5 ms·

As someone who works in IT for 20 years but has a bachelor in economic psychology, i do believe that we have not solved AGI yet because the creators of the mode

As someone who works in IT for 20 years but has a bachelor in economic psychology, i do believe that we have not solved AGI yet because the creators of the models have the generalized view of the universe that you are "one person" and there are just so many detailed facets to that. Basically the assumption is that if you cram enough data into your gpt model, it should know everything. Which is of course not true, it repeats the things it reads the most with a probability. Basically how there are two versions of smart teens, the ones who learn every day and the ones who just pick up concepts on the fly and run with them. I think the first space has been explored plenty, for the second one I have a concept ready and dearly hope that power gets cheaper in europe ;)

igleria 4y ago
> power gets cheaper in europe Have you heard about our lord and saviour dynamic tariffs?
- raverbashing 4y ago
  What about it? Dynamic tariffs -> shift your workload to the cheapest times AIs are good at planning this Imagine if cloud providers had a "Dynamic tariff" tier, cheaper to run computing at US_EAST nighttime or something like that
  - jhoelzel 4y ago
    i think that was what he was trying to imply and the fact that you just cant "pause" training by putting your computer into hybernate mode is also present =)
JKCalhoun 4y ago
Street-smart AI.
- jhoelzel 4y ago
  well yes and no. This AI would be more street-smart than GPT but only because it would grasp the concept of what "danger" actually is! I think of it more in a way that learning is more abstract than fact learning. From experience, we think that there are fact learners and principle learners but there are also a mixtures of the two! The general accepted model entails that in order to do high level math, for instance, you need to understand the basics, but for me much of those concept actually clicked in college. This did not stop me from applying them with success a lot earlier though. For instance multiplication in Kindergarten is fact learning too! In Germany we also have the term "Fachidioten", which loosely translates to people that are so smart in their field, that they are unable to see problems from different directions. This is more of less what i think a mega gtp model turns into. especially because of selection bias in the training data. Validity of output (truth) can only be achieved through the trust of the source which is always relative to the context of the topic. Henceforth a selectively trained model will always return the data you feed it including all biases. Even if you have it crawl all of the internet and the library of Alexandria and every written word on the planed you can find, it will still return to you the general accepted consensus.
lostmsu 4y ago
> Basically the assumption is that if you cram enough data into your gpt model, it should know everything. Which is of course not true, it repeats the things it reads the most with a probability. That's only how the system was designed intentionally. E.g. there's intentionally no self-feedback loop.
- jhoelzel 4y ago
  so we are both agreeing on the same thing? :D
  - lostmsu 4y ago
    Conceptually, no. For me your statement sounds like it says we did not solve flight, because our planes have to land.
    - jhoelzel 4y ago
      Well I am in fact trying to argue that the self feedback loop is what is missing to solve AGI and even more so implying that the reason for that may be that there are different ways to see a "human" psychologically. Also that validity in data can only be achieved using a multi modal approach with source ranking. Psychology essentially has the same problem and is only a "science" where reproducible. Quantitative and Qualitative psychology have 2 approaches to the same solution whereas the latter is "reading between the lines" and the former is "bean counting", meaning statistical interference. I am trying to say that friend of mine has created "Chicken Infinite" in 2014, which is basically an endless auto generated cooking book. Deep-L has also been around for a while. These applications lead me to believe that text applications, trained on a large dataset do not have to be this intensive. Furthermore what makes chatgpt enticing, is its chat interface which is using a multi model approach too. Have it create a detailed story for you with multiple prompts and then ask it to generate the prompt to generate this story and you will see various model instructions. (or at least you could last month). Or differently put, there is no AGI because the understanding function is simply not present and i think that the reasoning for that is buried in the approach of the human mind.

igleria 4y ago

> power gets cheaper in europe Have you heard about our lord and saviour dynamic tariffs?

raverbashing 4y ago
What about it? Dynamic tariffs -> shift your workload to the cheapest times AIs are good at planning this Imagine if cloud providers had a "Dynamic tariff" tier, cheaper to run computing at US_EAST nighttime or something like that
- jhoelzel 4y ago
  i think that was what he was trying to imply and the fact that you just cant "pause" training by putting your computer into hybernate mode is also present =)

JKCalhoun 4y ago

Street-smart AI.

jhoelzel 4y ago
well yes and no. This AI would be more street-smart than GPT but only because it would grasp the concept of what "danger" actually is! I think of it more in a way that learning is more abstract than fact learning. From experience, we think that there are fact learners and principle learners but there are also a mixtures of the two! The general accepted model entails that in order to do high level math, for instance, you need to understand the basics, but for me much of those concept actually clicked in college. This did not stop me from applying them with success a lot earlier though. For instance multiplication in Kindergarten is fact learning too! In Germany we also have the term "Fachidioten", which loosely translates to people that are so smart in their field, that they are unable to see problems from different directions. This is more of less what i think a mega gtp model turns into. especially because of selection bias in the training data. Validity of output (truth) can only be achieved through the trust of the source which is always relative to the context of the topic. Henceforth a selectively trained model will always return the data you feed it including all biases. Even if you have it crawl all of the internet and the library of Alexandria and every written word on the planed you can find, it will still return to you the general accepted consensus.

lostmsu 4y ago

> Basically the assumption is that if you cram enough data into your gpt model, it should know everything. Which is of course not true, it repeats the things it reads the most with a probability. That's only how the system was designed intentionally. E.g. there's intentionally no self-feedback loop.

jhoelzel 4y ago
so we are both agreeing on the same thing? :D
- lostmsu 4y ago
  Conceptually, no. For me your statement sounds like it says we did not solve flight, because our planes have to land.
  - jhoelzel 4y ago
    Well I am in fact trying to argue that the self feedback loop is what is missing to solve AGI and even more so implying that the reason for that may be that there are different ways to see a "human" psychologically. Also that validity in data can only be achieved using a multi modal approach with source ranking. Psychology essentially has the same problem and is only a "science" where reproducible. Quantitative and Qualitative psychology have 2 approaches to the same solution whereas the latter is "reading between the lines" and the former is "bean counting", meaning statistical interference. I am trying to say that friend of mine has created "Chicken Infinite" in 2014, which is basically an endless auto generated cooking book. Deep-L has also been around for a while. These applications lead me to believe that text applications, trained on a large dataset do not have to be this intensive. Furthermore what makes chatgpt enticing, is its chat interface which is using a multi model approach too. Have it create a detailed story for you with multiple prompts and then ask it to generate the prompt to generate this story and you will see various model instructions. (or at least you could last month). Or differently put, there is no AGI because the understanding function is simply not present and i think that the reasoning for that is buried in the approach of the human mind.