Here is a summary of the work that has the title: How a computer can invent by itself (i.e. the Methods for developing inventions with the help of which three programmers can easily create a program using which a computer can invent many inventions by itself)
Let’s suppose that two such conditional propositions are written to the computer memory (and also other conditional propositions are written): 1) If: fire is placed under the stone, then: the stone will heat up. 2) If: the stone will heat up, then: the stone will expand. Words of conditional proposition which stand from (i.e. after) the word «if» and before the word «then» are called the basis of conditional proposition, and words of conditional proposition that stand after the word «then» are called the consequence of conditional proposition. Let’s suppose that computer should solve the following inventive task, i.e. the computer has to determine what needs to be done to have the following: the stone will expand (i.e. the computer has to determine how the following can be obtained: the stone will expand), let’s call this task the original inventive task (let’s assume that this task has not been solved yet). From the second conditional proposition it follows that in order for the computer to solve the original inventive task it is necessary for the computer to solve the following inventive task, i.e. it is necessary for the computer to determine what needs to be done to obtain the following: the stone will heat up (i.e. it is necessary for the computer to determine how the following can be obtained: the stone will be heated); let’s call this task the second inventive task. And (from the first conditional proposition it follows that) in order for the computer to solve the second inventive task, it is necessary for it to solve the following inventive task, i.e. it is necessary for the computer to determine what needs to be done to have the following: fire will be placed under a stone (let's call this problem the third inventive task). ))And the third inventive task has been solved, because it is known how to get the following: fire will be placed under a stone. And if the third inventive task has been solved, then the second inventive task has been solved too. And if the second inventive task has been solved, then the original inventive task has been solved too. The Rule: Let’s take any inventive task (let's call this inventive task the fourth inventive task). In order for a computer to create an inventive task, having solved which it thereby solved the fourth inventive task, it is necessary for the computer to find in its own memory such a conditional proposition that has the following feature: the consequence of this conditional proposition and description of this fourth inventive task have the same meanings or consist of the same words which are located in the same sequence. And the basis of this conditional proposition will be an inventive task, having solved which the computer thereby solves the fourth inventive task. They have the same meanings: a) the word and interpretation of this the word b) synonyms and so on. Computer can find the same words in its memory. Let's take any inventive task (let's call this inventive task the fifth inventive task). The computer will solve the fifth inventive task if it does the following: first, using this rule, it will create such an inventive task (let’s call this task the sixth inventive task), having solved which it thereby solves the fifth inventive task, then, using this rule, the computer will create such an inventive task, having solved which it thereby solved the sixth inventive task, etc., (on average 90 times) to the moment at which (i.e. until) the computer creates such an inventive task the solution of which is known, and if the computer creates such (i.e. the latter) inventive task, then the computer will solve the fifth inventive task. That is, the computer will solved the fifth (i.e. any) inventive task if it creates on average 90 such tasks. Almost all currently known information (which is needed to create inventions) can be expressed in the form of conditional propositions. If, for example, 400 random physical effects in the form of conditional propositions are stored in the computer memory, then the computer can create on average a lot of inventions using this method (an average inventor knows 150 physical effects).
To Inkognito91I'm not sure that I understand your whole position on this, but what you have said in your first paragraph quoting Schumpeter (1945) is of course correct but the position taken by Schumpeter is that Monopolies are good. However, monopolies are good for the few that have them, - together with the licence to make money for the organization and its shareholders, - sometimes at the expense of society as a whole (the many). This is why many governments in the world (including the USA) have rules governing monopolies because they are bad for competition and thus ultimately for the consumer who cannot not benefit from lower prices and increasingly better products.Open Innovation increases the innovation activity thereby leading to better and more plentiful products for society as a whole, organizations stay ahead of the game through continuous innovation in an attempt to produce a Blue Ocean (Kim & Mauborgne, 2005) and take competitive advantage for shorter but successive periods of time. The old way which worked in the less Global marketplace of fifty years ago was to attempt to derive benefit from static and ultimately ageing products that were able to achieve massive economies of scale through the protection of patents until such time as it was either substituted by something superior or the patent ran out leaving the company without anything to replace it. In the Global marketplace there is little protection for products (no matter how good your lawyers are!) that are not continuously updated.
There is a problem tho. Schumpeter (1945) says that the monopoly of the innovation is its greatest rent. But in the extreme type of "open innovation", open source products (BSD licences for example),open innovation aalows an knowledge outflow, that decreases the potential endurance of the monopoly and therefor decreases the rents of the innovation. So basicly this video is just stating the basic innovation status and not the open innovation phenomenon. In open innovation the key attribute is that not only the result of the innovation is shared (e.g. more efficient cars) but also the explicit way how to get to the results (e.g. the construction plan of these cars).
Open Innovation can be very beneficial to draw on lots of outside expertise that may not exist in a company. Utilizing these extra resources can help develop ideas that may never have been brought to fruition. A nice video which breaks down the concept in simple to understand terms.
I agree but open innovation in "shallow" meaning is to release ideas. The movie didn't also explain types of open innovation. Inside-out (release "ideas") and outside-in (use someones "ideas"). To fully understand open innovation You need to dig in the mechanisms of creating value for our company that is due to licensing the solution that we give to the market. It can also take form of shared cooperation with other companies, create spin-off or even joint-ventures. Its not only "taking from our trash and throwing outside". OpenSoruce is different issue tho. It is not limited by business model (like in open innovation companies) (like H. Chesrbough said).
