Neural Network to Write Picture-Based Poems

Microsoft had created XiaoIce chatbot that is the neural network poet
13 August 2018   1585

Microsoft has trained XiaoIce's artificial intelligence system to read the image and generate Chinese poems describing what is depicted on it. This is reported by The Next Web.

The system consists of two neural networks. One of them recognizes the details in the picture and selects keywords, and then generates a poem. The second part evaluates the total. The algorithm received a set of instructions from the researchers and worked until the best result was achieved. If it did not suit the researchers, they changed the instruction set and restarted the system.

For example, for such an image, the algorithm generates a poem:

Example Image for XiaoIce
Example Image for XiaoIce

Wings hold rocks and water lightly

in the loneliness

Stroll the empty

The land becomes soft

Xiaolce's Poem

According to scientists, modern Chinese poetry requires great imagination and creative use of language, which is a difficult task even for a person.

To determine the quality of the program, the researchers conducted experiments, where they offered people to choose between the poems of the Microsoft bot and other algorithms. In the overwhelming majority of participants chose the first option.

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   468

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.