The hottest Cognitive Science Substack posts right now

And their main takeaways
Category
Top Technology Topics

In search of the mystery of the cortical column and human-like general intelligence

Artificial General Ideas • 1 implied HN point • 25 Feb 26
🕹 Technology Cognitive Science
  1. Build NeuroAI by reverse-engineering general cortical principles so systems learn, think, and plan efficiently like humans and learn from experience rather than just from written human knowledge.
  2. Prioritize new kinds of world models that are hierarchical, causally structured, and compositional, and combine those with episodic memory, distributed reasoning across perception and action, active inference, and continual learning.
  3. Close the loop between AI and neuroscience by using brain observations—like recurrence, feedback, attention, replay, schemas, and local plasticity—to drive algorithm design and iterate with targeted experiments to refine theories.

The movie isn't alive

Sunday Letters • 39 implied HN points • 19 Feb 24
🕹 Technology Cognitive Science
  1. Humans often see faces in things that don't have them, which shows how our minds can trick us. This idea extends to chatbots, which can seem alive but are really just processing prompts without true understanding.
  2. Chatbots may appear to have memory or awareness in a conversation, but they actually rely on previous prompts without retaining any real continuity. This can make interactions feel more human-like, even though they lack true awareness.
  3. It's helpful to recognize that chatbots and similar technologies are more about creating illusions than actual intelligence. Understanding this can improve how we design and use them, rather than expecting them to behave independently like a living being.

AGI is Not Multimodal

The Gradient • 49 implied HN points • 04 Jun 25
🕹 Technology Cognitive Science
  1. Recent AI models have shown impressive capabilities, but they don't represent true human-like intelligence. They succeed because of scaled hardware and not because they think like us.
  2. Trying to combine different AI models into a single system won't lead to real understanding or human-level AI. This approach is flawed and unlikely to work.
  3. Instead of mixing models, we should focus on how AI interacts with the world and learns from it. Understanding AI should be about its actions and experiences in the environment.

In cautious defense of LLM-ology

The Counterfactual • 119 implied HN points • 02 Mar 23
🕹 Technology Cognitive Science
  1. Studying large language models (LLMs) can help us understand how they work and their limitations. It's important to know what goes on inside these 'black boxes' to use them effectively.
  2. Even though LLMs are man-made tools, they can reflect complex behaviors that are worth studying. Understanding these systems might reveal insights about language and cognition.
  3. Research on LLMs, known as LLM-ology, can provide valuable information about human mind processes. It helps us explore questions about language comprehension and cognitive abilities.

How much of our disbelief can we suspend in augmented reality?

On Looking • 59 implied HN points • 27 Jun 23
🕹 Technology Cognitive Science
  1. Technologies like augmented reality challenge our perception and reshape our senses, training us to suspend disbelief and engaging us in a new form of visual literacy.
  2. The labor of making things look real involves an intricate mix of technology, cultural references, and societal norms, often blurring the lines between what is real and what is constructed.
  3. The desire for connection in an increasingly technological world raises questions about the authenticity of human interactions and challenges us to navigate the fine line between presence and absence, between virtual and physical realms.
Get a weekly roundup of the best Substack posts, by hacker news affinity:

Building the science factory with LLMs

The Counterfactual • 39 implied HN points • 13 Dec 23
🔬 Science Cognitive Science
  1. Large Language Models (LLMs) could make scientific research faster and more efficient. They might help researchers come up with better hypotheses and analyze data more easily.
  2. Breaking down the research process into smaller parts might allow automation in areas like designing experiments and preparing stimuli. This could save time and improve the quality of research.
  3. While automating parts of scientific research can be helpful, it's important to ensure that human involvement remains, as fully automating the process could lead to lower-quality science.

