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Inside Microsoft’s Sci-fi Human Body Tracking Cryptocurrency

Microsoft has applied for a patent of a cryptocurrency system using body activity data. In the filing, the multinational conglomerate argued that, as a part of a cryptocurrency mining process, a task can be given to a user to complete. The cryptocurrency system can give a task to your device instructing you to complete a “human body activity.” 

A sensor in the user’s device may sense the body activity of the user for verification, where upon the cryptocurrency system awards the user, whose body activity data is verified. “The sensed body activity is associated with the received task; and transmit the generated body activity data to a system or network which verifies the body activity data to award cryptocurrency.”

Basically, a task is given to a user as a solution to “mining” challenges in the cryptocurrency system. “For example, a brain wave or body heat emitted from the user when the user performs the task provided by an information or service provider, such as viewing advertisement or using certain internet services, can be used in the mining process,” reads the filing. “Instead of massive computation work required by some conventional cryptocurrency systems, data generated based on the body activity of the user can be a proof-of-work, and therefore, a user can solve the computationally difficult problem unconsciously.”

Microsoft claims its system could reduce the computational energy used during the mining process––even speeding it up. The system would not necessarily be implemented into a blockchain. “The cryptocurrency system detailed does not necessarily need to be implemented on a blockchain,” according to the filing. “The system, method, and computer program products described herein may be applied to both centralized and decentralized cryptocurrency networks or databases.” 

The filing says communication networks are not limited to computer networks, telecommunication networks (cellular), mobile wireless data networks, and any combination thereof. “User device may include any device capable of processing and storing data/information and communicating over communication network,” states the filing “For example, user device may include personal computers, servers, cell phones, tablets, laptops, smart devices (e.g. smart watches or smart televisions).” 

A sensor, which could come in the form of a wearable, could sense the body activity of a user. For instance, functional magnetic resonance imaging (fMRI) scanners or sensors, electroencephalography (EEG) sensors, near infrared spectroscopy (NIRS) sensors, heart rate monitors, thermal sensors, optical sensors, radio frequency (RF) sensors, ultrasonic sensors, cameras, or any other sensor or scanner that can measure or sense body activity or scan the human body.

The fMRI could measure body activity, such as blood flow in the brain to identify different types of activity, and use a magnetic field and radio waves to create detailed images of the body.

The filing links to a Berkeley study revealing “how the fMRI can measure brain activity associated with visual information and generate image data.”

In the study, UC Berkeley researchers used fMRI and computational models to decode and reconstruct the visual experiences of the mind. For the study, subjects watched Hollywood movie trailers. The technology can for now only recreate movie clips people already viewed, but the goal is to reproduce the visual thoughts inside our heads, such as dreams and memories.

“This is a major leap toward reconstructing internal imagery,” said Professor Jack Gallant, a UC Berkeley neuroscientist and coauthor of the study published online today (Sept. 22) in the journal Current Biology. “We are opening a window into the movies in our minds.”

In short, the researchers decoded brain signals generated by moving pictures. “Our natural visual experience is like watching a movie,” said Shinji Nishimoto, lead author of the study and a post-doctoral researcher in Gallant’s lab. “In order for this technology to have wide applicability, we must understand how the brain processes these dynamic visual experiences.” 

Users may only be connected to the blockchain during a certain period of time each day. Tasks include the following: 

  • watching or listening information (e g. advertisement) for a certain time using services (e.g. search engine, chat bot, e-mail, social media/networking service and any internet or web service)
  • uploading or sending information/data to a website, a server or a network (e.g. content sharing website, and cloud network or server), or any other information or service which may produce effects on users. 
  • a transaction in the public ledger.

The system could be secured by a “Computer Automated Program to Tell Computers and Flumans (sic) Apart (CAPTCHA) and reCAPTCHA.” The sensor on the cryptocurrency contraption senses the body activity of the user that is body response related to the task provided by the task server, and transmits the sensed body activity to the device. 

Body activity could mean radiation emitted from human body (heat of the body, pulse rate, or brain wave), brain activities, body fluid flow (e.g. blood flow), organ activity  or movement, body movement, and any other activities that can be sensed and represented in the form of images, waves, signals, texts, numbers, degrees, or any other form of information or data.

Examples of body radiation emitted from the human body may include radiant heat of the body, pulse rate, or brain wave. Brain waves might include gamma waves, such as learning or memory tasks, beta waves, involved in logical thinking and/or conscious thought, alpha waves, potentially related to subconscious thoughts, theta waves that are involved in deep and raw emotions and delta waves related to sleep and deep relaxation. 

An electroencephalogram (EEG) might evaluate the electrical activity in the brain. Body movement includes eye movement, facial movement or any other muscular movements. Brain activity can be sensed using fMRI. The cryptocurrency system verifies if the body activity data o user generated by user device satisfies one or more conditions set by the algorithm.

“The conditions may be set by simulating human body activity across all of body activities that can constitute hashes,” reads the filing. “Machine learning algorithms may be used to simulate body activities and set the conditions for valid body activities, for example, but not limited to, using generative adversarial networks.”

The filing continues: “If the hash of the body activity of user has the desirable patterns or is within the target range, then the proof of work or proof of stake is considered solved, and that hash can be a new block. The target range or value may be changed periodically to maintain a preselected level of difficulty, although it is not required. For example, the target value may be inversely proportional to the difficulty. By varying the difficulty, a roughly constant rate of block generation may be kept.”

The system might use statistical data so that normal body activity, easy activities, or fake body activities does not get validated. “The target range of valid body activity may be selected from a range that human miners cannot fake their own body activity to satisfy the target range to prove and validate the proof-of-work,” reads the filing. “At operation, cryptocurrency system may check whether the hash of the body activity, received from user device is within the target range set by the cryptocurrency system, or comprises a desirable pattern set by the cryptocurrency system.” 

When the completion of a task is successfully verified, the cryptocurrency system then awards cryptocurrency to you. “For example, a cryptocurrency system awards to user an amount of cryptocurrency corresponding to the task accomplished by user.” 

The filing puts forth certain activities for which you might be rewarded, including providing certain services. The filing lists search engines, chatbots, applications or websites, offering users access for free to paid contents (e.g. video and audio streaming or electric books), or sharing information or data with users.

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