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Neuralink: A brighter future or a dystopia coming true?

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In late August Elon Musk, the South African billionaire entrepreneur, unveiled the Neuralink chip which meant a scientific breakthrough for many and the beginning of a dystopian future for others.

In this article we’ll look at this chip from a simple point of view. What is it? How does it work? And why was it made?
Neuralink is a company based in California founded by no other than Elon Musk, the CEO. He funded the company with 100 million dollars from his fortune. The company is quite small, employing only about 100 highly qualified employees. Don’t be fooled, it may seem like a small number, but these individuals have achieved wonders with their ambition.

Now before talking about the chip, let’s talk about the brain. Our brains are basically computers, very sophisticated computers. A computer would be transmitting binary data in 0 and 1, and the data would be circulating within the integrated circuit like cars do on a highway, fast and in large quantities.

Our brains are quite similar, in the brain there are links, known as neurons, through which data in the form of electrical impulses move. If you move your hand scrolling down this article, that means your brain sent such electrical impulses through your nerves to reach your hand.

During last August’s webcast demo, Musk showed the audience three pigs; one with no chip,one which had the chip implanted in its head but removed and one which had the chip still implanted. All were alive, well and seemed to act normal. What was special however was that the third pig’s brain transmitted data to a screen when the pig was eating straws. With each move, the graph on the screen showed a peak in the brain activity.

The chip implanted in the pig’s head is planned to go on human trials in the future. It does have specifications just like a smartphone, it’s 23mm by 8mm, a megabyte wireless transmission rate and a battery that can hold all day thus the user can recharge it at night while sleeping and yes, it’s wireless charged.

The chip has about 3000 electrodes, they are basically very small sensors, thinner than a human hair. These electrodes monitor the brain.They can receive and transmit data to any connected device. At least that’s what Elon is planning.

The chip is aimed to cure diseases and disabilities such as blindness, Parkinson, nerve damage and even depression and anxiety. Elon went further in his demo mentioning the Dystopian TV series « Black Mirror » and stating that the Neuralink chip can allow people to store and save their memories. The user can pay a couple thousand dollars, the price of a laser eye surgery, get the chip implanted under his skull and leave the hospital on the same day!

However, as ambitious as it seems, scientists and experts are doubting whether such a bold project can succeed within the expected time frame. They believe that the data transmitted within our brains is quite hard to decrypt anytime soon and thus Musk may be aiming too far for what science can do for now. Nevertheless the project is seen as a step forward in neurotechnology.

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Sciences et technologie

Episode 2: Buying a Soccer Team

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As we are progressing into a world where sports have become a vital part of our lives, it has also become a hot market for investors to gain greater income. We can also see that there has been a surge in sports viewership which leads to more tournaments. Capitalizing on them has become a difficult task for an investor. So a programmers team have come up with a strategy to build the best team whilst keeping in mind the investor’s budget which has a limit of 1 billion Euros relying on Machine learning algorithms to detect potential recruits for their clubs and potential assets for the investor to optimize their market gains.

How does that work ?

The team have a FIFA dataset in which there are few columns named — rating, release clause, and wages. They built 2 models using Supervised Learning on Rating variables and made it a classification problem by splitting this variable into 2 classes: greater than or equal to 70 and less than 70 ratings. They chose 70 as their threshold as most of the major clubs have only players with ratings greater than 70. In the second model, the rating class was obtained from previous best classifiers instead of « actual rating » and the release-clause was combined with annual wages to determine the cost to investors.

Dataset

The dataset used is FIFA 19 and FIFA 20 data which contain 18k+ unique player ratings with 100+ different attributes for each player:

  • Player positions, with the role in the club and in the national team.
  • Player attributes with statistics as Attacking, Skills, Defense, Mentality, GK Skills, etc.
  • Player personal data like Nationality, Club, DateOfBirth, Wage, Salary, etc.

Example: Bangladesh National Team

Due to the miscoordination among the players recently, the national team of Bangladesh slipped to their worst ever FIFA ranking of 194th. The ultimate success of a team depends upon its player selection. Generally, the coach and the management team select the best 11 players for each match from a pool of players by evaluating various attributes of the players. Now, using these Machine Learning algorithms, a better player classification technique is proposed and the soccer team is formed automatically of the best player combination possible. The results achieved based on the performance attributes would help the coach and management team to build up a more successful soccer team.

Conclusion

The constructed 2 models that utilize Machine learning algorithms benefit investors while simultaneously select the rightfully classified players as good performers and then regress them in the budget of the investor. Ultimately, the narrowed down selection process of a player within a club is rather better than selecting at random.

 

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