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This website is powered by the question of how thinking works.

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Information and Interpretation

How is data assigned a meaning? What does information consist of? The answer seems clear, as the bit is generally regarded as its building block.

• But how do bits get their meaning?

Entropy is the quantity by which information appears in physics – thanks to C. E. Shannon, the inventor of the bit. Bits measure entropy and are regarded as the measure of information. But what is entropy and what does it really have to do with information?

• Entropy and Information

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Artificial Intelligence (AI)

Today there is a lot of talk about AI. I have been creating such systems for forty years – but without labelling them with this publicity term.

• The big difference: corpus-based and rule-based AI
• How real is the probable?
• Which requires more intelligence: jassen (a popular Swiss card game) or chess?
• What distinguishes biological intelligence from machine intelligence?

What today is called AI are always neural networks. What is behind this technology? Neural networks are extremely successful – but are they intelligent?

-> Can machines be intelligent? 

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Logic

Mathematical logic, to many, appears to be the ultimate in rationality and logic. I share the respect for the extraordinary achievements of the giants on whose shoulders we stand. However, we can also think beyond this:

• Are statements always either true or false?
• Can classical logic with its monotonicity really be used in practice?
• How can time be incorporated into logic?
• Can we approach logical contradictions in a logically correct way?

Aristotle’s classical syllogisms still influence our view of the world today. This is because they gave rise to the ‘first order logic’ of mathematics, which is generally regarded as THE classical logic. Is there a formal way out of this restrictive and static logic, which has a lot to do with our static view of the world?

-> Logic: From statics to dynamics

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Semantics and NLP (Natural Language Processing)

Our natural language is simply ingenious and helps us to communicate abstract ideas. Without language, humanity’s success on our planet would not have been possible.

• No wonder, then, that the science that seeks to explain this key to human success is considered particularly worthwhile. In the past, researchers believed that by analysing language and its grammar they could formally grasp the thoughts conveyed by it, which is still taught in some linguistics departments today. In practice, however, the technology ‘Large Language Model’ (LLM) of Google’s has shattered this claim.

As a third option, I argue in favour of a genuinely semantic approach that avoids the gaps in both the grammar and the LLMs. We will deal with the following:

• Word and meaning
• Semantic architectures
• Concept molecules

-> Semantics and Natural Language Processing (NLP)

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Scales: Music and Maths

A completely different topic, which also has to do with information and the order in nature, is the theory of harmony. Rock and hits are based on a simple theory of harmony, jazz and classical music on complex ones. But why do these information systems work? Not only can these questions be answered today, the answers also provide clues to the interplay between the forces of nature.

• Why do all scales span an octave?
• The overtone series is not a scale!
• Standing waves and resonance
• Prime numbers and scales

-> How musical scales evolved

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The author

My name is Hans Rudolf Straub. Information about my person can be found here.

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Books

On the topics of computational linguistics, philosophy of information, NLP and concept molecules:

The Interpretive System, H.R. Straub, ZIM-Verlag, 2020 (English version)
– More about the book

Das interpretierende System, H.R. Straub, ZIM-Verlag, 2001 (German version)
– More about the book

On the subject of artificial intelligence:

Wie die künstliche Intelligenz zur Intelligenz kommt, H.R. Straub, ZIM-Verlag, 2021 (Only available in German)
– More about the book
– Ordering the book from the publisher

You can order a newsletter here.

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Thank You

Many people have helped me to develop these topics. Wolfram Fischer introduced me to the secrets of Unix, C++ and SQL and gave me the opportunity to build my first semantic interpretation programme. Norbert Frei and his team of computer scientists actively helped to realise the concept molecules. Without Hugo Mosimann and Maurus Duelli, Semfinder would neither have been founded nor would it have been successful. The same applies to Christine Kolodzig and Matthias Kirste, who promoted and supported Semfinder in Germany. Csaba Perger and Annette Ulrich were Semfinder’s first employees, full of commitment and clever ideas and – as knowledge engineers – provided the core for the emerging knowledge base.

Wolfram Fischer actively helped me with the programming of this website. Most of the translations into English were done by Vivien Blandford and Tony Häfliger, as well as Juan Utzinger.

Thank you sincerely!