why do you use the term superintelligence
I'm afraid I had to come to the conclusion that LLMs, although being fun to play around with sometimes and seeming surprising at first, it's a similar kind of fun and surprise to sleight-of-hand. Like sleight-of-hand, and unlike real general intelligences (i.e. other people), it seems less and less fun and surprising the more exposed to it I become.
I guess this won't change your mind though. Maybe you've understood more about them than I have, and maybe I'm just grumpy and cynical.
But when I saw one in person, I was disappointed. I saw no flapping. I saw no feathers.
Sure I saw it soar through the clouds but that's just sleight of hand I'm sure. A trick. Planes surely do not fly.
I didn't say that I had only "heard about" LLMs. I said I played around with them.
If you were being faithful to what I wrote, you would take in the full thing, including the part about how LLMs become less fun and surprising the more you play with them.
Planes do not fly less effectively the more experienced you become at piloting them.
So I can only conclude that you did not come here to have a discussion in good faith. So what are you really after? Do you think you'll change my mind with your poetry?
The situation is even worse than my story outlined because you understand neither the workings of the brain and how it is intelligent nor what the computation that preceeded a prediction of a language model represents.
You don't know x and you don't y but you are convinced x=/y.
>the part about how LLMs become less fun and surprising the more you play with them.
Do they ? I don't think so.
>Planes do not fly less effectively the more experienced you become at piloting them.
How well a plane flies is an objective measure. How "fun" and "surprising" something is is largely subjective and can change on grounds that have nothing to do with what is being evaluated.
Your refutation boils down to "It's just linear algebra!".
Setting aside the fact that you can be reductionist about anything including biology, Okay? So what?
Results matter not vague and meaningless philosophical ramblings.
There isn't a testable definition of general intelligence that GPT-4 fails that a chunk of humans also wouldn't.
If they fall short then so do people. Guess those people aren't generally intelligent then according to you.
>It can't tell the difference between truth and falsity
Yes, it very much can.
GPT-4 logits calibration pre RLHF - https://imgur.com/a/3gYel9r
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback - https://arxiv.org/abs/2305.14975
Teaching Models to Express Their Uncertainty in Words - https://arxiv.org/abs/2205.14334
Language Models (Mostly) Know What They Know - https://arxiv.org/abs/2207.05221
The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets - https://arxiv.org/abs/2310.06824
>The more interesting question is why are people like you personally offended
I'm not offended about anything.
Sure there is and it's a basic one: can it determine a fact?
LLMs cannot do first-principles reasoning well (unless it has seen the pattern before), but they excel at reasoning through analogy.
And guess what? Most humans reason analogically too. Analogical reasoning -- as opposed to first principles reasoning -- is actually more effective and useful in many situations, especially in ill-defined domains. Humans often think, "this situation looks like something that I've seen before, so I can apply my past knowledge but with a few tweaks."
That's a big part of the problem, people thinking imprecisely and using "AGI" and "ASI" interchangeably.
What sets humans apart from AI right now, is specific types of out-of-the-box thinking.
Let's say there's a bridge, an AI gets to control a robot, and is awarded points for crossing that bridge.
I think you can be pretty sure that over time, the AI will figure out how to control the robot's limbs, move toward opposite side of the bridge, and find its way around obstacles.
Meanwhile, humans may walk back & forth, because they enjoy crossing the bridge. Or stand in the middle for an hour, watching boats pass underneath. Some asshats may climb it. On a hot sunny day, others may go halfway & then jump off for a refreshing swim. Yet others may do some protest, and use the bridge as a scaffold to hang a banner from. Etc etc.
Much such behavior defies logic. But yet, the bridge will primarily be used as intended, to cross from side to side. And humans go about in this fashion in many if not all their activities.
When I see AIs that show similar creative / out-of-box behavior, while remaining mostly goal-oriented, and learn from its mistakes without humans nudging it every step of the way, then I think we'll have achieved AGI.
Beyond that, SI is just a matter of scale & efficiency.
Yeah that's not the reason at all.
GPT-4 logits calibration pre RLHF - https://imgur.com/a/3gYel9r
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback - https://arxiv.org/abs/2305.14975
Teaching Models to Express Their Uncertainty in Words - https://arxiv.org/abs/2205.14334
Language Models (Mostly) Know What They Know - https://arxiv.org/abs/2207.05221
The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False Datasets - https://arxiv.org/abs/2310.06824
When there is enough evidence corporate wonderland is overflowing with one dimensional intelligence cause their goals and what gets rewarded is extremely narrow.
Einstein and Newton will fail the test 100%.