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Throughout history there are moments where humans realize they're not special in a way they previously thought they were — universe doesn't revolve around us, o

by gdubs 4y ago

Throughout history there are moments where humans realize they're not special in a way they previously thought they were — universe doesn't revolve around us, other animals possess skills we thought were unique to us, etc. I think what's interesting is that many types of creativity may really just be re-synthesizing "stuff we already know." So a lot of the negative comments along the lines of, "it can't be creative because it never thinks of anything beyond its training data" don't click with me. I think synthesizing two existing concepts into some third thing is actually a form of creativity. These nets may not learn the same way we do exactly, and they may not possess the same creative abilities as us — but there's definitely something interesting going on. I for one am taking a Beginner's Mind view of it all. It's pretty fascinating.

xiphias2 4y ago
I wish the negative comments were right, but from these models it’s clear that the next step in evolution, AGI is something many of us will experience at some time in the future. I would stop that kind of evolution, as it can be catastrophic, but I know that humanity is not able to stop itself from evolving further.
- avereveard 4y ago
  Idk while gpt is impressive I haven't seen any inductive reasoning coming out of it. And even then for proper agi it would need to close the loop after inducing an hypothesis with testing. Meatbags are going to be useful for a while still.
  - zarzavat 4y ago
    What do you mean exactly by inductive reasoning? It can translate code from one language to another. Code that it has never seen before. Or between natural language and programming language. It's certainly not perfect but it is reasoning all right
- dinkumthinkum 4y ago
  I don’t think anyone had demonstrated AGI is a foregone conclusion. I’m not sure it is possible with a Turing machine. We do not think in any manner like a Turing machine or any computer ever conceived. If we do, no one has provided any evidence of such a claim. Humans can make complex insights with hardly any training and on very few calories.
  - zadler 4y ago
    One day, there could be a telephone in every town
  - virgildotcodes 4y ago
    How do you figure regarding hardly any training? Humans are constantly training on a never ending stream of sensory information from the time their brains form in the womb, not to mention whatever subconscious and conscious processes are reconciling that data with memory, or whatever training has been built into our minds over eons of evolution. An 18 year old will have been training for ~160,000 hours on a volume of raw data that is probably far beyond our ability to currently store let alone train an AI with. As far as training for a specific task, all that training on other matters kicks in to help the human learn or accomplish a “novel” task more rapidly, for example, knowing how to read and interpret the instructions for that task, knowing how to move your appendages and the expected consequences of your physical interactions with a material object. You’re certainly not taking a fetus with a blank slate and getting it to accomplish much at all.
    - dinkumthinkum 4y ago
      It absolutely is hardly any training for the types of problems humans have solved. Ramanujan did not need to consume the entire corpus of mathematics or even had much formal education whatsoever. He did so, again, on very few calories compared to pre-trained AI models. I am not claiming learning how to pick up a rock does not help you in any way to understand continued fractions but it is pretty unreasonably to compare an AI as has been demonstrated as being anywhere near the same sort of thing.
  - 4y ago
frebord 4y ago
Just about human intelligence in general. I used to think replacing my software job was a long ways off because it is fairly intellectually challenging but chatgpt has really changed my opinion on that. Its funny how many people will immediately poke holes in it for software development, but two years ago I could not imagine an AI could write code like chatgpt is doing now.
- pydry 4y ago
  The challenge isnt writing code. It is writing code that is relatively free of defects. It falls down hard on that point.
  - fsflover 4y ago
    Sounds similar to the arguments against self-driving: "Self-driving itself isn't the challenge. It is self-driving better than humans". AFAIK this is already possible at least under certain conditions or at certain roads.
  - Hedepig 4y ago
    Do you believe we're at the peak of what will be capable? As shown by this post, we're still discovering what's possible with the tools we have now. Also, human programmers aren't amazing at writing defect free code.
  - pmontra 4y ago
    Free of defects is the least of the problems. Doing what a customer wants is the major one. One could argue that customers will be able to write their code alone but they'll always have something else to do and will pay somebody to do it, exactly as for all the other parts of their business. On the other side maybe one wouldn't have to know one of the current programming languages, much like we don't have to know machine code nowadays. English and a good dose of perseverance could be enough.
- moffkalast 4y ago
  Yeah I now routinely ask it for boilerplate to get things done way faster and it's REALLY good at flawlessly translating from one programming language to another. It'll be a shame when it goes behind a paywall. On that thought, does anyone even still use Copilot?
inthepipe 4y ago
> I think what's interesting is that many types of creativity may really just be re-synthesizing "stuff we already know." This is obviously true, and yet we've invented so many things. From the wheel, to control of fire, to farming and animal husbandry, to mathematics, to metallurgy, to physics, to semiconductors, etc. The interesting question is, was the invention of all those things simply the re-synthesis of "stuff we already know?" If the answer is yes, doesn't that mean we're now on the cusp of a something akin to a singularity? We can now synthesize nearly-unlimited streams of coherent human thought. If we had a way of differentiating the wheat from the chaff, we could analyze what would have been millennia of human output in the proverbial blink of an eye. If human knowledge is just "stuff we already know", then we better buckle up. It's about to be a wild ride.
- visarga 4y ago
  > If we had a way of differentiating the wheat from the chaff This is the key to AGI. We need verification systems, they can be a code execution environment, a database of facts, a math symbolic engine, a physical simulation, a game, or real world lab experiments. These verifiers will produce signal that can be used by the language models to improve. The cheaper and faster verification is, the faster we can iterate. Generating ideas is cheap, proof matters. Just remember AlphaZero a bit - it started from scratch, playing against itself, in a few hours it surpassed human level. Go simulation and verification is trivial. The board is just a matrix. So learning from massive search and verification is a proven path to super-human level. Here is a related paper: > Evolution through Large Models https://arxiv.org/abs/2206.08896 https://arxiv.org/abs/2206.08896
  - inthepipe 4y ago
    Proof definitely matters. But at this point, as ChatGPT, AlphaZero, and others demonstrate, NNs can solve any problem provided you can express the problem as a differentiable function and get enough training data to train the function. We may be very close to a breakthrough where we can train models that detect sound, good ideas. And 100% accuracy likely isn’t necessary. Even pruning the search space for good ideas by a large amount would make humans way more productive.
visarga 4y ago
> I think synthesizing two existing concepts into some third thing is actually a form of creativity. And the space is combinatorial. Most of it is unexplored. It is creativity, but also a form of search.
sharemywin 4y ago
Especially since there are very few people that can actually be 100% creative. Most human creativity is derivative. I didn't invent a new language I learned English. If you think about it the most creative is random noise. then you apply rules it it to constrain the noise or limit the predictions. And add more rules in layers. so getting the system to produce more creativity is just relaxing the rules at different layers.

