it is necessary to know whether a coherent form is possible. For these reasons, it contributed to research at the University of California, San Francisco, where researcher Edward Chang placed electrons above the human brain.
When embedded electrons read data from single neurons, this method, called electrocorticography, or ECoG, measures the size of the major nerve cells at the same time. Chevillet says Facebook hopes it will also be possible to identify similarities from the outside of the headline.
The UCSF team has made remarkable progress and today reports in the New England Journal of Medicine that it used electrode pads to change voice in real time. The case involved a 36-year-old man whom the researchers called “Bravo-1,” who suffered a massive stroke and could not make a sound and could only whisper or moan. In their report, Chang’s team claims that with electrons above their brains, Bravo-1 has been able to create computer-generated sentences at a rate of about 15 words per minute. This technology involves measuring neural signals in the motor cortex that are related to Bravo-1’s movements that move its tongue and voice when it thinks it is speaking.
To that end, the Chang team asked Bravo-1 to consider uttering one of 50 common words in 10,000, feeding the patient’s symptoms for in-depth study. After training the nation to match words with neural signals, the team was able to accurately identify the word Bravo-1 assuming to say 40% of the time (probability would be about 2%). Even so, his conclusions were flawed. “Hello how are you?” can come out “Hungry, how are you.”
But scientists have changed the way we work by adding a language – a program that determines which movements are available in English. This increased the accuracy to 75%. With this cyborg approach, the machine can predict that the Bravo-1 statement “I’m right with my nurse” means “I love my nurse.”
The result is astonishing, there are over 170,000 words in English, so performance can drop out of Bravo-1’s unconventional word. This means that this approach, while potentially useful as a treatment, is not as close to what Facebook had. “We’re seeing programs in the future of technical support in the hospital, but that’s not where our business is,” says Chevillet. “We’re really looking at consumer services, and there’s a very long way to go.”
Light failure
Facebook’s idea of quitting brain reading is not surprising to researchers who learn these skills. “I can’t say I’m surprised, because he had said he was looking for a short time and reviewing things,” said Marc Slutzky, a professor at Northwestern whose former student Emily Mugler was a key figure in Facebook’s work. “Speaking from experience, the goal of translating words is very difficult. We are still far from a practical, all-inclusive answer.”
However, Slutsky says UCSF’s work is “the next best part” that demonstrates the incredible potential and limitations of brain science. “It still looks like you can choose free speech,” he says. “Patients who say ‘I want to drink water’ compared to ‘I want my medicine’, are different.” He says that if the types of cosmetics can be taught over a long period of time, as well as on more than one brain, they can change rapidly.
While UCSF research was being conducted, Facebook also paid for other sites, such as the Applied Physics Lab at Johns Hopkins, to learn how to make light through a skull to read neurons regardless. Similar to MRI, these scans rely on light detection that measures blood volume in areas of the brain.
It is a technology that remains a major stumbling block. Even with recent changes, including some on Facebook, they may not be able to carry neural signals with sufficient thought. Another problem, says the Chevillet, is that blood flows in a way that they see happening after five seconds a group of neurons burn, which in turn reduces the ability to run a computer.
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