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Supervisor Elham AbolFateh
Editor in Chief Mohamed Wadie

Musk Reveals New Electronic Mental Chip


Sat 29 Aug 2020 | 11:34 AM
Ahmed Yasser

Elon Musk announced a pig whose brain he claimed has been implanted with a small computer chip. According to Times, the pig named Gertrude was presented during a live stream event of his company Neuralink.

Gertrude's coin-sized computer chip was described as a Fitbit in your skull with tiny wires.

On other hand, the new device unveiled on Friday is much smaller and does not require the visible ear device. It would be implanted in the brain by a surgical robot under local anaesthesia.

Musk co-founded Neuralink in 2016 with an aim to create a wireless brain-machine interface.

Also, he showed off another pig named Dorothy and claimed that the device had been implanted and subsequently removed.

What Dorothy illustrates is that you can put in the Neuralink, remove it, and be healthy, happy and indistinguishable from a normal pig.

According to Reuters, Neuralink has raised over $150 million in funding, including $100m from Musk himself, the Guardian reported.

The company has about 100 employees, but could soon expand to 10,000, Musk said at the event.

The Tesla CEO also announced that the US Food and Drug Administration (FDA) has awarded Neuralink a breakthrough device authorisation which can help expedite research on a medical device.

The ultimate goal for Neuralink is a full brain-machine interface which will achieve a symbiosis with artificial intelligence.

Noteworthy, startups such as Kernel, Paradromics and NeuroPace also are trying to exploit advancements in material, wireless and signaling technology to create similar devices to Neuralink.

In addition, medical device giant Medtronic PLC produces brain implants to treat Parkinson’s disease, essential tremors and epilepsy.

Amy Orsborn, an assistant professor at the University of Washington who researches neural interfaces explained that scientists still face a range of issues, including preventing tissue scarring around the implant.

The quality of measurements and the development of machine-learning algorithms to interpret brain signals.