> Artificial intelligence systems found to Excel at imitation, but not innovation And they do it using the Microsoft spreadsheet software?
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Artificial intelligence systems found to excel at imitation, but not innovation
51–60 of 126 posts
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#52Well, you mean the systems designed to predict the next words based on analysis of the text they were feed excel at imitation?!
We have plenty of AIs designed to create new things. Those excel in creating new things. But they don't excel into bullshiting journalists into believing they are intelligent, so you don't hear about them.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#53Save you a click. According to the article all artificial intelligence are LLMs and the biased benchmark they used got a low score.
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Re: Artificial intelligence systems found to excel at imitation, but not innovation
#54As I see it the AI schism is more about the debate between functionalism/computationalism and the idea that the chinese room thought experiment was an argument for, "biological naturalism". There is a lot of effort dedicated to showing that AIs dont have some innate quality called "consciousnes" or "sentience" or what have you. There is not just a lot of effort to show that, but also to show that that is somehow a li…
Consciousness and sentience are just poorly defined vocabulary that delude people into thinking it's meaningful categorizations.
There's just a bunch of traits related to intelligence and we categorize that if something has enough of those traits then it's "alive". But the words "consciousness" and "sentience" are so poorly defined that we can't pinpoint the formal grouping of what these traits actually are. So for a person to be conscious one can say the person must have feelings, another definition could be no emotions needed but the ability to reason is required... Etc.. etc.
First up these definitions are just arbitrary categorizations. We each individually choose the traits that define the word consciousness, and second we don't even formalize the choice we sort leave the words impartially defined and all debates on whether LLMs are conscious are simply debating about this impartiality. It's a debate about a vocabulary issue for a word that isn't fully defined and people don't realize there's nothing profound or meaningful about the debate at all.
These words are everywhere in the English language and causes us to debate certain concepts as if it's meaningful without us realizing we are just debating a vocabulary problem.
Take for instance a car and a boat. These words are less fuzzy and more rigorously defined so debates on whether something is a car or a boat don't seem that profound. But the words are fuzzy enough that I can generate an example to help you see my point. Let's say I built something that can both drive and sail on the water. Is that thing a car or a boat? Is that question meaningful or is it just a categorization problem with inadequate vocabulary leaving me unable to specify exactly when an object classification transitions from boat to car? From this example it becomes evident that the debate is ludicrous that it's all an illusion. You are debating vocabulary.
For words that are more fuzzy the same problem exists. But it's harder to see that it's just a vocabulary problem because the words are so fuzzy.
Take for example, what is life? Is a bug alive? Is a plant? Or what is philosophy and what is not philosophy? Or what is good and what is evil? The discussion around all these issues are not profound. They are simply a discussion around vocabulary and categorization. We are too deluded by language to move past it.
Many concepts exist as a gradient and we are simply trying to discretize this gradient into fixed categories and then spending an endless amount of time debating on where the lines of demarcation goes.
So are LLMs conscious? It's loaded question. Let's not talk about vocabulary.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#55IMHO The perceived lack of creativity comes from their low fidelity access to the world. They are trained on text and images which loosely captures the world and then their output is also limited to text and images.
Once the machines have high fidelity connection to the world, for example a machine with microphone, camera and ways to manipulate objects resides among humans they will be actually trained and generate output on much higher spectrum.
Human's creativity comes from continuous observation as they mess with the world. Once the machine is in that position, I fully expect tho have human like and even beyond creativity.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#56Earlier quoted context omitted.
The very first python app I wrote was a statistical bard generator. I had python calculate word frequencies from a Shakespeare corpus and spit them back out with a probability distribution. Honestly it read just as well ;) We’re simpler than we imagine.
> We’re simpler than we imagine. Indeed, creativity (not just randomness) is a quite high bar, that I think even most humans don't pass. Most of us don't create a lot of new things and ideas in our daily lives. We mostly follow the steps of those that came before them, with small adjustments here and there.
Recombination makes dna and rna every day. Our limitation in seeing this is our short and fleeting lives.
There is a pub:grill in Tempe called monkeypants. Is that a new idea or just clever?
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#57How could a statistical system trained on data display intelligence let alone innovation? It's just very good statistics at the end of the day. Artificial Perception is about as far as you can get with ml/dl tech if you point the sensors at the world of space-time. If you point it at words, as with LLM, you get statistics about words - that is, no actual understanding of what the words model in the minds of the origi…
I'd argue that intelligence is precisely the ability to predict (and therefore also plan) outcomes based on prior experience. The ability to perceive and predict what happens next; the ability to predict/plan/act and be mostly correct about what you predicted would happen as a result of your actions.
With this definition, LLMs in their ability to predict can reasonably be considered to display some basic form of intelligence, even if only in their own world of words rather than the world at large. If we build embodied robots with a similar ability to predict, and also the ability to continually update their predictions based on prediction success/failure (the closed loop that is missing from LLMs), then we'll have something much more recognizably close to animal intelligence.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#58That's the PowerPoint of AI though... replacing all of the computer manual labor.
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#59Pardon my superficial understanding, but how'd it innovate if it tries to get the most probable result or energy-spending efficient result, which feels like the opposite of thinking out of the box?
Re: Artificial intelligence systems found to excel at imitation, but not innovation
#60Earlier quoted context omitted.
... and our judgments of composition favor recall over precision. Which is to say that as human judges we're good at finding sense in something generated if it's plausible. We'll take a proposition (eg in a composition) and construct a justification for it. "I can see how that makes sense". I am conflating plausible combination with high recall. Precision, in this sense, is that no proposition would be acceptable wit…
The very first python app I wrote was a statistical bard generator. I had python calculate word frequencies from a Shakespeare corpus and spit them back out with a probability distribution. Honestly it read just as well ;) We’re simpler than we imagine.
Btw Andrej Karpathy builds a Shakespeare LLM here: