Answers.Body: <p>First of all, the statement <em>'it (AI) is an encyclopedia, not an expert'</em>, thus implies it cannot <em>'improve, use new techniques, tools, languages and so on'</em> is <strong>wrong</strong>. AI <strong>can</strong> discover new knowledge.</p>
  <p>Take the example of algorithm, which is the heart of programming. Do we agree that if someone invents a novel, effective algorithm, that makes him an expert?</p>
  <p>Then take a look at <a href="https://deepmind.google/discover/blog/discovering-novel-algorithms-with-alphatensor/" rel="nofollow noreferrer">this work</a>, where AI taught us a new and better way to multiple two matrices. We human have been tackling this task for thousands of years and the latest improvement was made in 1969 (half a century back). <strong>In writing better algorithm, AI can beat us to it</strong>.</p>
  <p>In fact it is not at all surprising; years back, the infamous version of AlphaGo, the <a href="https://deepmind.google/discover/blog/alphago-zero-starting-from-scratch/" rel="nofollow noreferrer">AlphaGo Zero</a>, which <strong>uses no (zero, nil) human knowledge</strong>, beat the whole mankind in the 3,000 years old game. In fact, it was discovered that if we incorporate human knowledge to the AI, its performance actually <em>worsens</em>. Human 'expertise' can be junk.</p>
  <p>If there is anything we human are better at: be humble and modest, realize and admit our limits, and always learn from those better than us.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-11T11:46:33.050Z
Answers.Text: Ok, improving matrix multiplication by going from 80 multiples down to 76. With massive amounts of hardware and work. Reminds me of replacing a headphone wire with 2 complex transceivers (Bluetooth) and 2 computers, all to go the same 3 feet. Will we ever tire of ourselves?
Answers.UserDisplayName: Edificial Inelegance
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Answers.CreationDate: 2024-01-11T13:09:30.020Z
Answers.Text: I couldn't read the linked article without creating an account, but OP mentions specifically "low performing employees". I suppose were are talking about programs like ChatGPT in this context, which is meant for the masses to generate answers "out of thin air". AlphaTensor and AlphaZero are in a totally different league, although they are good examples on how reinforcement learning can solve surprisingly difficult tasks. But those solutions are built by experts for experts.
Answers.UserDisplayName: NikoNyrh
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Answers.CreationDate: 2024-01-11T20:56:32.743Z
Answers.Text: @NikoNyrh the AlphaGo idea of having the AI figure things out for itself seems reasonable. We could just chuck programming and have AlphaCode make up a whole new thing from scratch. Worth a try...
Answers.UserDisplayName: Edificial Inelegance
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-12T10:48:38.827Z
Answers.Text: @EdificialInelegance you missed the point completely - AI has made a **discovery**, a **new algorithm** which can do a calculation 10-20% more effective than we ever know. The "*massive amounts of hardware and work*" was to discover the algorithm, much like human spending a lifetime researching. **No effort is needed to enjoy the benefit**. I suggest you to take some time to re-read the article and think about the implication.
Answers.UserDisplayName: lpounng
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-12T11:00:58.287Z
Answers.Text: @NikoNyrh If I read OP correctly, his point was "(because AI) **uses past information**... How can it help... to **improve**, use new techniques... and so on?" And my point is that 1: not all AI needs past (or more precisely, human's) information; 2: AI has shown that it can invent new techniques, tool, languages etc. which we never know nor imagined (recall the novel moves of Go, and the never-known matrix algorithm). Even we narrow down the scope to LLM, just like OP commented, what stops him to combine LLM with (say) AlphaCode, that can invent new algorithm per our request on-the-fly?
Answers.UserDisplayName: lpounng
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-12T14:27:11.090Z
Answers.Text: So let it rip, discover away. Just don't include old rubbish in the setup conditions. **Garbage In, Garbage Out**
Answers.UserDisplayName: Edificial Inelegance
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-13T14:56:37.310Z
Answers.Text: @EdificialInelegance Yes, I long for the day where we ignorance people learn to step aside and let AI do the job. No more garbage from human's bias and prejudice. AlphaGo Zero already showed us how harmful human's garbage knowledge can be.
Answers.UserDisplayName: lpounng
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-13T15:07:38.577Z
Answers.Text: "*'Tis a consummation devoutly to be wished.*"
Answers.UserDisplayName: Edificial Inelegance
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-22T02:20:49.340Z
Answers.Text: See, an encyclopedia using past info is talking. Can't produce new result though.
Answers.UserDisplayName: lpounng
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-11T04:54:25.233Z
Answers.LastActivityDate: 2024-01-11T06:34:45.673Z
Answers.LastEditDate: 2024-01-11T06:34:45.673Z
Answers.UserDisplayName: lpounng
Answers.Body: <p>From what you write it seems that you believe that human new ideas are not based on past experience. This is an extremly bold statement very difficult to prove.
  Almost everybody would define a new idea idea of the connection of two previously unconnected dots. Ai can do that as much as we can.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-01-11T11:50:04.183Z
Answers.Text: No, human new ideas are based only on experience. I think that AI is quite lacking in this area. Have you seen any AIs lately? What are they learning about a world of humans with needs and wants? Probably nothing. So why should we have them managing things for us?
Answers.UserDisplayName: Edificial Inelegance
