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Why is it so difficult to develop a general-purpose AI?

Assumptions and constraints

What means linear?

The requirement for a linear function is the existence of space,
which enables us a movement of an object in a direction,
where each step has the same length as all the other steps,
like walking along a path, which is smooth, without any holes.

Is this important? Yes it is, because our path is always there,
without any disturbances, as the physical space does not change.
This implies that every object has the same length at every given moment,
which enables us to quantify the space in different units of measurement.

Math has a lot of advantages in our everyday life, wherever we go,
not to mention the fact that during the last 400 years, math has evolved,
containing more than 3000 applications areas, even enabling us to go to the moon.
There are lots of mathematical functions, but all are based on the physical space.

What means non-linear?

In order to understand the non-linear concept, let us have an example:
The clouds in the sky, where our space is the cloud itself, he he.
As the cloud has sometimes a temporary connection to other clouds,
in other times there is no connection between them, not at all.

How do you measure an object inside the cloud, which represents in our case the space itself?
The answer is unambiguous, namely we can NOT do this, as the size of each individual cloud
inevitably changes in time, sometimes even connecting with other clouds, forming big clouds,
while sometimes the clouds even suddenly disappear and new clouds are forming out of nowhere.

Therefore we can NOT use the cloud as a linear space, because it changes all the time.
This is the reason why, the usual mathematical functions do not apply for this case.
The same functionality we can recognize while observing neuronal activity in the brain.
We urgently need another toolset, in order to explain and use non-linear behaviour.


There are several impediments, which actually block the creation of an AI.

The academic world
1. Each individual has usually only one domain of activity, means specialty, but AI requires quite a few
2. The dominant tool used in research is experiments, but not on microscopic living brain tissue
3. The expected result for drawing conclusions is always a mathematical formula, for AI this is irrelevant
4. Until today, there is no viable explanation for neuron and neural nets, as their function is non-linear

Math is the greatest obstacle for AI
1. Math is based on something we can measure, using certain units of measurement
2. Measurement implies everything is linear, same like moving along a smooth line, without any obstacles
3. Math implies every object we measure is the same, no regards to its structure, while all objects are considered lifeless
4. Intelligence is a living brain tissue, neurons act non-linear, means no acting along a line and no unit of measurement

The research institutes
1. A research institute is an agency funded by certain investors, which are looking to solve own issues
2. They gather different problems from various sources, e.g. academic, industry, finance, social, etc.
3. The write down the list as open points and ask for individual new solutions for each of the items
4. The budget for this list is then squeezed within their annual financial possibilities

The industry
1. IF AI is an airplane, most people want to use it as a passenger, but designing an airplane is difficult
2. Companies want to use AI as a commodity, same like keeping human slaves with intelligence, they can control
3. As AI is NOT math, no math formula can explain it, as intelligence requires a living organism
4. But without math, companies have great difficulties in developing and offering a commercial product

Explaining AI
1. Today, most companies use the term AI, even if in fact they are using statistics to create large databases
2. AI means Artificial Intelligence, but until today, there is no definition for what intelligence even is
3. People mix up their own free will with intelligence, as we assume our will is more important than intelligence
4. In our everyday life, we have no respect for human intelligence, as we hire and fire intelligent people

The importance of AI
1. The importance of developing and using a real general-purpose AI is comparable with the Manhattan project
2. In contradiction with a weapon, which is kept only for doomsday scenarios, AI can be used in everyday life
3. The very existence of an AI will change our world forever, as our understanding of the world will evolve
4. The results of understanding AI, will boost many scientific areas, like medicine, biology, pedagogy, etc.

Conclusion
AI is difficult, complex and needs deep interdisciplinary knowledge from many known sciences,
as math is no help at all, it requires another way of thinking, extending the common linear rules,
First understand the basic principles and develop a corresponding theory about human intelligence,
then creating a new technology, from inception via prototype to production, overcoming many social hurdles.

Tipalo general-purpose AI
1. Tipalo publishes the basic principle of our biological approach, as the brain is the only intelligence we know nowadays
2. We prove our theory of adaptive biological brains, with self-programmable neural nets using an own self-learning mechanism
3. We are creating a proof of concept, which is a hardware operating system for simulating brain tissue in FPGA-SiP and 3DSOC
4. Then we design an AI prototype, which will implement an Artificial Nervous System with different brain regions for a body hardware