Earlier quoted context omitted.
What a awful way to think about internship. The goal is to help people grow, so they can achieve things they would not have been able to deal with before gaining that additional experience. This might include boring dirty work, yes. But that means they thus prove they can overcome such a struggle, and so more experienced people should be expected to also be able to go though it - if there is no obvious more pleasant…
What an awful way to think about other people, always assuming the very worst version of what they said.
ChatGPT agent: bridging research and action
491–500 of 508 posts
Re: ChatGPT agent: bridging research and action
#492Earlier quoted context omitted.
>The cognitive burden is much lower when the AI can correctly do 90% of the work. Yes, the remaining 10% still takes effort, but your mind has more space for it. I think their point is that 10%, 1%, whatever %, the type of problem is a huge headache. In something like a complicated spreadsheet it can quickly become hours of looking for needles in the haystack, a search that wouldn't be necessary if AI didn't get it a…
I understand the idea. My position is that this is a largely speculative claim from people who have not spent much time seriously applying agents for spreadsheet or video editing work (since those agents didn’t even exist until now). “Getting something almost right, no matter how close, can often be worse than not doing it at all” - true with human employees and with low quality agents, but not necessarily true with…
Re: ChatGPT agent: bridging research and action
#493Earlier quoted context omitted.
Why would they want an LLM to slurp their web site to help some analyst create a report about the cost of widgets? If they value the data they can pay for it. If not, they don't need to slurp it, right? This goes for training data too.
The alternative is the AI only telling customers about competitors wares
Re: ChatGPT agent: bridging research and action
#494Earlier quoted context omitted.
Unless humans exceed the Turing computable, the human brain is the existence proof that a sufficiently complex Turing machine can be made to replicate human thought in a compact space. That encoding a naive/basic UTM in an LLM would potentially be impractical is largely irrelevant in that case, because for any UTM you can "compress" the program by increasing the number of states or symbols, and effectively "embedding…
You seem to be making a giant leap from “human thought can probably be emulated by a Turing machine” to “human thought can probably be emulated by LLMs in the actual physical universe.” The former is obvious, the latter I’m deeply skeptical of. The machine part of a Turing machine is simple. People manage to build them by accident. Programming language designers come up with a nice-sounding type inference feature and…
Current architectures may very well not be sufficient, but that is an entirely different issue.
Re: ChatGPT agent: bridging research and action
#495Earlier quoted context omitted.
The alternative is the AI only telling customers about competitors wares
That's for the publisher to decide. Your argument reminds me of the old chestnut "We're paying you in publicity!"
In the circumstances the merchant would be expecting to receive a valuable service and simultaneously get paid for getting serviced.
More akin to Google paying to index you or going to a lady of the evening and holding your hand out for a tip after.
Re: ChatGPT agent: bridging research and action
#496The "spreadsheet" example video is kind of funny: guy talks about how it normally takes him 4 to 8 hours to put together complicated, data-heavy reports. Now he fires off an agent request, goes to walk his dog, and comes back to a downloadable spreadsheet of dense data, which he pulls up and says "I think it got 98% of the information correct... I just needed to copy / paste a few things. If it can do 90 - 95% of the…
> how it normally takes him 4 to 8 hours to put together complicated, data-heavy reports. Now he fires off an agent request, goes to walk his dog, and comes back to a downloadable spreadsheet of dense data, which he pulls up and says "I think it got 98% of the information correct... This is where the AI hype bites people. A great use of AI in this situation would be to automate the collection and checking of data. Se…
Why would you need ai for that though? Pull your sources. Run a diff. Straight to the known truth without the chatgpt subscription. In fact by that point you don’t even need the diff if you pulled from the sources. Just drop into the spreadsheet at that point.
Re: ChatGPT agent: bridging research and action
#497Earlier quoted context omitted.
> said we'd have self driving cars "in a few years" back in 2015 And they wouldn't have been too far off! Waymo became L4 self-driving in 2021, and has been transporting people in the SF Bay Area without human supervision ever since. There are still barriers — cost, policies, trust — but the technology certainly is here.
People were saying we would all be getting in our cars and taking a nap on our morning commute. We are clearly still a pretty long ways off from self-driving being as ubiquitous as it was claimed it would be.
Re: ChatGPT agent: bridging research and action
#498Earlier quoted context omitted.
