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1. The current approach to AI and NLP – and how it fails

In the years before the first flight of the Wright brothers, aviation wasn't scientific yet, because the attempts were “inspired by nature”, using feathers, flapping wings, bird suits, and so on:
• YouTube: “Man's Early Flight Attempts”;
• YouTube: “first attempts to fly by man”;
• YouTube: “Death Jump - Franz Reichelt jumps off the Eiffel Tower”.

However, the Wright brothers understood: A machine will only be able to fly if it is based on the laws of nature, obeying the Laws of Physics. So, apparently, using the laws of nature is a fundamental approach, whilst being “inspired by nature” isn't.

This situation is illustrative for the current state of AI and NLP:
• This field is lacking a unifying, fundamental (=natural) and deterministic (=implementable) definition of intelligence, and the understanding how natural intelligence and natural language are related;
• Without natural definition, this field is lacking a natural foundation;
• Without foundation, the techniques developed on AI and NLP are in fact baseless. And without one common (=natural) foundation, its disciplines – like automated reasoning and natural language – can not be integrated;
• Being baseless, AI got stuck at a simulation of behavior, and NLP got stuck at keyword level.

Even 60 years after the start of this field, 160 years after the publication of “The Laws of Thought” by George Boole, and 2,400 years after Aristotle's works on logic, scientists are still unable to convert a sentence like “Paul is a son of John” to “John has a son, called Paul” – and vice versa – in a generic way (=through an algorithm).

Both sentences have the same meaning. So, it must be possible to convert one sentence to the other – and vice versa – as explained in 1.5.2. Fundamental flaw in the Turing test. However, such a conversion requires to understand what natural intelligence is. Lacking a natural definition of intelligence, not a single scientific paper supports the mentioned conversion in a generic way (=through an algorithm).

Common knowledge:
• If problems are fundamental, one needs to repair the foundation. Actually, it is better to remove the old foundation, and to pour a new one;
• If two disciplines have different foundations, they can't be integrated, because a building can only have one foundation. If another foundation would be poured next to an existing one, both foundations will move relative to each other. Then the expanded building – resting on both foundations – will prolapse, and eventually collapse.

Only a fundamental approach – based on laws of nature – will deliver significant progress.