Cooking a dish by following instructions using Human Level Artificial Intelligence

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This video shows a robot cooking Chinese clam dish by following instructions from a webpage. There are no sound in the video because I wanted to show the viewers what the robot is thinking while making the dish. The flashing text and freeze frames are the internal thoughts of the robot and not instruction text for the viewers. These internal thoughts describe the details of how the robot produce intelligence.

The robot learns to cook meals by reading instructions in books or observing demonstrations. This is how human beings learn to cook. We all know that humans can work in any restaurant, like: Mcdonalds, Pizza hut, Chinese restaurants, Mexican restaurants, French restaurants and so forth. And the majority of knowledge comes from reading cook books or observing demonstrations.

When reading a cooking recipe, the robot is using human intelligence to organize data. He uses logic, common sense, and organization skills to identify the ingredients, linear cooking steps, map out important information from the webpage (this makes searching for data in the webpage easier), grouping tasks together, establishing association between task and rules (for example, establishing relations from cooking steps to ingredients needed for each step), ignoring information not related to cooking clams, and filtering out long or useless data from webpage.

By the way, a webpage is like a page from a cook book.

After reading the recipe instructions 1 or 2 times, the robot should have all the information it needs to cook Chinese clams. He will know the linear cooking steps (a general outline of the steps and a detailed outline of the steps), know the ingredients needed to make the dish, and know how to organize the instructions so that he won't run into trouble during the cooking phase.

Occasionally the robot will forget things (like what is step4 or what are the ingredients needed for preparing the sauce), however, he can re-look at the webpage and find the answers. Because the instructions to cooking Chinese clams are so long and the ingredients is long, the robot will occasionally forget steps. The robot uses logic to search for forgotten information from the webpage.

Practice making the same dish 2-3 times will allow the robot to have permanent knowledge about cooking Chinese clam dish. In the second try, the robot still might occasionally look at instructions in cook books/webpages, but after the 3rd try, the robot knows how to make Chinese clam dish using knowledge from its brain. It can recall all ingredients and linear steps from memory, instead of looking that information up in cook books. Remember, the robot's brain stores pathways in memory. These pathways record instructions from cook books, as well as, the robot's 5 senses of making the Chinese clam dish.

This method of learning to cook meals by reading cook books can be used to learn to cook "any" meal. If the robot doesn't know how to cook a lobster dish, he can read the instructions in a book or watch someone do a demonstration. If the robot doesn't know how to make pizza, he can read the instructions in a book or watch someone do a demonstration. If the robot doesn't know how to make clam chowder, he can read the instructions in a book or watch someone do a demonstration. The robot can learn to cook any meal by reading cook books.

This is very important because if you want to build a robot to cook in a French restaurant or a Chinese restaurant, this type of learning must be used. The current AI methods used to teach robots to cook are useless. Things like machine learning or programmers manually inserting knowledge, or common sense systems are completely useless. The reason that no one today has built a robot that can work in a restaurant is strong proof that current AI methods do not work (2013).

By the way, the method to learn to cook can be used to learn complex subject matters, like computer science, or physics, or chemistry. When reading technical books, the robot has to organize information, identify important data, filter bad data, establish relations between diagrams and text, identify a process, identify linear steps, generate a rule system, reinterpreting vague information, summarizing text, and so forth, are used to learn complex subject matters. In computer science, a neural network has many parts and has many processes. The robot has to use intelligence to understand a neural network from all aspects. Also, the job of the robot's brain is to organize this data and store said data in optimal areas in memory so that the search functions can find information fast.