AI to Design Halloween Costumes

Artificial intelligence can be really spooky in the eve of Helloween
29 October 2018   1347

Janelle Shane spoke about experimenting with AI on the eve of Halloween. The neural network was trained with a database with the names of costumes and it learned how to create its own. Janelle was able to do this with The New York Times: Editor Jessia Ma illustrated the results.

Last year, readers of the blog AIweirdness helped Janel to collect a base of 4.5 thousand names of suits. In 2018, she used the textgenrnn neural network and collected 7,100 samples using the New York Times publication (sent by people during the year). At the first stage, the algorithm created the word and compared it with examples from the database. In the event of a mismatch, the neural network changed the structure of the selection of letters. With each stage of the development of AI (they were called "epochs"), the generated costumes became more real to be realized.

In the first epoch, the costumes “Watand Hampir”, “Deadly Zanzai Vom” met. In the third, it was already “Greek beer” and “Darot Vader”. By the fifth stage, the AI ​​generated a “must-have minivan”, “Princess Laya”. At the seventh stage, a “giant box” and a “cyborg baby man” met. By the ninth, a “chewing cow” and a “wild Thor-pirate” appeared. And at the eleventh stage, the neural network created already full-fledged costumes, like the “death eater” or “witch hat”.

With the growing popularity of machine learning, the complexity of tasks grows and the scope of AI is expanding. At the end of October 2018, Honda, SoundHound, and three universities — Washington, Pennsylvania, and MIT — began to develop the Curious Minded Machine, an artificial, self-learning intelligence. Scientists expect the system to understand the actions of a person and offer him more effective ways to achieve goals.

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   188

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.