Here is a summary of the work that has the title: How a computer can invent by itself (i.e. the Methods for developing inventions with the help of which three programmers can easily create a program using which a computer can invent many inventions by itself)
Let’s suppose that two such conditional propositions are written to the computer memory (and also other conditional propositions are written):
1) If: fire is placed under the stone, then: the stone will heat up.
2) If: the stone will heat up, then: the stone will expand.
Words of conditional proposition which stand from (i.e. after) the word «if» and before the word «then» are called the basis of conditional proposition, and words of conditional proposition that stand after the word «then» are called the consequence of conditional proposition.
Let’s suppose that computer should solve the following inventive task, i.e. the computer has to determine what needs to be done to have the following: the stone will expand (i.e. the computer has to determine how the following can be obtained: the stone will expand), let’s call this task the original inventive task (let’s assume that this task has not been solved yet). From the second conditional proposition it follows that in order for the computer to solve the original inventive task it is necessary for the computer to solve the following inventive task, i.e. it is necessary for the computer to determine what needs to be done to obtain the following: the stone will heat up (i.e. it is necessary for the computer to determine how the following can be obtained: the stone will be heated); let’s call this task the second inventive task. And (from the first conditional proposition it follows that) in order for the computer to solve the second inventive task, it is necessary for it to solve the following inventive task, i.e. it is necessary for the computer to determine what needs to be done to have the following: fire will be placed under a stone (let's call this problem the third inventive task). ))And the third inventive task has been solved, because it is known how to get the following: fire will be placed under a stone. And if the third inventive task has been solved, then the second inventive task has been solved too. And if the second inventive task has been solved, then the original inventive task has been solved too.
The Rule: Let’s take any inventive task (let's call this inventive task the fourth inventive task). In order for a computer to create an inventive task, having solved which it thereby solved the fourth inventive task, it is necessary for the computer to find in its own memory such a conditional proposition that has the following feature: the consequence of this conditional proposition and description of this fourth inventive task have the same meanings or consist of the same words which are located in the same sequence. And the basis of this conditional proposition will be an inventive task, having solved which the computer thereby solves the fourth inventive task. They have the same meanings: a) the word and interpretation of this the word b) synonyms and so on.
Computer can find the same words in its memory. Let's take any inventive task (let's call this inventive task the fifth inventive task). The computer will solve the fifth inventive task if it does the following: first, using this rule, it will create such an inventive task (let’s call this task the sixth inventive task), having solved which it thereby solves the fifth inventive task, then, using this rule, the computer will create such an inventive task, having solved which it thereby solved the sixth inventive task, etc., (on average 90 times) to the moment at which (i.e. until) the computer creates such an inventive task the solution of which is known, and if the computer creates such (i.e. the latter) inventive task, then the computer will solve the fifth inventive task. That is, the computer will solved the fifth (i.e. any) inventive task if it creates on average 90 such tasks.
Almost all currently known information (which is needed to create inventions) can be expressed in the form of conditional propositions. If, for example, 400 random physical effects in the form of conditional propositions are stored in the computer memory, then the computer can create on average a lot of inventions using this method (an average inventor knows 150 physical effects).
only 67 suscribers? i changed that now to 68. You are great, thank you
I don't understand :(
To Inkognito91I'm not sure that I understand your whole position on this, but what you have said in your first paragraph quoting Schumpeter (1945) is of course correct but the position taken by Schumpeter is that Monopolies are good. However, monopolies are good for the few that have them, - together with the licence to make money for the organization and its shareholders, - sometimes at the expense of society as a whole (the many). This is why many governments in the world (including the USA) have rules governing monopolies because they are bad for competition and thus ultimately for the consumer who cannot not benefit from lower prices and increasingly better products.Open Innovation increases the innovation activity thereby leading to better and more plentiful products for society as a whole, organizations stay ahead of the game through continuous innovation in an attempt to produce a Blue Ocean (Kim & Mauborgne, 2005) and take competitive advantage for shorter but successive periods of time. The old way which worked in the less Global marketplace of fifty years ago was to attempt to derive benefit from static and ultimately ageing products that were able to achieve massive economies of scale through the protection of patents until such time as it was either substituted by something superior or the patent ran out leaving the company without anything to replace it. In the Global marketplace there is little protection for products (no matter how good your lawyers are!) that are not continuously updated.
THANK YOOOOU, finally I understood
Subtitles, please!
There is a problem tho. Schumpeter (1945) says that the monopoly of the innovation is its greatest rent. But in the extreme type of "open innovation", open source products (BSD licences for example),open innovation aalows an knowledge outflow, that decreases the potential endurance of the monopoly and therefor decreases the rents of the innovation.
So basicly this video is just stating the basic innovation status and not the open innovation phenomenon. In open innovation the key attribute is that not only the result of the innovation is shared (e.g. more efficient cars) but also the explicit way how to get to the results (e.g. the construction plan of these cars).
Open Innovation can be very beneficial to draw on lots of outside expertise that may not exist in a company. Utilizing these extra resources can help develop ideas that may never have been brought to fruition. A nice video which breaks down the concept in simple to understand terms.
I agree but open innovation in "shallow" meaning is to release ideas. The movie didn't also explain types of open innovation. Inside-out (release "ideas") and outside-in (use someones "ideas"). To fully understand open innovation You need to dig in the mechanisms of creating value for our company that is due to licensing the solution that we give to the market. It can also take form of shared cooperation with other companies, create spin-off or even joint-ventures. Its not only "taking from our trash and throwing outside". OpenSoruce is different issue tho. It is not limited by business model (like in open innovation companies) (like H. Chesrbough said).