tanzle.ai — Foundational Insights

Tanzle’s leadership team has a long track record of developing new computing paradigms.  That experience led to a key insight --- there are two distinctly different data categories, natural language (narrative) and natural phenomena (real-world).

Today’s popular AI is LLM based, which is designed specifically for narrative data (linear & symbolic). By contrast, no AI has been developed specifically for real-world data (dynamic, emergent, multi-dimensional & deterministic). These data categories and AI approaches are fundamentally opposites.

This revealed a massive, unmet need for an AI that unifies and operates on real-world data. The following cumulative insights led to this conclusion and further illuminate its implications.

1. The internet unifies vast amounts of narrative data (not real-world data)
2. Narrative data is 16 - 45% not trustworthy (Is AI Eating Itself?)
3. Vast amounts of real-world data are locked up in silos (not unified)
4. When unified, in one AI environment, real-world data is of immense value to every person & use-case (releasing tremendous value)
5. By unifying real-world data people can monetize data they generate (digital asset market)
6. What people need from this AI is to sync their mental models with real-world data for taking intelligent actions (exemplified by Charlie Munger & Richard Feynman)
7. To develop this new AI required a new technical & business architecture, built from the ground up, for unifying real-world data (natural phenomena).

Tanzle.ai is a new class of AI (not LLM), which is science-based (US Genesis Mission) and a market for monetizing digital assets that enable intelligent actions for profitable sustainability by leveraging phones, drones, sensors and robots.

Tanzle.ai is foundationally the opposite of today's LLM hallucinogenic AI (Is AI Eating Itself?). While LLMs are useful for certain natural language tasks, they are poorly suited for characterizing real‑world systems that are dynamic, emergent, multi-dimensional & deterministic.

Tanzle.ai is purpose built for science- and knowledge-driven use cases. Rather than treating the real world as text, tanzle.ai is designed to characterize real-world data and natural phenomena directly by characterizing reality as a Dynamic Emergent Holarchy — an architecture informed by first principles from quantum mechanics, high‑energy physics and quantum biology.

This sharp distinction between natural language and natural phenomena is the core insight. Applying natural language‑based AI (LLMs) to real-world data (natural phenomena) is using the wrong computational approach for the problem: at best, it can produce surface‑level results, but it fundamentally constrains accuracy, scalability and insight. 

In tanzle.ai human intelligence is defined as how well a person syncs their mental models with reality. This syncing with reality enables people to take intelligent actions to enjoy profitable sustainability across all human endeavors.

Intelligent actions — The more people’s mental models are in sync with reality, the more intelligence they use when taking actions. Examples are the legendary Charlie Munger (made billions) and Nobel Prize winner Richard Feynman (major contributions to quantum physics), who attribute their incredible success to syncing their mental models with reality. This mental model syncing approach is applicable to all human endeavors.

Mental Models — They are the superstructure of human intelligence and are internal representations of external reality, as opposed to natural phenomena, which “just are,” with no human interpretation. These mental model internal representations are approximations of the real world and can be more or less in sync with reality.

Mental Costs — The mental energy and time costs for people to sync their mental models with reality are incredibly high and can be literally uncomfortable and even physically painful. To address these costs, tanzle.ai radically reduces high cognitive loads via new technological innovations built from the ground up. In contrast, LLMs have no such ability and suffer from:

• Cognitive Miserliness
• Cognitive Blindness (Inattentional Blindness)
• Confirmation Bias
• Dunning-Kruger Effect
• Cognitive Dissonance
• Sunk Cost Fallacy
• Information Overload
• Anticipated Regret
• Normalization of Deviance
• Lollapalooza Effect
• Normalcy bias
• Many More...

Action Communities are foundational in tanzle.ai. They are groups of people with varied backgrounds and expertise, bringing their passion, intelligence, creativity and leveraging financial resources to take action, achieving their purpose with meaningful, measurable, concrete results. Action Communities can form within or outside of organizations or government entities.

Unlike today's social media platforms, where posting is the main activity, tanzle.ai Action Communities are about taking intelligent actions to achieve measurable goals and become profit centers by scaling their activities within an organization or worldwide. This is accomplished by syncing the users' mental models with self-learning unified real-world data to collectively take action.

Action Communities can span across all verticals such as energy, manufacturing, finance, research, national security, policy and education. Specific use cases include mining, supply chain, wildfires, insurance, science, lifelines, ocean health and more.