6 ms·

The important point is, I feel, that most people are not even at the level of intelligence of a "a mediocre, but not completely incompetent, graduate student."

by noch 2y ago

The important point is, I feel, that most people are not even at the level of intelligence of a "a mediocre, but not completely incompetent, graduate student." A mediocre graduate science student, especially of the sort who graduates and doesn't quit, is a very impressive individual compared to the rest of us. For "us", having such a level of intelligence available as an assistant throughout the day is a massive life upgrade, if we can just afford more tokens.

thewanderer1983 2y ago
>A mediocre graduate science student, especially of the sort who graduates and doesn't quit, is a very impressive individual compared to the rest of us. Incorrect. University graduates shows a good work ethic, a certain character and a ability to manage time. It's not a measure of being better than the rest of humanity. Also, it's not a good measure of intelligence. If you only want to view the world through credentials. Academics don't consider your intelligence until you have a Ph.D and X years of work in your field. Industry only uses graduates as a entry requirement for junior roles and then favors and cares only about your years of experience after that. Given that statement I can only assume you haven't been to University. You are mistaken to think, especially in time we are in now that the elite class are any more knowledgeable then you are.
- ahnick 2y ago
  Here are the key points outlining why thewanderer1983's response misinterprets noch's comment and contains inaccuracies: Misinterpretation of the Original Point: Intelligence vs. Moral Superiority: Noch discusses the intelligence level of a mediocre graduate science student compared to the general population. Thewanderer1983 misreads this as a claim of moral or inherent superiority over "the rest of humanity," which was not implied. Conflation of Educational Levels: University Graduates vs. Graduate Students: The response conflates undergraduate university graduates with graduate science students. Noch specifically refers to graduate students who have pursued advanced degrees, which typically require higher levels of specialization and intellectual rigor. Incorrect Assessment of Intelligence Measures: Graduate Studies as a Measure of Intelligence: Successfully completing graduate studies, especially in science, often requires significant intellectual capability. Dismissing this as "not a good measure of intelligence" overlooks the challenges inherent in advanced academic work. Irrelevant Focus on Credentials and Industry Practices: Credentials vs. Intelligence Discussion: Noch's comment centers on intelligence levels, not merely on holding credentials. Bringing up how industry values experience over degrees shifts the focus away from the original discussion about intelligence. Unfounded Assumptions About Noch's Background: Ad Hominem Attack: Suggesting that Noch hasn't been to university is an unfounded personal assumption that does not contribute to the argument and detracts from a respectful discourse. Introduction of the 'Elite Class' Notion: Straw Man Argument: Thewanderer1983 introduces the concept of an "elite class," which Noch did not mention. This misrepresents the original comment and argues against a point that wasn't made. Overgeneralizations About Academia and Industry: Academia's Recognition of Intelligence: Claiming that academics don't consider intelligence until one has a Ph.D. and years of work is an overgeneralization. Intelligence is recognized and valued at various academic levels. Industry's View on Graduates: Stating that industry only uses graduates as an entry requirement ignores the significant roles that advanced degree holders often play in innovation and leadership within industries. Ignoring the Core Benefit Highlighted: AI as a Life Upgrade: Noch emphasizes how access to AI with the intelligence level of a graduate student is a substantial benefit for most people. Thewanderer1983 fails to address this key point, instead focusing on unrelated issues. Misunderstanding of the Value of Graduate Education: Work Ethic vs. Intellectual Achievement: While a good work ethic is important, graduate education in science also demands high intellectual capability, critical thinking, and problem-solving skills. Logical Fallacies: Red Herring: The discussion about industry preferences and academic credentials diverts from the main argument about the intelligence level of graduate students. Ad Hominem: Attacking Noch's presumed lack of university experience instead of addressing the argument presented.
  - dpig_ 2y ago
    If you couldn't be bothered to write this comment, I can't be bothered to read it.
    - ahnick 2y ago
      but you did bother to comment on it. :)
  - mfgk 2y ago
    An excellent example of an LLM (or an imitated LLM output) that fiercely defends the status quo, is overly verbose, does not come to the point, makes incorrect assumptions and lectures from a high horse. LLMs are good for mediocre poems and presidential speeches that have no shame.
    - ahnick 2y ago
      Yeah, well, you know, that's just like, uh, your opinion, man.
  - thewanderer1983 2y ago