Why we should look for the good reasons behind our behaviour

Optimally Irrational • 77 implied HN points • 12 Dec 24
📖 Philosophy Cognitive Science
  1. Understanding our behavior is important because it's not just random; it comes from a long history of survival and adaptation. We should look for reasons behind our choices instead of labeling them as irrational.
  2. Historically, research has focused a lot on cognitive biases, making it seem like humans are mostly flawed thinkers. Now, there's a shift towards recognizing our mental processes can also be adaptively efficient.
  3. Many behaviors that seem like mistakes may actually be smart solutions given the complex decisions we face. It's better to explore the reasons behind behaviors to find their potential usefulness.

Cognitive sovereignty

storyvoyager • 6 implied HN points • 01 Dec 25
🕹 Technology Cognitive Science
  1. Accessing knowledge on an external server isn’t the same as being intelligent; intelligence depends on internal processing, not just retrieval.
  2. Having 'taste' or good ideas requires storing and processing at least some knowledge inside the brain rather than outsourcing all judgment.
  3. The future will favor developing organic, brain-integrated semiconductors so people can maintain cognitive independence alongside AI.

The aim of maximising happiness is doomed to fail as a public policy

Optimally Irrational • 79 implied HN points • 27 Nov 24
📖 Philosophy Cognitive Science
  1. Aiming to make everyone happy through public policy might not work. Happiness is not a simple thing that can just be increased.
  2. People adapt to their situations quickly, which means that any increase in happiness usually fades back to a normal level. This makes it hard to keep happiness growing over time.
  3. Happiness is often more about feeling good in the moment than about long-term goals. People might even choose challenging paths because they bring deeper satisfaction, rather than just chasing fleeting feelings of joy.

When does AI have rights?

The Future of Life • 19 implied HN points • 29 Feb 24
🕹 Technology Cognitive Science
  1. AI might need rights if it mimics human behavior closely enough. We should think about this now before AI becomes super intelligent.
  2. Consciousness, sentience, and rights are important ideas, but they're not well-defined and can differ between people. Understanding these can help us decide who deserves rights.
  3. Sapience is being smart in a deep way, and it seems to be the best indicator for deciding if something deserves rights. It's more than just feeling or basic thinking.

mathiness instills confidence

bad cattitude • 165 implied HN points • 22 Feb 24
🔬 Science Cognitive Science
  1. Mathiness can make people feel more confident, especially if they aren't familiar with math.
  2. Adding complex math or 'mathiness' to information can influence how people perceive its quality, especially if they lack knowledge in math and models.
  3. It's important to be cautious of trusting information just because it includes numbers or complex equations; don't assume accuracy or rigor without verifying.

GPT-4 captures judgments about semantic relatedness quite well

The Counterfactual • 59 implied HN points • 18 May 23
🕹 Technology Cognitive Science
  1. GPT-4 is really good at understanding word similarities. In tests, it matched human opinions better than many expected.
  2. Sometimes GPT-4 thinks that certain words are more similar than people do. It tends to view pairs of words like 'wife' and 'husband' as more alike than humans generally agree on.
  3. Using GPT-4 for semantic questions could save time and money in research, but it's still important to include human input to avoid biases.

A review of "Don’t forget the boundary problem..."

Unstabler Ontology • 19 implied HN points • 08 Feb 24
🔬 Science Cognitive Science
  1. The article discusses the binding problem in consciousness theories, which is about combining different features into a unified awareness.
  2. Functionalism is challenged by the boundary problem, questioning why there are limits to our conscious experiences.
  3. Electromagnetic theories of consciousness are explored, considering the role of EM fields in demarcating conscious entities and potential solutions using field topology.

Intelligence and combinatorial complexity

Sunday Letters • 39 implied HN points • 27 Aug 23
🕹 Technology Cognitive Science
  1. More agents working together can create better intelligence than a single agent. This is surprising because we might think one advanced model is enough, but collaboration can enhance performance.
  2. Human-like patterns help improve AI performance. Just as we can review our work for errors, AI systems can use different modes to refine their outputs.
  3. Complex systems come with challenges like errors and biases. As AI gets more complicated, these issues tend to increase, similar to problems found in complex biological systems.

