BETA
Formal net
Brian learns about the world with its controlled ...
Includes only formulated ideas, i.e. Questions, Hypotheses, Predictions, and Observations
Observation
Brian learns about the world with its controlled hallucination process
The controlled hallucination process is also a hypotheses-prediction-observation correction learning process. Brains can learn brand new concepts by generating new hypotheses about the world, making predictions about the sensory input, and correcting according to observation (actual sensory input)
Supports
The hypothetico-deductive method is ubiquitous at different levels of human learning
From unconscious learning in brian to individual scientific inquiries to collective scientific inquiries.
87.8%
Generalizes to
AI can achieve human-level intelligence through self-supervised learning alone.
Because this self-supervised learning process mimics the brain's learning mechanism: make predictions and learn from prediction errors.
50.0%
Infers
LLM / Foundation models can provide the structural foundation for AGI as language provides for human ...(14 more characters.)
No Content
27.3%
AGI
Predicts
Advances in AI R&D will bring another tech revolution same scale as the internet.
Major disruptions in businesses will start to appear around 2024 - i.e. profitable (by free cash flow) and hyper-growth companies relying on large-scale neural networks as their main tech strength.
64.0%
2025-10-26
2024-06-26
Business & Industrial AI p/Investing
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Predicts
LLM will be instrumental in achieving at least one human-level AI task beyond NLP in 3 years
GitHub copilot is promising, but it's not human-level yet. It might be possible for Self-driving to use LLMs as foundations to build models that can predict the social behavior of humans on the street.
98.4%
2025-10-27
p/investing
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Generalizes to
Hypothesis-prediction testing is a fundamental learning mechanism
No Content
89.8%
Infers
Formulating inquiry thoughts into observations, hypotheses, and predictions enables learning.
Thanks to the intrinsic set of fixed relationships between them, this formalization provides a helpful structure to our inquiry. It enables the learning cycle of observations -> hypotheses -> predictions -> correct with observations. This can be argued for [philosophically](https://www.themind.net/hypotheses/W2wRBi5mSeGueEYevUjMzw) and [neuroscientifically](https://www.themind.net/hypotheses/M4p8C9lOTRu8ipf5zGtEJA).
76.3%
the mind net
Infers
Digitalized minds
A system can be created to let users record their inquiry thoughts/ideas as observations, hypotheses, and predictions (OH&P). Thanks to the intrinsic structure, the system can digitalize these thoughts/ideas with auto connections and visualization, thus providing an automatic way to organize these thoughts/ideas. We can call this digitalized mind. The digitalized mind makes thoughts/ideas easier to consume, assess and generate new insights.
66.7%
The mind net p/The Mind Net
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