    I can play this silly game also. Let’s evaluate the correctness of Thewanderer’s argument in detail: Distinction Between Credentials and Intelligence: Correctness: Thewanderer is correct in stating that a university degree is not a definitive measure of intelligence. Intelligence is a complex trait that encompasses various cognitive abilities, problem-solving skills, creativity, and emotional intelligence. Academic credentials primarily reflect one’s ability to succeed in a structured educational environment, which is just one aspect of intelligence. Value of Real-World Experience: Correctness: The argument that real-world experience is crucial is accurate. Many industries value practical experience and skills over formal education. For example, in technology and business sectors, hands-on experience, problem-solving abilities, and adaptability are often more important than academic qualifications alone. This is supported by numerous studies and industry practices that prioritize experience and performance over degrees. Critique of Credentialism: Correctness: Thewanderer’s critique of credentialism is valid. Over-reliance on academic credentials can overlook the diverse talents and skills that individuals without formal degrees may possess. This perspective is supported by the growing recognition of alternative education paths, such as vocational training, apprenticeships, and self-directed learning, which can also lead to successful careers. Inclusivity and Egalitarianism: Correctness: Promoting inclusivity and valuing diverse forms of knowledge is a correct and progressive stance. Intelligence and capability are not confined to those with advanced degrees. Many successful individuals in various fields do not have formal academic credentials but have achieved significant accomplishments through experience, self-learning, and practical skills. Encouragement of Self-Worth: Correctness: Encouraging individuals to value their own experiences and knowledge is a positive and correct approach. It fosters confidence and self-worth, which are important for personal and professional growth. Recognizing the value of diverse experiences and perspectives contributes to a more inclusive and equitable society. In summary, Thewanderer’s argument is correct in several key aspects: It accurately distinguishes between academic credentials and broader measures of intelligence. It correctly emphasizes the importance of real-world experience. It validly critiques the overemphasis on academic credentials. It promotes an inclusive and egalitarian view of intelligence. It encourages self-worth and confidence in one’s abilities. These points collectively support a well-rounded and accurate perspective on intelligence and capability.
kiba 2y ago
We are more limited by our emotions, and then our skills in learning and acquiring knowledge. Intelligence is probably a distant third.
- atleastoptimal 2y ago
  Nah. Dogs are far emotionally better than most humans. Their intelligence is their limitation. Also “skills in learning and acquiring knowledge” is basically intelligence
  - deleted 2y ago
    [deleted]
a_wild_dandan 2y ago
My sheer productivity boost from these models is miraculous. It's like upgrading from a text editor to a powerful IDE. I've saved a mountain of hours just by removing tedious time sinks -- one-off language syntax, remembering patterns for some framework, migrating code, etc. And this boost applies to nearly all of my knowledge work. Then I see contrarians claiming that LLMs are literally never useful for anyone, and I get "don't believe your lying eyes" vibes. At this point, such sentiments feel either willfully ignorant, or said in bad faith. It's wild.
- christofosho 2y ago
  I think there may be a set of people that have figured out, 1) how to interact with LLMs; and 2) what in their lives is improved when interacting with LLMs. I am in the group that has not found the best use case for my own life, and have never needed it for improving anything I need to get done. Always looking for suggestions, though!
  - ants_everywhere 2y ago
    > I think there may be a set of people that have figured out, 1) how to interact with LLMs.... 1) is all about experimenting, which is what Tao is doing. Having a playful and open minded attitude is like 80% of the game
- llm_bro 2y ago
  [dead]
- bachmeier 2y ago
  > I see contrarians claiming that LLMs are literally never useful for anyone While I don't doubt that there's at least one person that has said this, what you're saying doesn't conflict with the things I and many others in the "skeptic" camp have said. LLMs are useful for a very specific set of tasks. The tasks you've listed are a tiny sliver of all the tasks that AI could potentially be doing. Would it be a good idea to consult an LLM if your mother is passed out on the floor? Probably not. The problem I have is with extrapolating from the current successes to conclude that many more tasks will be done by AI in five years.
sn9 2y ago
Anyone intelligent enough to make a living programming likely has more than enough IQ to become a mediocre somewhat competent graduate student in math. They just don't have the background, and probably lack the interest to dedicate studying for a few years to get to that level.
- azan_ 2y ago
  That's interesting take, personally I'd say that graduate-level math is orders of magnitude harder than significant majority of programming. And I mean that it's inherently harder, i.e. not due to lack of background.