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Answers.CreationDate: 2024-01-11T11:45:01.957Z
Answers.LastActivityDate: 2024-01-11T11:45:01.957Z
Answers.UserDisplayName: eugenio
Body: <p>I read a good <a href="https://www.businessinsider.com/ai-productivity-boost-job-performance-inequality-economics-2023-11" rel="nofollow noreferrer">article</a> about how AI raises the performance of low performing employees generally while not helping high performers as much. So employers might hire people with less experience, pay high performers less, fire high performers, etc.</p>
  <p>But don't people realize that AI uses past information? How can it help with areas like programming when you need to improve, use new techniques, tools, languages and so on? It can't, because it is an encyclopedia, not an expert.</p>
  <p>Will people learn this before some very bad choices are made? How can it be explained to them that recycling doesn't produce new stuff?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T01:04:51.810Z
Comments.Text: Yeah. I think the problem is much more complex. I think you're oversimplifying many of the real considerations of how AI is used and their different capabilities. You're being too broad in your statement. What type of AI are we talking about - LLMs, Transformers, Neural Networks, RL agents, Genetic Algorithms? I think each of these algorithms should be considered individually and not lumped together as "AI" because it can bring ambiguity. Personally, it is not that clear what AI will be able to do in the future and the argument that it is just recycling old stuff is not very well founded.
Comments.UserDisplayName: Cesar Ruiz
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T01:10:44.177Z
Comments.Text: @CesarRuiz Ok, so focus on the area of producing computer program code. My understanding is that it cobbles together things from existing examples. That can never write anything original in the sense of generalizing a method to a new language or situation. Heck, most humans have trouble with this. A lot has been written about why many programmers seem to lack understanding of basic programming concepts. So we're going to trust "the wisdom of (extrapolated) crowds"? Would you fly on that plane? Why pay people to do that?
Comments.UserDisplayName: Edificial Inelegance
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T01:18:23.690Z
Comments.Text: I was heartened when I heard someone say that if you sign off on something, *you the human*  are responsible for understanding it fully and providing it as your solution that you must stand by. Using tech is not a get-out clause. I hope that this becomes the bottom line for use of AI-generated material.
Comments.UserDisplayName: Edificial Inelegance
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T01:24:12.520Z
Comments.Text: I think it's still ambiguous because the methods I think you're talking about - the use of instruction trained LLM models for coding - does not represent all the LLMs able to code. I will reference the work by [Deepmind with FunSearch](https://deepmind.google/discover/blog/funsearch-making-new-discoveries-in-mathematical-sciences-using-large-language-models/) that does not use instruction based models in this case and demonstrates to be useful in generating "new ideas". Although there's could also be ambiguity on that term too. Just curious what do you think about their work?
Comments.UserDisplayName: Cesar Ruiz
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T01:31:32.060Z
Comments.Text: Well I made a mistake - technically FunSearch uses things like StarCoder or Codey that are instruction LLM models for coding. But they could use a fully pretrained model and still I think my argument could remain. I said this because at least for me the pretrained model could be seen as a more creative autocompleter of text even though much of its generations doesn't make much sense.
Comments.UserDisplayName: Cesar Ruiz
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T02:12:08.683Z
Comments.Text: As a programmer I often peruse many many pages of potential solutions and quickly bypass things that are far too complex or off-track. Quite frequently I abstract ideas from entirely different scenarios to create a simple, concise, understandable, maintainable solution.  Even if AI could suggest things that are relevant, you still need knowledge and experience to select and adjust the code to fit the situation. Coding is not just sticking Lego together, it is more like surgery. I found the idea laughable in the article of having junior Lawyers use AI suggestions. And in court they'll flounder.
Comments.UserDisplayName: Edificial Inelegance
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T08:12:41.087Z
Comments.Text: This question needs work. It presupposes an answer to a question (can AI generate novel solutions to coding problems), then is half rant, half impossible question about non-specific "people". I suggest alter the question to be about coding capabilities of AI, around the original assumption. Also worth clarifying whether asking about LLMs, or current crop of code assistants. These are far from being all of AI around code generation, although they get a lot of attention currently, and presumably what triggered the question
Comments.UserDisplayName: Neil Slater
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T11:51:33.810Z
Comments.Text: @NeilSlater thanks, I'll see what I can do.
Comments.UserDisplayName: Edificial Inelegance
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-01-11T12:27:46.280Z
Comments.Text: This is an interesting political/social question, but unfortunately it will only lead to opinions. My opinion is that people sometimes learn things too late or don't learn until they don't see the immediate effects, which may be too late to recover.
Comments.UserDisplayName: nbro
Tags: <ai-design>
Title: Do people realize that AI can't produce new results?
UserDisplayName: Edificial Inelegance
ThreadText: # Do people realize that AI can't produce new results?
  
