The hottest Cognitive Science Substack posts right now

The Aaron Lee Master Framework integrates various logical systems to understand language dynamics, emphasizing the contextual nature of meaning.
Key components like Non-Monotonic Logic and Fuzzy Logic help in adjusting beliefs based on new information and dealing with gradations in meaning, respectively.
The Framework's philosophical and logical foundations aim to provide a comprehensive model for the complexities of language and semantics by elucidating the emergence of meaning through interactions and context.

Institutions shape how we behave by restricting certain actions. This can be seen in clear rules or by making other choices harder or more costly.
Information is created when different conditions allow an entity to do work, as shown in the example of a simple organism's behavior. The way it manages energy and information is crucial for survival.
Just like simple organisms, institutions also gather information from their environment and use it to influence our actions. The way they set up rules determines the kind of work they can do.

If a system acts intelligently, we should consider it intelligent. It's about how it behaves, not just how it works inside.
Many people don't really understand what intelligence is, which makes it hard to define. Historically, we've only seen humans perform certain tasks, but now AI is doing them too.
AI like ChatGPT has limitations and doesn't have the full abilities of human intelligence yet. While it's impressive, it can't think or learn in the same way humans do.

Stories can have four key characters: you, your opponents, the known, and the unknown. This helps create a clear strategy in any situation.
Using four characters can bring a sense of stability compared to just three. It's about finding balance and understanding different perspectives.
In both stories and computer science, the concept of four relates to structure and relationships. Recognizing these connections can deepen our understanding of both fields.

Focusing on too many tasks at once can lead to a lack of quality decisions. It's important to realize that deep focus is rare and valuable.
Not all decisions are equally important. Some choices can be made quickly and changed later, while others require careful thought before proceeding.
Using curated lists can help simplify decision-making. They reduce complexity and make it easier to choose among options without feeling overwhelmed.

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Small language models can now solve math problems better than bigger models. They use special techniques that help them think deeply and reason through math challenges.
Different methods for handling questions work better in different situations. Using longer context helps with certain types of questions, while other methods might be better for conversations.
To achieve human-like intelligence, AI needs to improve in key areas like memory and understanding symbols. Current AI shows promise but has a long way to go.

Our minds often make small problems feel much bigger than they really are. We can trick ourselves into thinking these issues are more serious than what's actually happening.
It's important to remember what we take for granted. Many people have it much harder, and recognizing our privilege can help shift our perspective.
Practicing mindfulness can help change how we think. Activities like journaling or meditation can help us see things more clearly and reduce unnecessary stress.

AI can struggle with memorization instead of understanding, similar to how students might remember specific math problems without grasping the general concept. When AI memorizes examples too closely, it can't apply knowledge to new situations.
Techniques like regularization help AI focus on important patterns rather than get lost in details. This is like training athletes under various conditions to build real skills instead of just practicing one way.
Understanding how to forget unimportant information is crucial for both AI and human intelligence. The best learning doesn't come from remembering everything, but from knowing which patterns are worth keeping.

AI influences decision-making by creating invisible networks of ideas. These conversations shape how leaders think without them even realizing it.
Like economic markets guided by supply and demand, AI conversations can connect different ideas and solutions across various fields, making them more efficient.
This new form of influence might not be recognized today, but it could have big impacts on future decisions and policies, as ideas evolve through these AI interactions.