by noch 2y ago

thewanderer1983 2y ago

>A mediocre graduate science student, especially of the sort who graduates and doesn't quit, is a very impressive individual compared to the rest of us. Incorrect. University graduates shows a good work ethic, a certain character and a ability to manage time. It's not a measure of being better than the rest of humanity. Also, it's not a good measure of intelligence. If you only want to view the world through credentials. Academics don't consider your intelligence until you have a Ph.D and X years of work in your field. Industry only uses graduates as a entry requirement for junior roles and then favors and cares only about your years of experience after that. Given that statement I can only assume you haven't been to University. You are mistaken to think, especially in time we are in now that the elite class are any more knowledgeable then you are.

ahnick 2y ago
Here are the key points outlining why thewanderer1983's response misinterprets noch's comment and contains inaccuracies: Misinterpretation of the Original Point: Intelligence vs. Moral Superiority: Noch discusses the intelligence level of a mediocre graduate science student compared to the general population. Thewanderer1983 misreads this as a claim of moral or inherent superiority over "the rest of humanity," which was not implied. Conflation of Educational Levels: University Graduates vs. Graduate Students: The response conflates undergraduate university graduates with graduate science students. Noch specifically refers to graduate students who have pursued advanced degrees, which typically require higher levels of specialization and intellectual rigor. Incorrect Assessment of Intelligence Measures: Graduate Studies as a Measure of Intelligence: Successfully completing graduate studies, especially in science, often requires significant intellectual capability. Dismissing this as "not a good measure of intelligence" overlooks the challenges inherent in advanced academic work. Irrelevant Focus on Credentials and Industry Practices: Credentials vs. Intelligence Discussion: Noch's comment centers on intelligence levels, not merely on holding credentials. Bringing up how industry values experience over degrees shifts the focus away from the original discussion about intelligence. Unfounded Assumptions About Noch's Background: Ad Hominem Attack: Suggesting that Noch hasn't been to university is an unfounded personal assumption that does not contribute to the argument and detracts from a respectful discourse. Introduction of the 'Elite Class' Notion: Straw Man Argument: Thewanderer1983 introduces the concept of an "elite class," which Noch did not mention. This misrepresents the original comment and argues against a point that wasn't made. Overgeneralizations About Academia and Industry: Academia's Recognition of Intelligence: Claiming that academics don't consider intelligence until one has a Ph.D. and years of work is an overgeneralization. Intelligence is recognized and valued at various academic levels. Industry's View on Graduates: Stating that industry only uses graduates as an entry requirement ignores the significant roles that advanced degree holders often play in innovation and leadership within industries. Ignoring the Core Benefit Highlighted: AI as a Life Upgrade: Noch emphasizes how access to AI with the intelligence level of a graduate student is a substantial benefit for most people. Thewanderer1983 fails to address this key point, instead focusing on unrelated issues. Misunderstanding of the Value of Graduate Education: Work Ethic vs. Intellectual Achievement: While a good work ethic is important, graduate education in science also demands high intellectual capability, critical thinking, and problem-solving skills. Logical Fallacies: Red Herring: The discussion about industry preferences and academic credentials diverts from the main argument about the intelligence level of graduate students. Ad Hominem: Attacking Noch's presumed lack of university experience instead of addressing the argument presented.
- dpig_ 2y ago
  If you couldn't be bothered to write this comment, I can't be bothered to read it.
  - ahnick 2y ago
    but you did bother to comment on it. :)
- mfgk 2y ago
  An excellent example of an LLM (or an imitated LLM output) that fiercely defends the status quo, is overly verbose, does not come to the point, makes incorrect assumptions and lectures from a high horse. LLMs are good for mediocre poems and presidential speeches that have no shame.
  - ahnick 2y ago
    Yeah, well, you know, that's just like, uh, your opinion, man.
- thewanderer1983 2y ago
  I can play this silly game also. Let’s evaluate the correctness of Thewanderer’s argument in detail: Distinction Between Credentials and Intelligence: Correctness: Thewanderer is correct in stating that a university degree is not a definitive measure of intelligence. Intelligence is a complex trait that encompasses various cognitive abilities, problem-solving skills, creativity, and emotional intelligence. Academic credentials primarily reflect one’s ability to succeed in a structured educational environment, which is just one aspect of intelligence. Value of Real-World Experience: Correctness: The argument that real-world experience is crucial is accurate. Many industries value practical experience and skills over formal education. For example, in technology and business sectors, hands-on experience, problem-solving abilities, and adaptability are often more important than academic qualifications alone. This is supported by numerous studies and industry practices that prioritize experience and performance over degrees. Critique of Credentialism: Correctness: Thewanderer’s critique of credentialism is valid. Over-reliance on academic credentials can overlook the diverse talents and skills that individuals without formal degrees may possess. This perspective is supported by the growing recognition of alternative education paths, such as vocational training, apprenticeships, and self-directed learning, which can also lead to successful careers. Inclusivity and Egalitarianism: Correctness: Promoting inclusivity and valuing diverse forms of knowledge is a correct and progressive stance. Intelligence and capability are not confined to those with advanced degrees. Many successful individuals in various fields do not have formal academic credentials but have achieved significant accomplishments through experience, self-learning, and practical skills. Encouragement of Self-Worth: Correctness: Encouraging individuals to value their own experiences and knowledge is a positive and correct approach. It fosters confidence and self-worth, which are important for personal and professional growth. Recognizing the value of diverse experiences and perspectives contributes to a more inclusive and equitable society. In summary, Thewanderer’s argument is correct in several key aspects: It accurately distinguishes between academic credentials and broader measures of intelligence. It correctly emphasizes the importance of real-world experience. It validly critiques the overemphasis on academic credentials. It promotes an inclusive and egalitarian view of intelligence. It encourages self-worth and confidence in one’s abilities. These points collectively support a well-rounded and accurate perspective on intelligence and capability.