  (Asked by: username_0 on 2024-01-11)
  
  I read a good [article](https://www.businessinsider.com/ai-productivity-boost-job-performance-inequality-economics-2023-11) about how AI raises the performance of low performing employees generally while not helping high performers as much. So employers might hire people with less experience, pay high performers less, fire high performers, etc.
  
  But don't people realize that AI uses past information? How can it help with areas like programming when you need to improve, use new techniques, tools, languages and so on? It can't, because it is an encyclopedia, not an expert.
  
  Will people learn this before some very bad choices are made? How can it be explained to them that recycling doesn't produce new stuff?
  
  **Tags:** ai-design
  > **Comments:**
  > **username_1**: Yeah. I think the problem is much more complex. I think you're oversimplifying many of the real considerations of how AI is used and their different capabilities. You're being too broad in your statement. What type of AI are we talking about - LLMs, Transformers, Neural Networks, RL agents, Genetic Algorithms? I think each of these algorithms should be considered individually and not lumped together as "AI" because it can bring ambiguity. Personally, it is not that clear what AI will be able to do in the future and the argument that it is just recycling old stuff is not very well founded.  
  > **username_0**: @CesarRuiz Ok, so focus on the area of producing computer program code. My understanding is that it cobbles together things from existing examples. That can never write anything original in the sense of generalizing a method to a new language or situation. Heck, most humans have trouble with this. A lot has been written about why many programmers seem to lack understanding of basic programming concepts. So we're going to trust "the wisdom of (extrapolated) crowds"? Would you fly on that plane? Why pay people to do that?  
  > **username_0**: I was heartened when I heard someone say that if you sign off on something, *you the human*  are responsible for understanding it fully and providing it as your solution that you must stand by. Using tech is not a get-out clause. I hope that this becomes the bottom line for use of AI-generated material.  
  > **username_1**: I think it's still ambiguous because the methods I think you're talking about - the use of instruction trained LLM models for coding - does not represent all the LLMs able to code. I will reference the work by [Deepmind with FunSearch](https://deepmind.google/discover/blog/funsearch-making-new-discoveries-in-mathematical-sciences-using-large-language-models/) that does not use instruction based models in this case and demonstrates to be useful in generating "new ideas". Although there's could also be ambiguity on that term too. Just curious what do you think about their work?  
  > **username_1**: Well I made a mistake - technically FunSearch uses things like StarCoder or Codey that are instruction LLM models for coding. But they could use a fully pretrained model and still I think my argument could remain. I said this because at least for me the pretrained model could be seen as a more creative autocompleter of text even though much of its generations doesn't make much sense.  
  > **username_0**: As a programmer I often peruse many many pages of potential solutions and quickly bypass things that are far too complex or off-track. Quite frequently I abstract ideas from entirely different scenarios to create a simple, concise, understandable, maintainable solution.  Even if AI could suggest things that are relevant, you still need knowledge and experience to select and adjust the code to fit the situation. Coding is not just sticking Lego together, it is more like surgery. I found the idea laughable in the article of having junior Lawyers use AI suggestions. And in court they'll flounder.  
  > **username_2**: This question needs work. It presupposes an answer to a question (can AI generate novel solutions to coding problems), then is half rant, half impossible question about non-specific "people". I suggest alter the question to be about coding capabilities of AI, around the original assumption. Also worth clarifying whether asking about LLMs, or current crop of code assistants. These are far from being all of AI around code generation, although they get a lot of attention currently, and presumably what triggered the question  
  > **username_0**: @NeilSlater thanks, I'll see what I can do.  
  > **username_3**: This is an interesting political/social question, but unfortunately it will only lead to opinions. My opinion is that people sometimes learn things too late or don't learn until they don't see the immediate effects, which may be too late to recover.  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_4 on 2024-01-11. Score: 2
  
  First of all, the statement *'it (AI) is an encyclopedia, not an expert'*, thus implies it cannot *'improve, use new techniques, tools, languages and so on'* is **wrong**. AI **can** discover new knowledge.
  