Psychology Findings You Can Bank On

Unsafe Science • 54 implied HN points • 24 Dec 24
🔬 Science Cognitive Science
  1. Psychological research has produced valuable insights that can enhance our understanding of human behavior. It's important to pay attention to these findings.
  2. Some claims made in the social sciences are questionable and need to be critically evaluated. Not everything that is published is reliable.
  3. There's ongoing debate about the quality of psychological studies, so it's good to be skeptical and look for well-supported evidence.

Should psycholinguists use LLMs as "model organisms"?

The Counterfactual • 39 implied HN points • 17 Jul 23
🔬 Science Cognitive Science
  1. Using model organisms in research helps scientists study complex systems where human testing isn't possible. But ethics and how well these models represent humans are big concerns.
  2. LLMs, or Large Language Models, may offer a new way to study language by providing insights without needing to use animal models. They can help test theories about language acquisition and comprehension.
  3. Though LLMs have serious limitations, they can still be useful for understanding how language functions. Researchers can learn about what types of input are important and how language is processed in the brain.

Cognitive Science needs linguistic diversity

The Counterfactual • 59 implied HN points • 20 Feb 23
🔬 Science Cognitive Science
  1. Cognitive science and linguistics are often too focused on English, which means we miss out on understanding how different languages work. Studying only a few languages makes it hard to see the full picture of language and cognition.
  2. Different languages influence how we think and perceive the world. For example, some languages have unique ways of expressing colors or time that can change how speakers of those languages understand these concepts.
  3. To improve our understanding of cognition, researchers need to include a wider variety of languages in their studies. We should explore languages beyond English to get a better grasp on how the human mind works across different cultures.

The Willpower to Care About Academic Debates

Living Fossils • 31 implied HN points • 12 Feb 25
🚌 Education Cognitive Science
  1. Ego depletion, the idea that willpower decreases after making tough choices, has been largely debunked. Many studies found that there is no strong evidence to support this theory.
  2. The ego depletion debate shows how important solid theories are in science. Without a strong theory, even widely accepted ideas can lead researchers astray.
  3. Psychology needs to be more disciplined in building ideas that align with what we know about the human mind and evolution. This helps avoid wasting time on false concepts.

What metastructures might LLMs have?

How the Hell • 68 implied HN points • 29 Jun 24
🕹 Technology Cognitive Science
  1. LLMs have different layers, like humans do. Lower layers handle basic language, while higher layers form more complex ideas.
  2. These models might develop their own unique structures for understanding visuals, since they don't see like humans do.
  3. There could be even higher layers that aren't just about language but add more complexity. It's still unclear how we might study these structures.

Chaos is the most unrecognized form of order

Hack-a-craft’s Weekly Digest • 2 implied HN points • 17 Dec 25
🔬 Science Cognitive Science
  1. Chaotic systems follow precise rules but are extremely sensitive to tiny differences, so small changes can produce huge, unpredictable outcomes.
  2. People expect simple, linear cause and effect, so they often miss the hidden order in chaotic situations that don’t follow straight lines.
  3. Disruption and uncertainty can spark creativity and innovation by breaking old patterns and letting new, better orders emerge.

Bicycles for the Mind and Software-Augmented Mentats

Bzogramming • 30 implied HN points • 06 Jan 25
🕹 Technology Cognitive Science
  1. Our minds work like software made up of various pieces that interact with each other. The way we learn, remember, and think can change based on our experiences and the information we take in.
  2. Computers can help enhance our thinking, just like a bike helps us move better. But we still have a long way to go in fully using technology to improve how we think and learn.
  3. As we learn more about how the brain works and how to interact with computers, we may discover new ways to enhance our mental abilities. This could lead to different skills and talents that we haven't seen before.

What's Going on Under the Hood of LLMs

The End of Reckoning • 19 implied HN points • 21 Feb 23
🔬 Science Cognitive Science
  1. Transformer models, like LLMs, are often considered black boxes, but recent work is shedding light on the internal processes and interpretability of these models.
  2. Induction heads in transformer models help with in-context learning and the ability to predict information based on the sequence of tokens seen before.
  3. By analyzing hidden states and conducting memory-based experiments, researchers are beginning to understand how transformer models store and manipulate information, providing insights into how these models may represent truth internally.