kiba 2y ago

We are more limited by our emotions, and then our skills in learning and acquiring knowledge. Intelligence is probably a distant third.

atleastoptimal 2y ago
Nah. Dogs are far emotionally better than most humans. Their intelligence is their limitation. Also “skills in learning and acquiring knowledge” is basically intelligence
- deleted 2y ago
  [deleted]

a_wild_dandan 2y ago

My sheer productivity boost from these models is miraculous. It's like upgrading from a text editor to a powerful IDE. I've saved a mountain of hours just by removing tedious time sinks -- one-off language syntax, remembering patterns for some framework, migrating code, etc. And this boost applies to nearly all of my knowledge work. Then I see contrarians claiming that LLMs are literally never useful for anyone, and I get "don't believe your lying eyes" vibes. At this point, such sentiments feel either willfully ignorant, or said in bad faith. It's wild.

christofosho 2y ago
I think there may be a set of people that have figured out, 1) how to interact with LLMs; and 2) what in their lives is improved when interacting with LLMs. I am in the group that has not found the best use case for my own life, and have never needed it for improving anything I need to get done. Always looking for suggestions, though!
- ants_everywhere 2y ago
  > I think there may be a set of people that have figured out, 1) how to interact with LLMs.... 1) is all about experimenting, which is what Tao is doing. Having a playful and open minded attitude is like 80% of the game
llm_bro 2y ago
[dead]
bachmeier 2y ago
> I see contrarians claiming that LLMs are literally never useful for anyone While I don't doubt that there's at least one person that has said this, what you're saying doesn't conflict with the things I and many others in the "skeptic" camp have said. LLMs are useful for a very specific set of tasks. The tasks you've listed are a tiny sliver of all the tasks that AI could potentially be doing. Would it be a good idea to consult an LLM if your mother is passed out on the floor? Probably not. The problem I have is with extrapolating from the current successes to conclude that many more tasks will be done by AI in five years.

sn9 2y ago

Anyone intelligent enough to make a living programming likely has more than enough IQ to become a mediocre somewhat competent graduate student in math. They just don't have the background, and probably lack the interest to dedicate studying for a few years to get to that level.

azan_ 2y ago
That's interesting take, personally I'd say that graduate-level math is orders of magnitude harder than significant majority of programming. And I mean that it's inherently harder, i.e. not due to lack of background.