MIT to Create Plant Cyborg

Elowan the robot with the plant drives to the light source necessary for photosynthesis
06 December 2018   1492

Specialists at the Massachusetts Institute of Technology (MIT) have developed the Elowan robot, which is in a kind of symbiosis with the plant. A living organism uses electrical signals to control the movement of the robot.

So far, the system only responds to some changes, such as lighting a plant or a lack of water. Silver electrods are used to transmit signals, which are implanted in the leaves, roots and stem of the plant. The direction of movement of the robot depends on the strength of the impulse. For example, in one of the experiments, the robot on which the pot with the plant stood, itself drove up to the light source necessary for photosynthesis.

The algorithm looks like this: the plant needs light, this causes certain biochemical changes that generate an electrical impulse. The robot captures it, decrypts and executes the desired command.

In the future, such systems may be useful for automatic farms, where robots themselves will take care of plants, responding to their needs for light, water or nutrients. Such technologies will be used in agriculture on Earth, as well as in distant space expeditions, where it will be necessary to grow plants on board a ship.

BNC to Monitor BTC Community's Mood

The system called Twitter Sentiment analyzes over 34M BTC-related Twitter posts each week, using AI to track the mood of the community
22 January 2020   470

Blockchain-based New Zealand-based research firm Brave New Coin (BNC) has unveiled a new system for measuring the mood of the Bitcoin community based on Twitter messages.

According to BNC, the new Twitter Sentiment rating system analyzes over 34 million BTC-related Twitter posts each week. The company uses artificial intelligence (AI) algorithms that look for records containing the words bitcoin, $ BTC and BTC and others.

BNC notes that user sentiment continues to be a “significant” factor in the price and dynamics of digital assets, and a new technique has been developed to track these sentiments. According to the BNC, it took 18 months to launch the Bitcoin Twitter Sentiment. The data obtained is divided into seven categories - Opinion, Technical Information, Inside the Network, Advertising, Bots, Macros and Hacking.

For the week ending January 17, the most common entries were in the Opinion category - their number was 30.42% of all data received. In second place was the category Technical Information, and in third inside the network (includes information on mining and hashrate).

BNC spokeswoman Pierre Ansaldi said that during the first quarter of this year, the company will also launch community sentiment analysis tools for other crypto assets.