Microsoft AI to Win Greenhouse Competition

Five AI systems from different teams took part in cucumber growth competition
17 December 2018   1816

From August to December, five teams from technology companies and universities from different countries participated in the competition for growing cucumbers in autonomous greenhouses. Irrigation, fertilizing, temperature control and other factors were controlled by artificial intelligence. The best result was shown by the Sonoma team from Microsoft Research. In addition, it reached a yield of 50 kilograms of cucumbers per square meter.

The results of the participants were evaluated by three parameters:

  1. net profit (market value of the harvested crop minus water, energy, and labor) was 50% of the final estimate;
  2. the use of artificial intelligence (reliability of the algorithm, the effectiveness of its strategy) - 30%;
  3. system stability (water, carbon dioxide and energy per kilogram of cucumbers) - 20%.

The Microsoft Research team achieved the highest yield and net profit. The second place was taken by the team from Tencent - their algorithm showed the best strategy for the use of resources. Third place went to The Croperators team from Delphy and AgroEnergy.

The jury noted that the control group of agronomists, which grew cucumbers on their own, used less electricity than any of the teams with AI. At the same time, it lost only to the team from Microsoft in terms of net profit.

According to the founders, the purpose of the competition was not to start building autonomous greenhouses around the world. The organizers wanted to know at what stage of development artificial intelligence is and what is its advantage over people in the agrarian sphere.

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   464

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.