  Take the example of algorithm, which is the heart of programming. Do we agree that if someone invents a novel, effective algorithm, that makes him an expert?
  
  Then take a look at [this work](https://deepmind.google/discover/blog/discovering-novel-algorithms-with-alphatensor/), where AI taught us a new and better way to multiple two matrices. We human have been tackling this task for thousands of years and the latest improvement was made in 1969 (half a century back). **In writing better algorithm, AI can beat us to it**.
  
  In fact it is not at all surprising; years back, the infamous version of AlphaGo, the [AlphaGo Zero](https://deepmind.google/discover/blog/alphago-zero-starting-from-scratch/), which **uses no (zero, nil) human knowledge**, beat the whole mankind in the 3,000 years old game. In fact, it was discovered that if we incorporate human knowledge to the AI, its performance actually *worsens*. Human 'expertise' can be junk.
  
  If there is anything we human are better at: be humble and modest, realize and admit our limits, and always learn from those better than us.
  
  > **Comments:**
  > **username_0**: Ok, improving matrix multiplication by going from 80 multiples down to 76. With massive amounts of hardware and work. Reminds me of replacing a headphone wire with 2 complex transceivers (Bluetooth) and 2 computers, all to go the same 3 feet. Will we ever tire of ourselves?  
  > **username_5**: I couldn't read the linked article without creating an account, but OP mentions specifically "low performing employees". I suppose were are talking about programs like ChatGPT in this context, which is meant for the masses to generate answers "out of thin air". AlphaTensor and AlphaZero are in a totally different league, although they are good examples on how reinforcement learning can solve surprisingly difficult tasks. But those solutions are built by experts for experts.  
  > **username_0**: @NikoNyrh the AlphaGo idea of having the AI figure things out for itself seems reasonable. We could just chuck programming and have AlphaCode make up a whole new thing from scratch. Worth a try...  
  > **username_4**: @EdificialInelegance you missed the point completely - AI has made a **discovery**, a **new algorithm** which can do a calculation 10-20% more effective than we ever know. The "*massive amounts of hardware and work*" was to discover the algorithm, much like human spending a lifetime researching. **No effort is needed to enjoy the benefit**. I suggest you to take some time to re-read the article and think about the implication.  
  > **username_4**: @NikoNyrh If I read OP correctly, his point was "(because AI) **uses past information**... How can it help... to **improve**, use new techniques... and so on?" And my point is that 1: not all AI needs past (or more precisely, human's) information; 2: AI has shown that it can invent new techniques, tool, languages etc. which we never know nor imagined (recall the novel moves of Go, and the never-known matrix algorithm). Even we narrow down the scope to LLM, just like OP commented, what stops him to combine LLM with (say) AlphaCode, that can invent new algorithm per our request on-the-fly?  
  > **username_0**: So let it rip, discover away. Just don't include old rubbish in the setup conditions. **Garbage In, Garbage Out**  
  > **username_4**: @EdificialInelegance Yes, I long for the day where we ignorance people learn to step aside and let AI do the job. No more garbage from human's bias and prejudice. AlphaGo Zero already showed us how harmful human's garbage knowledge can be.  
  > **username_0**: "*'Tis a consummation devoutly to be wished.*"  
  > **username_4**: See, an encyclopedia using past info is talking. Can't produce new result though.  
  
  ---
  
  ### Answer by username_6 on 2024-01-11. Score: 1
  
  From what you write it seems that you believe that human new ideas are not based on past experience. This is an extremly bold statement very difficult to prove.
  Almost everybody would define a new idea idea of the connection of two previously unconnected dots. Ai can do that as much as we can.
  
  > **Comments:**
  > **username_0**: No, human new ideas are based only on experience. I think that AI is quite lacking in this area. Have you seen any AIs lately? What are they learning about a world of humans with needs and wants? Probably nothing. So why should we have them managing things for us?  
  
  ---
  
  