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   1635

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.

AI to Recognize Text Written by Invisible Keyboard

Developers said they tried to increase the typing speed on the on-screen keyboards
06 August 2019   152

Korean developers have created an algorithm that recognizes text printed on an imaginary keyboard on a touchscreen. Such a “keyboard” is not tied to a specific area on the screen, and the “keys” are not limited to clear squares.

As a result, a person types blindly in a QWERTY layout without thinking about where the keyboard should be and whether it got into the key.

Imaginary Buttons Press CloudsImaginary Buttons Press Clouds

According to the developers, they tried to increase the typing speed on the on-screen keyboards. The on-screen keyboard, unlike the hardware keyboard, does not offer feedback that confirms pressing. There is a risk to miss and not press the desired button. Because of this, people endlessly stare at the screen and eventually print more slowly.

The new algorithm allows you not to worry about this, you can enter text from memory, and the keyboard with 96% accuracy will guess what the person wanted to say. Tests have shown that the average typing speed on an imaginary keyboard is slightly less than on a hardware keyboard: 45 words per minute versus 51.