It seems perfectly simple to measure, and they just need to contain at least that much, so companies would overshoot by a bit to make sure.
If a company claims it contains a litre, and a customer sues, all the company has to do is bring one to court. And have a representative get a litre out in a way that seems reasonable to the judge.
Small correction: Jordan was not involved in the 1973 war.
I think perhaps a more useful, less subjective definition of AGI is something along the line of:
Can perform most jobs that are:
fully remote
any average human can be trained to do
can communicate by email or text, doesn’t require voice/video calls
Because if it really was generally intelligent why can’t it do that job?
Overall I appreciate what you’re trying to do here, but it’s not convincing.
The biggest problems are in this section:
The first is the machine itself. It is a computational device with audiovisual output. That implies its creators have sensory apparatus that processes both. They see. They hear.
Atmosphere dense enough for pressure wave propagation. Bilateral body plans with clustered sensory organs.
The machine has no idea that light or sounds exist. All it knows is that there’s two forms of output—both of which are interpretable to it. The evidence points equally strongly to creators running in Conway’s game of life as it does to ones in our universe.
You give as an example a situation which is inherently not repeatable, where were forced to make do with reasoning under significant uncertainty and with very limited information, to decide what’s going on out of an incredibly wide hypothesis space. You correctly point out this is hard.
You then say that in a situation where we can perform repeated experiments to exclude one hypothesis P-values work ok.
But in that exact situation Bayesian reasoning works fine. Sure you might not agree on which alternative hypothesis is true but so long as both of you agree there are any alternative hypothesese that make it more likely to see the given results, after a few rounds you’ll have extremely low credence in the original hypothesis.
What does it mean to raise the temperature by a fixed amount before we’ve defined temperature?
Without having read the book, or knowing the history of temperature, an obvious property I’d want my scale of temperature to have is that the temperature of a mixture of identical substances at different temperatures is the weighted average of the constituent parts.
Then you can easily recreate the celcius scale. Let the temperature of freezing water be 0, and the temperature of boiling water be 100.
Mix 99 parts freezing water with one part boiling water, and mix well (and quickly, in an insulated environment). That’s 1 degree celcius.
Repeat for the other 98 combinations.
If we’re lucky the mercury in our thermometer moves up a constant amount each time, and we can avoid mixing things to calibrate our thermometer in the future. If we’re unlucky it doesn’t and we need to painstakingly calibrate all thermometers. If we’re really unlucky a scale that works on one substance doesn’t work on another and then we need to rethink this whole temperature thing again.
Is this standard for the MBTI?
The test we used did, I have very little further knowledge of the MBTI other than what was discussed on this course.
That assumes you’re in a better position to make such investments than the charity?
It’s a good metaphor, but I think one important aspect this misses is overfitting—when you have a lot of parameters the NN can literally memorise small training sets till it gets 100% on the training set and 0% on the test set. Whereas a smaller model is forced to learn the underlying structure, so generalises better.
Hence larger models need a much larger training set even to match smaller models, which is another disadvantage of larger models (besides for higher per token training and inference costs).
Ok, in that case you’re just basically referring to the SSA Vs SIA. That’s an old chestnut, and either way leads to seemingly paradoxical results.
Yes
In universalism the question is then why out of all the parts of the consciousness I could happen to be experiencing, I’m experiencing this particular part.
There is no other deck of cards here. There’s no copy of me to compare myself to, and say how curious that looks exactly like me.
That’s like saying that every game of cards must be rigged, because otherwise the chance of having this particular card order is miniscule...
Do we have the numbers?
what percentage of anthropic shares are owned by employees?
Of those what percentage are owned by EA pulled employees?
Of those how many which actually translate their words into actions once they have the money?
What percentage do we expect them to give, and over what time frame?
How does that compare to current EA related funding?
Making up random numbers (I’ve done zero research)
Not more than 50 billion owned by employeess
Not more than 20 billion owned by EA employees
75% will put their money where their mouth is
And donate 50%. If they spread that over 20 years, at current interest rates that’s about 500 million a year
Givewell raised 400 million last year. Not all of that is from EAs, but not all EAs donated there. Let’s say total of 500 million.
Then if this all happens it about doubles fundings for EA related causes. Is a reasonable chance of that happening worth upfronting donations for?
Fair enough. I found it unreadable in a way I associate with AI (lots of dense words, but tricky to extract the content out of them), and the em dashes are somewhat of a giveaway.
Given how much slop there is I do appreciate if people clarify what they used AI for because I don’t want to wade through a ton of slop which wasn’t even human written.
Thanks for replying.
Hi, was this post written by, or with assistance from, AI?
Thanks
That could be argued about every single thing in law, yet law continues to work.