AttnGAN Neural Network to Draw Strange Pictures

The neural network is good at drawing birds by the text description, but bad everything else
20 August 2018   2789

The author of the AI Weirdness blog Janelle Shane had discovered the generative-controversial neural network called AttnGAN, which is trained to draw images on the text description. The problem is that it requires too accurately defined picture parameters and sometimes can not determine the boundaries of objects.

Janelle notes that, while the neural network was trained on a narrow set of data in the form of birds, it obtained nice images:

AttnGAN
AttnGAN

However, when the creators trained it on a dataset that included pictures from sheep to shopping centers, it could not create a meaningful image in a similar way. The author of AI Weirdness believes that the error lies in too wide a set of initial data, in which AttnGAN could not select the appropriate instances:

AttnGAN
AttnGAN

In addition, it somehow has a problem with determining the correct number of holes on the human face. Developers AttnGAN added to the control dataset person celebrities to create photorealistic portraits, but the neural network couldn't do that:

AttnGAN
AttnGAN

Additionally, neural network is real bad at displaying animals:

AttnGAN
AttnGAN

Janelle Shane calls the project AttnGAN "Visual Chatbot on the contrary." This chat bot analyzes the image that the user sends and describes it, often implausibly.

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   477

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.