The hottest Reasoning Substack posts right now

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Meta-rational practices: Overview 1

Meaningness • 219 implied HN points • 09 Mar 24
📖 Philosophy Meta-rationality Norms Practices Reasoning
  1. Meta-rationality is different from traditional rationality and requires an open-ended inquiry and responsiveness to various contexts and purposes.
  2. Meta-rationality involves ongoing consideration of when and how to apply rationality, recognizing situations where rational methods may not be sufficient.
  3. The norms of reasonableness, rationality, and meta-rationality differ in terms of accountability, formal rules adherence, and responsiveness to context and purpose.

Gain of Function.

News Items • 471 implied HN points • 18 Jan 24
🔬 Science AI Mathematics Reasoning Training
  1. AlphaGeometry AI system solves complex geometry problems as well as a human Olympiad gold-medalist.
  2. AlphaGeometry combines neural language model with a rule-bound deduction engine for reasoning.
  3. Development of AlphaGeometry highlights AI's logic reasoning progress and ability to discover and verify new knowledge.
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3 Tests AGI Must Pass

Insight Axis • 237 implied HN points • 27 Aug 23
🕹 Technology AI Computing Testing Reasoning Creativity
  1. Computers must excel at calculations to form the foundation for any further intelligence programming.
  2. After calculation, computers need to progress to reasoning - the ability to evaluate information and use it to make value-based decisions.
  3. The ultimate test for artificial intelligence is creativity - the capability to acknowledge rules but break them intuitively to create something new.

Chain of Thought Prompting for LLMs

Deep (Learning) Focus • 294 implied HN points • 24 Apr 23
🕹 Technology AI Deep Learning Language Models Reasoning Prompting
  1. CoT prompting leverages few-shot learning in LLMs to improve their reasoning capabilities, especially for complex tasks like arithmetic, commonsense, and symbolic reasoning.
  2. CoT prompting is most beneficial for larger LLMs (>100B parameters) and does not require fine-tuning or extensive additional data, making it an easy and practical technique.
  3. CoT prompting allows LLMs to generate coherent chains of thought when solving reasoning tasks, providing interpretability, applicability, and computational resource allocation benefits.

Program-Aided Language Models

Deep (Learning) Focus • 196 implied HN points • 22 May 23
🕹 Technology AI Programming Reasoning Language Models Deep Learning
  1. LLMs can struggle with tasks like arithmetic and complex reasoning, but using an external code interpreter can help them compute solutions more accurately.
  2. Program-Aided Language Models (PaL) and Program of Thoughts (PoT) techniques leverage both natural language and code components to enhance reasoning capabilities of LLMs.
  3. Decoupling reasoning from computation within LLMs through techniques like PaL and PoT can significantly improve performance on complex numerical tasks.

"Mid" is unfalsifiable

Philosophy bear • 62 implied HN points • 18 May 23
📖 Philosophy Concepts Reasoning Reality Ethics
  1. Calling someone 'mid' is unfalsifiable because it's hard to prove you're not just average.
  2. Labeling someone as 'mid' can lead to implications similar to being called 'ugly'.
  3. The concept of 'mid' has become popular due to unrealistic expectations and fear of commitment in relationships.

Understanding human stupidity in a post-truth era

Klement on Investing • 9 implied HN points • 05 Jan 24
📖 Philosophy Human nature Reasoning Education Satire
  1. Human stupidity involves a temporary inability to properly reason, plan, or learn.
  2. Stubbornness often accompanies stupidity, making people hold on to disproven beliefs.
  3. In a post-truth era, combating human stupidity requires strong institutions, satire, education, and sometimes allowing people to face the consequences of their beliefs.

Can Large Language Models Reason?

AI: A Guide for Thinking Humans • 4 HN points • 10 Sep 23
🔬 Science Reasoning Language Models Evaluation Pattern matching
  1. There is a debate about whether large language models have reasoning abilities similar to humans or rely more on memorization and pattern-matching.
  2. Models like CoT prompting try to elicit reasoning abilities in these language models and can enhance their performance.
  3. However, studies suggest that these models may rely more on memorization and pattern-matching from their training data than true abstract reasoning.

GRANTED: Reasoning with unreasonable people

Granted • 0 implied HN points • 31 Jan 21
🚌 Education Reasoning Learning Debate Teaching
  1. The primary goal of a university is more about promoting the pursuit of knowledge rather than just teaching skills.
  2. In arguments, rather than preaching or prosecuting, try treating it like an interview by asking questions to help others consider their reasons for change.
  3. Recognize the 'I'm-not-biased' bias by understanding that knowing what you don't know is wisdom.

An Introduction to the Philosophies of Baruch Spinoza

Wayne's Earth • 0 implied HN points • 15 Dec 22
📖 Philosophy God Ethics Reasoning Morality History
  1. Spinoza believed that God and nature are one and the same, a view known as pantheism, which suggests that all things in nature are expressions of a single divine force. This unity prompts us to appreciate and honor nature.
  2. Spinoza advocated for an ethical system grounded in reason rather than emotions or religious doctrines. He emphasized judging actions by their consequences and thinking critically about decisions to prevent harm to others.
  3. Even centuries later, Spinoza's ideas on God, nature, ethics, and reason are influential. His insights are appreciated by modern philosophers, highlighting his timeless wisdom and significant impact on philosophical thought.