You seem to be making a giant leap from “human thought can probably be emulated by a Turing machine” to “human thought can probably be emulated by LLMs in the actual physical universe.” The former is obvious, the latter I’m deeply skeptical of. The machine part of a Turing machine is simple. People manage to build them by accident. Programming language designers come up with a nice-sounding type inference feature and…
I'm not making a leap there at all. Assuming we agree the brain is unlikely to exceed the Turing computable, I explained the stepwise reasoning justifying it: Given Turing equivalence, and given that for each given UTM, there is a bigger UTM that can express programs in the simpler one in less space, and given that the brain is an existence-proof that a sufficiently compact UTM is possible, it is preposterous to thin…
This is where it goes wrong. You’ve got the implication backwards. The existence of a program and a physical computer that can run it to produce a certain behavior is proof that such behavior can be done with a physical system. (After all, that computer and program are themselves a physical system.) But the existence of a physical system does not imply that there can be an actual physical computer that can run a program that replicates the behavior. If the laws of physics are computable (as they seem to be) then the existence of a system implies that there exists some Turing machine that can replicate the behavior, but this is “exists” in the mathematical sense, it’s very different from saying such a Turing machine could be constructed in this universe.
Forget about intelligence for a moment. Consider a glass of water. Can the behavior of a glass of water be predicted by a physical computer? That depends on what you consider to be “behavior.” The basic heat exchange can be reasonably approximated with a small program that would trivially run on a two-cent microcontroller. The motion of the fluid could be reasonably simulated with, say, 100-micron accuracy, on a computer you could buy today. 1-micron accuracy might be infeasible with current technology but is likely physically possible.
What if I want absolute fidelity? Thermodynamics and fluid mechanics are shortcuts that give you bulk behaviors. I want a full quantum mechanical simulation of every single fundamental particle in the glass, no shortcuts. This can definitely be computed with a Turing machine, and I’m confident that there’s no way it can come anywhere close to being computed on any actual physical manifestation of a Turing machine, given that the state of the art for such simulations is a handful of particles and the complexity is exponential in the number of particles.
And yet there obviously exists a physical system that can do this: the glass of water itself.
Things that are true or at least very likely: the brain exists, physics is probably computable, there exists (in the mathematical sense) a Turing machine that can emulate the brain.
Very much unproven and, as far as I can tell, no particular reason to believe they’re true: the brain can be emulated with a physical Turing-like computer, this computer is something humans could conceivably build at some point, the brain can be emulated with a neural network trained with gradient descent on a large corpus of token sequences, the brain can be emulated with such a network running on a computer humans could conceivably build. Talking about the computability of the human brain does nothing to demonstrate any of these.
I think non-biological machines with human-equivalent intelligence are likely to be physically possible. I think there’s a good chance that it will require specialized hardware that can’t be practically done with a standard “execute this sequence of simple instructions” computer. And if it can be done with a standard computer, I think there’s a very good chance that it can’t be done with LLMs.
Re: ChatGPT agent: bridging research and action
#499Earlier quoted context omitted.
That's for the publisher to decide. Your argument reminds me of the old chestnut "We're paying you in publicity!"
In your example the person is receiving something of tangible value and expecting to pay in near worthless coin. In the circumstances the merchant would be expecting to receive a valuable service and simultaneously get paid for getting serviced. More akin to Google paying to index you or going to a lady of the evening and holding your hand out for a tip after.
Re: ChatGPT agent: bridging research and action
#500Earlier quoted context omitted.
I’m rejecting the assertion that the data covers a physics model - which would be invariant across nations. I’m positing that the models encode cultural decision making norms- and using global south regions to highlight examples of cases that are commonplace but challenge the feasibility of full autonomous driving. Imagine an auto rickshaw with full self driving. If in your imagination, you can see a level 5 auto, jo…
You're not wrong on the "physics easy culture hard" call, just late. That was Andrej Karpathy's stated reason for betting on the Tesla approach over the Waymo approach back in 2017, because he identified that the limiting factor would be the collection of data on real-world driving interactions in diverse environments to allow learning theories-of-mind for all actors across all settings and cultures. Putting cameras…
I liked the use of the God of the gaps - an effective analogy for the counter position.
I’m rejecting the idea of the march of the 9s eventually getting to FSD - the cultural norms issue is about decision making not about physics.
Eg - You have to decide how aggressively to drive, overtake, or jockey for position.
My estimation is that this is not solvable by on board decision making, because that would be accepting unacceptable legal risk.