by gdubs 4y ago

xiphias2 4y ago

I wish the negative comments were right, but from these models it’s clear that the next step in evolution, AGI is something many of us will experience at some time in the future. I would stop that kind of evolution, as it can be catastrophic, but I know that humanity is not able to stop itself from evolving further.

avereveard 4y ago
Idk while gpt is impressive I haven't seen any inductive reasoning coming out of it. And even then for proper agi it would need to close the loop after inducing an hypothesis with testing. Meatbags are going to be useful for a while still.
- zarzavat 4y ago
  What do you mean exactly by inductive reasoning? It can translate code from one language to another. Code that it has never seen before. Or between natural language and programming language. It's certainly not perfect but it is reasoning all right
dinkumthinkum 4y ago
I don’t think anyone had demonstrated AGI is a foregone conclusion. I’m not sure it is possible with a Turing machine. We do not think in any manner like a Turing machine or any computer ever conceived. If we do, no one has provided any evidence of such a claim. Humans can make complex insights with hardly any training and on very few calories.
- zadler 4y ago
  One day, there could be a telephone in every town
- virgildotcodes 4y ago
  How do you figure regarding hardly any training? Humans are constantly training on a never ending stream of sensory information from the time their brains form in the womb, not to mention whatever subconscious and conscious processes are reconciling that data with memory, or whatever training has been built into our minds over eons of evolution. An 18 year old will have been training for ~160,000 hours on a volume of raw data that is probably far beyond our ability to currently store let alone train an AI with. As far as training for a specific task, all that training on other matters kicks in to help the human learn or accomplish a “novel” task more rapidly, for example, knowing how to read and interpret the instructions for that task, knowing how to move your appendages and the expected consequences of your physical interactions with a material object. You’re certainly not taking a fetus with a blank slate and getting it to accomplish much at all.
  - dinkumthinkum 4y ago
    It absolutely is hardly any training for the types of problems humans have solved. Ramanujan did not need to consume the entire corpus of mathematics or even had much formal education whatsoever. He did so, again, on very few calories compared to pre-trained AI models. I am not claiming learning how to pick up a rock does not help you in any way to understand continued fractions but it is pretty unreasonably to compare an AI as has been demonstrated as being anywhere near the same sort of thing.
- 4y ago

