Essay

Descartes’s division of mind and matter has shaped our contemporary world order since the 17^th century. But that order is now questioned amid a new technological revolution, largely driven by AI.

Truth is increasingly defined by the top result of Google search while a growing percentage of human activity is driven by AI-algorithms. But these algorithms do not explain the underlying reality that produces them.

Some philosophers describe truth not as a relationship outside of the human mind that we can align belief to, but they see it as a product of belief.

Adding causality and common-sense to the equation, AI has no chance to terminate truth.

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The concept of ‘Digital Twins’ has emerged as a promising technology to enhance current AI-Applications.

The implementation of a digital twin is represented  by an assembly of software that mirrors the structure of a unique physical object, a process, an organization or an individual.

Adding the 3-D space provided by the metaverse and its  augmented and virtual reality tools, digital twins provide new insights for solving problems at the corporate as well as the individual level.

Getting there will take time. With advancements in hardware performance and data analytics, a ten-year timeframe seems realistic.

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The computational model, comparing the brain to the computer, has been the most prominent metaphor in neuroscience and AI for decades. It implies that computers are very closely aligned to the functionality of the human brain.

A new theory of how the brain works — the neural transduction theory — might upend everything we know about consciousness and the universe itself. According to this theory our bodies are completely encased by transducers.

The arguments to advance AI-research from a computer to a transducer metaphor are intriguing, especially in respect to causality. Our capacity to adapt will remain the limiting factor unless the quest for survival opens a new chapter in human evolution.

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Animals and humans exhibit learning abilities and understandings of the world that are far beyond the capabilities of current AI and machine learning (ML) systems.

How is it possible for an adolescent to learn to drive a car in about 20 hours of practice and for children to learn language with what amounts to a small exposure.

For many years now Artificial General Intelligence (AGI) has been the holy grail of AI-research Since years with little or no progress for overcoming problems related to causality. Based on a new approach of self-learning systems, with curiosity and common sense as driver, we might finally achieve an AI that serves humans as opposed to humans serving AI-machines.

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The Metaverse, proposed by Meta (formerly Facebook), is still under construction – its main building block is AI. Microsoft, as competitor, positions the Metaverse as a ‘digital space inhabited by digital representations of people and things.’

To some critics the Metaverse looks alarmingly like productivity software kitted out with VR glitter. The real threat comes from Zuckerberg’s ‘Suckerverse’.

The lack of experiencing so called ‘embodiment’ defines one of the limits of the Metaverse and its often-overhyped expectations.

It is difficult to predict where the Metaverse will be in five years and if we are indeed witnessing a paradigm shift towards the next industrial revolution.

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Perception is not supposed to be an accurate representation of sensory information. Rather, it is supposed to be an interpretation.

The mental experience of perceiving is filtered by our senses before our biological neurons and its synaptic connections within the brain will react. An illusion is a distortion of the senses and an indicator as to how the mind normally organizes and interprets sensory stimulation.

Higher level decisions require a broad understanding of issues which go beyond the capacity of current AI-technologies. Hence, human judgement and sound assessment of technological progress are likely to remain the key to successful decision-making for a long time to come.

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Biological cells generated from stem cells, can be used to provide the computational functionality of real neurons, providing so-called ‘wetware’ of living cells.

Due to limitations of processing power and energy consumption of silicon-based computers, wetware- based cell-computing is likely to bring about a paradigm-shift in machine learning technology.

Supported by Venture Capital, Start-Ups are driving the market with a vision, that within a few years, 10 billion neurons on a chip might be capable of processing our entire knowledge space.

Answering the many related ethical issues is complex. We are confronted with a radically new phenomenon of science which humanity has not been exposed to.

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Although there are many more forms of art, literature and music are especially well suited to discuss the application of AI as both can be digitally produced and distributed (Books, CDs, Video-Streaming).

Literature is the art-form of language and words are its tools while Music is the art-form concerned with combining vocal or instrumental sounds.

While AI provides tools, there are limits how far they can support the process of composing art. The fact that mathematics represents an intrinsic part of music and the same holds true for AI as well, demonstrates that integrating the disciplines of natural sciences and the humanities presents a potential path towards a new form of man/machine interaction, with creativity representing human’s most valuable contribution.

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