Jane Austen and Cognitive Bias—Or on Persuasion

Vremya • 139 implied HN points • 01 Jun 21
📚 Literature Cognitive Science
  1. Jane Austen explores the idea of love and how men and women experience it differently. She suggests that women may find it harder to move on from love than men do.
  2. Motivated reasoning is a key concept, where people look for evidence that supports what they already believe. This means we often see our own experiences as proof for our opinions.
  3. Austen also hints at cognitive biases like the availability heuristic, which is when we overestimate how common something is based on how easily we can recall examples from our life. This can lead to skewed perceptions of reality.

Welcome, and what this is

The Counterfactual • 59 implied HN points • 17 Jul 22
🚌 Education Cognitive Science
  1. The newsletter will cover topics like language, statistics, and AI, mixing research with personal thoughts. Expect both solid research reviews and imaginative columns about the future.
  2. Posts will be written in a clear, clean format using Substack. This platform helps catch mistakes easily and connects with a larger community of writers and readers.
  3. The author aims to write about things that are interesting and useful, hoping to share knowledge and insights that spark curiosity in readers.

Straightlining OCD

Living Fossils • 15 implied HN points • 18 Dec 24
🏥 Health & Wellness Cognitive Science
  1. Humans have evolved in messy environments, but our modern spaces are often too neat and straight. This neatness can create feelings of dissatisfaction and perfectionism, as humans are always seeking better conditions.
  2. OCD might be more common today because our environments exaggerate feelings of dissatisfaction. We notice minor imperfections more easily in our structured lives than our ancestors did in their chaotic natural settings.
  3. People today are better equipped to try and fix their surroundings, which can lead to a cycle of anxiety and compulsive behavior. Our ability to improve things can sometimes make us feel worse when everything doesn't match our ideals.

Learning Starts by Caring About Something

peoplefirstengineering • 14 implied HN points • 13 Nov 24
🚌 Education Cognitive Science
  1. Emotional engagement is key to learning. We remember things better when we care about them and connect emotionally to the experiences.
  2. Learning is more effective in collaborative settings. Working together with others, like in pair programming or group discussions, helps make the learning process more meaningful.
  3. To truly learn, we should explore what matters to us. Finding our personal connections to topics can lead to deeper understanding and growth.

Blowing off steam or picking a scab?

The Counterfactual • 19 implied HN points • 20 Dec 22
📖 Philosophy Cognitive Science
  1. Metaphors shape how we think about emotions like anger. For example, saying we need to 'blow off steam' suggests that expressing anger can help relieve it.
  2. Some people feel that expressing anger, like 'picking at a wound,' can make it worse over time. It may lead to more anger instead of helping to heal it.
  3. Choosing a metaphor for anger depends on the person and situation. Both 'blowing off steam' and 'picking a scab' have valid points about handling anger, but they suggest different approaches.

Episodic Memory for Gossip

The Memory Palace • 1 HN point • 21 May 24
📖 Philosophy Cognitive Science
  1. We often share memories to understand others better and make smarter choices about who we work with. Gossip, or sharing stories about people's past actions, plays a big role in this.
  2. Episodic memory may have evolved to help us remember people's behaviors, which helps us avoid bad partners and build better cooperation. Remembering who can be trusted is really important for survival.
  3. Sharing stories about others is a great way to learn without putting ourselves at risk. It helps us judge people's actions and create a better understanding of their reputations in our social circles.

Letter #5: The transmission of the listener

Charles Eisenstein • 3 implied HN points • 28 Jun 25
📖 Philosophy Cognitive Science
  1. Creating something meaningful can be both rewarding and tiring. It's important to acknowledge that mix of feelings.
  2. Engagement with the audience can lead to a deeper understanding of your work. Listening to feedback helps improve and grow your ideas.
  3. Taking breaks after intense focus on a project is helpful. It gives you time to reflect and recharge for the next challenges.