frebord 4y ago

Just about human intelligence in general. I used to think replacing my software job was a long ways off because it is fairly intellectually challenging but chatgpt has really changed my opinion on that. Its funny how many people will immediately poke holes in it for software development, but two years ago I could not imagine an AI could write code like chatgpt is doing now.

pydry 4y ago
The challenge isnt writing code. It is writing code that is relatively free of defects. It falls down hard on that point.
- fsflover 4y ago
  Sounds similar to the arguments against self-driving: "Self-driving itself isn't the challenge. It is self-driving better than humans". AFAIK this is already possible at least under certain conditions or at certain roads.
- Hedepig 4y ago
  Do you believe we're at the peak of what will be capable? As shown by this post, we're still discovering what's possible with the tools we have now. Also, human programmers aren't amazing at writing defect free code.
- pmontra 4y ago
  Free of defects is the least of the problems. Doing what a customer wants is the major one. One could argue that customers will be able to write their code alone but they'll always have something else to do and will pay somebody to do it, exactly as for all the other parts of their business. On the other side maybe one wouldn't have to know one of the current programming languages, much like we don't have to know machine code nowadays. English and a good dose of perseverance could be enough.
moffkalast 4y ago
Yeah I now routinely ask it for boilerplate to get things done way faster and it's REALLY good at flawlessly translating from one programming language to another. It'll be a shame when it goes behind a paywall. On that thought, does anyone even still use Copilot?

inthepipe 4y ago

> I think what's interesting is that many types of creativity may really just be re-synthesizing "stuff we already know." This is obviously true, and yet we've invented so many things. From the wheel, to control of fire, to farming and animal husbandry, to mathematics, to metallurgy, to physics, to semiconductors, etc. The interesting question is, was the invention of all those things simply the re-synthesis of "stuff we already know?" If the answer is yes, doesn't that mean we're now on the cusp of a something akin to a singularity? We can now synthesize nearly-unlimited streams of coherent human thought. If we had a way of differentiating the wheat from the chaff, we could analyze what would have been millennia of human output in the proverbial blink of an eye. If human knowledge is just "stuff we already know", then we better buckle up. It's about to be a wild ride.

visarga 4y ago
> If we had a way of differentiating the wheat from the chaff This is the key to AGI. We need verification systems, they can be a code execution environment, a database of facts, a math symbolic engine, a physical simulation, a game, or real world lab experiments. These verifiers will produce signal that can be used by the language models to improve. The cheaper and faster verification is, the faster we can iterate. Generating ideas is cheap, proof matters. Just remember AlphaZero a bit - it started from scratch, playing against itself, in a few hours it surpassed human level. Go simulation and verification is trivial. The board is just a matrix. So learning from massive search and verification is a proven path to super-human level. Here is a related paper: > Evolution through Large Models https://arxiv.org/abs/2206.08896 https://arxiv.org/abs/2206.08896
- inthepipe 4y ago
  Proof definitely matters. But at this point, as ChatGPT, AlphaZero, and others demonstrate, NNs can solve any problem provided you can express the problem as a differentiable function and get enough training data to train the function. We may be very close to a breakthrough where we can train models that detect sound, good ideas. And 100% accuracy likely isn’t necessary. Even pruning the search space for good ideas by a large amount would make humans way more productive.

visarga 4y ago

> I think synthesizing two existing concepts into some third thing is actually a form of creativity. And the space is combinatorial. Most of it is unexplored. It is creativity, but also a form of search.

sharemywin 4y ago

Especially since there are very few people that can actually be 100% creative. Most human creativity is derivative. I didn't invent a new language I learned English. If you think about it the most creative is random noise. then you apply rules it it to constrain the noise or limit the predictions. And add more rules in layers. so getting the system to produce more creativity is just relaxing the rules at different layers.