Neural Network to be Used For Cooking Receipts

One of the best cooking receipt by an AI is to preheat the oven to 3500 ° C for 8 minutes
06 August 2018   2255

The creator of the AIweirdness blog decided to write a cookbook using a neural network. She used the framework from the GitHub resource and published the results.

Despite its early developments, Janelle Shane decided to literally start from scratch and used the possibilities of the textgenrnn framework, transforming them into recipes. The final data for learning the neural network looked like this:

  • framework: textgenrnn, long text mode;
  • memory: 40 characters (default);
  • Duration: about 15 hours with NVIDIA Tesla K80 graphics card (using Google Cloud);
  • temperature: 0,6.

The latest results were better than they were before. But, nevertheless, there are still absurd combinations of ingredients:

  • 1 long granules sugar;
  • 1 Spanish water;
  • 1 cup of cream cheese seeds.

And the names of recipes resemble computer-generated descriptions for products with AliExpress. More details can be found in the AIweirdness blog.

Initially, in order to teach AI to make culinary recipes, Janelle used 30,000 ready-made recipes, which she collected from various sources. However, this experience was not successful. Considering memory of only a few words in length without a certain selection concept, something extraordinary or simply unreal was obtained. For example:

  • 4.5 kg of broccoli dried in a clay pan;
  • half a pint of spicy pieces;
  • 42 cups of milk;
  • Preheat the oven to 3500 ° C for 8 minutes.

And these examples from the cooking tips perfectly illustrate the ineffectiveness of the original method:

  • mix honey, liquid water of the toes, salt and 3 tablespoons of olive oil;
  • throw a frying pan;
  • tear off part of the pan.

In June 2018 AI was taught to create memes. A month later, in July 2018, scientists attempted to improve the model for recognizing speech accents.

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.