Everything net
LLM / Foundation models can provide the structural ...
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... In popular media, there is often a connection drawn between the advent of awareness in artificial agents and those same agents simultaneously achieving human or superhuman level intelligence. ...

... In this work, we explore the validity and potential application of this seemingly intuitive link between consciousness and intelligence. ...

... We find that all three theories specifically relate conscious function to some aspect of domain-general intelligence in humans. ...

... With this insight, we turn to the field of Artificial Intelligence (AI) and find that, while still far from demonstrating general intelligence, many state-of-the-art deep learning methods have begun to incorporate key aspects of each of the three functional theories. ...

... Given this apparent trend, we use the motivating example of mental time travel in humans to propose ways in which insights from each of the three theories may be combined into a unified model. ...

... We believe that doing so can enable the development of artificial agents which are not only more generally intelligent but are also consistent with multiple current theories of conscious function. ...

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How to cultivate Asian heritage languages in the classroom for children from Asian immigrant families? For teachers who don't ...(108 more characters.)
Education Language Resources classroom Translanguaging
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How might young school children be introduced to coding?
Education school children Coding classroom
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... Collective Intelligence ...

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... [https://www.inc.com/bill-murphy-jr/how-emotionally-intelligent-people-use-send-a-bible-rule-to-become-remarkably-more-memorable.html](https://www.inc.com/bill-murphy-jr/how-emotionally-intelligent-people-use-send-a-bible-rule-to-become-remarkably-more-memorable.html) ...

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emotional intelligence
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... This is consistent with the theory of Cultural Group Selection as an explanation for the rise of human large-scale cooperation. ...

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... Where causality comes in is when we venture to model the 1/2 https://t.co/AmgYUOenjq ...

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... Thread… Here’s my basic understanding of the model: the economy has some industries that are capital intensive and others that are not. When the central bank makes interest rates artificially low, it makes capital investment cheap and skews the economy toward capital intensive sectors. ...

... The period through the end of 2007 arguably fits the austrian model. There was arguably over investment in residential home construction. In 2006 and 2007 the home building industry was contracting while other industries were still growing. But in mid 2008, the situation changed. ...

... I can’t figure out how to explain this period with an Austrian model. I don’t see why anyone would consider this kind of mass unemployment necessary or how it set us up for stronger growth later. ...

2948 characters.

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4 items
Human brains have no biological apparatus for logic thinking (or, more broadly speaking, system 2 thinking). This is in contrast with the fact that human language faculties are more likely supported by prewired circuitries.
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More precisely, LLMs model the concepts in natural languages using the language (albeit in a different syntax). Obviously, LLMs don't need to learn the concepts from scratch, they already have encoded words. More importantly, it doesn't need to learn a representation of the kinds of relationships between concepts, those are also encoded in words in the language as well, such as, "is", "belong to," "cause", etc. Here comes the more speculative part. To perform cognitive tasks, LLMs need to learn the specific relationships between specific concepts, and those relationships can be connections between a group of words, e.g., "swan", "black", "is", here "swan" and "black" are two concepts while "is" is the relationship between them. However, such groups of words can have multiple interpretations. Thus to truly encode a specific relationship, LLMs need to have connections embedded with syntax. e.g. it needs to encode the relationship between "black," and "swan" as "swan is black". i.e. A language phrase encodes the relationship. Thus one might be able to say that LLMs model the world in language. It might be a totally different gramma from natural language, but a syntax nonetheless and it's quite possible that this syntax is inspired by the syntax in natural language. The ability to model concepts using words, phrases and even sentences combined with syntax is critical. [It might be the reason we humans reached our level of intelligence](https://www.themind.net/hypotheses/8yof9E9YTYu4vHQI4qgBcw).
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This is how humans reached this level of intelligence. In some sense, language and its syntax provides the programming language for brains and reduced the need for specialized neural circuitries. To reach the same level of intelligence without a vastly larger number of neural circuitries in artificial neuron networks, they need to be able to do the same thing. .
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Because this self-supervised learning process mimics the brain's learning mechanism: make predictions and learn from prediction errors.
50.0%
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... Super intelligence without AGI: collective intelligence consists of both human and artificial non-general intelligence. It is race between the technology development between AGI and that of super intelligence. ...

211 characters.

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... That being said, the chat bot format did provide a great way for a wider community to explore potential use cases with LLM hence directions for future development (#GPT4?). It's probably the original intention of the release, but the community got carried away. ...

449 characters.

LLM ChatGPT
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... How to make sure that the first AGI is minimum ly safe\, I\.e\. never hostile to human \(behavioral vise\) and 2\. How to make sure such an benevolent AGI can defeat all other forms of unsafe AGIs\, known or unknown\.
...

232 characters.

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... Collective digitalized mind, i.e. digitalized and connected thoughts/ideas from multiple users by itself, may not automatically achieve collective intelligence (the intelligent capabilities of solving problems collectively). ...

379 characters.

p/Collective Intelligence p/The Mind Net
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Read this [fascinating paper. ]( https://arxiv.org/abs/2204.05133)Made me think that developing such an AI system that incorporates ...(175 more characters.)
AGI
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... Isn't the source of the deep historical pessimism in the 20th century our lack of understanding regarding humans' tendency of violence against fellow humans? If this mystery is solved by EDSC, then can it turn into a foundation for a deep historical optimism? ...

262 characters.

EDSC
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... In SayCan, we showed how we can connect robot learning pipelines to large language models, bringing a lot of common sense knowledge to robotics. The hope was that as the LLMs become better (which they seem to be consistently doing), it will have a positive effect on robotics. ...

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p/investing
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Aggregation of opinions over the thoughts and ideas in a digitalized collective mind to give them different weights and importance ...(39 more characters.)
p/Collective Intelligence p/The Mind Net
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Social intelligence is the driving evolutionary pressure responsible for the development of human intelligence
79.2%
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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
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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
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