Bird Perspectives and Outside Views

Seeking Bird Perspectives • 6 implied HN points • 02 Dec 24
📖 Philosophy Cognitive Science
  1. The bird perspective means looking at things from a higher viewpoint to understand the bigger picture. It helps you see how your situation fits into a larger context.
  2. The outside view uses past experiences and similar cases to predict outcomes, but it can miss important details about your specific situation. It's important to find a balance between general predictions and unique factors.
  3. Using these perspectives can help reduce biases in decision-making. They inspire clearer thinking, but they shouldn't be used as the only way to argue or win a debate.

#11: Productive discomfort

The Uncertainty Mindset (soon to become tbd) • 59 implied HN points • 14 Jan 20
🚌 Education Cognitive Science
  1. Embracing discomfort can lead to personal growth. Learning new things often feels uncomfortable, but it can help expand your skills and knowledge.
  2. Regularly challenging yourself can make discomfort easier to handle. By gradually exposing yourself to tough situations, you can improve your ability to cope with stress and anxiety.
  3. Curiosity in the face of discomfort leads to valuable insights. Instead of avoiding unpleasant feelings, exploring what makes you uncomfortable can reveal opportunities for learning and innovation.

Should we teach children to memorize the multiplication tables?

The Science of Learning • 4 HN points • 26 Jun 23
🚌 Education Cognitive Science
  1. Children benefit from memorizing multiplication tables because it helps them solve math problems more easily. When students know their math facts, they can focus on more complex thinking instead of getting stuck on basic calculations.
  2. Research shows that students who memorize math facts do better in math overall. This memorization builds a strong foundation for advanced math skills later on.
  3. It's important to strike a balance between memorization and understanding in math education. Teaching kids to remember math facts can actually support their overall learning and make problem-solving easier.

What's the Price Elasticity of Demand for Intelligence?

How the Hell • 3 HN points • 18 May 24
🕹 Technology Cognitive Science
  1. The price of cognitive work, measured in 'cycogs,' varies widely and changes how much people might buy depending on cost. As the price goes down, more people are likely to use this intelligence.
  2. At different price points, people's spending on cognitive work can increase significantly. For example, if cycogs cost $1, people might buy a lot more because it allows for more access to services and creative projects.
  3. As technology improves and costs drop, traditional jobs in knowledge work might decline because many will prefer custom, AI-generated solutions for their needs.

Human of the Gaps

Supermedicine • 4 implied HN points • 25 Mar 23
🔬 Science Cognitive Science
  1. Gaps in AI capabilities are not evidence of human exceptionalism.
  2. The 'God of the Gaps' logical fallacy relates to invoking higher powers in areas of ignorance.
  3. Humans being unique is due to temporary limits, not supernatural qualities.

Space is a sensory-motor sequence in the hippocampus

Artificial General Ideas • 1 implied HN point • 12 Aug 24
🔬 Science Cognitive Science
  1. The hippocampus may not just represent physical space but instead processes space as a sequence of sensory and motor experiences. This means how we perceive space comes from our interactions, not just where we are.
  2. Place cells in the brain react to specific sequences of observations rather than directly to locations themselves. This explains why experiences in different environments can create similar neural responses.
  3. New models, like causal graphs, allow for better understanding and planning in navigational tasks. They can adapt to new environments quickly by using learned sequences without needing to rely on exact spatial representations.

How to get a million bucks: quick thoughts on cognitive programs and the ARC challenge.

Artificial General Ideas • 1 implied HN point • 13 Jun 24
🕹 Technology Cognitive Science
  1. The ARC challenge is about understanding abstract concepts from visual inputs and applying them to new situations. It's tricky because it's not based on a strict set of rules, making it harder to solve.
  2. Cognitive programs need a controllable world model to work properly. This means they must be able to run simulations using the information they have about the world.
  3. Abstract reasoning tests, like ARC, are important but not complete measures of intelligence. They need to be systematic and clear to truly assess reasoning skills.