Shortform Content
I did an ADHD test in Germany. They asked me questions at 1:30 and then said I have ADHD, and no further testing was required. If the interview had not been conclusive they would have done some other tests. They ask about symptoms like "Can you not sit still", "Do you forget appointments" and things like that.
The most interesting part was the preinterview part.
Scott writes here on how psychiatrists are the gatekeepers to Adderall:
...Aren’t psychiatrists creepy wizards who can see through your deceptions? There are people like that. They’re call
How many real numbers can be defined?
On one hand, there are countably many definitions. Each definition can be written on computer in a text file; now take its binary form as a base-256 integer.
On the other hand, Cantor's diagonal argument applies here, too. I mean, for any countable list of definable real numbers, it provides a definition of a real number that is not included in the list.
Funny, isn't it?
(solution)
Fractal Fuzz: making up for size
GPT-3 recognizes 50k possible tokens. For a 1000 token context window that means there are possible prompts. Astronomically large. If we assume the output of a single run of gpt is 200 tokens then for each possible prompt there are possible continuations.
GPT-3 is probabilistic, defining for each possible prompt () a distribution on a set of size , in other words a dimensional space. [1]
Mind-boggingly large...
Imagine if a magic spell was cast long ago, that made it so that rockets would never explode. Instead, whenever they would explode, a demon would intervene to hold the craft together, patch the problem, and keep it on course. But the demon would exact a price: Whichever humans were in the vicinity of the rocket lose their souls, and become possessed. The demons possessing them work towards the master plan of enslaving all humanity; therefore, they typically pretend that nothing has gone wrong and act normal, just like the human whose skin they wear would h...
2I've had success with something: meal prepping a bunch of food and freezing it.
I want to write a blog post about it -- describing what I've done, discussing it, and recommending it as something that will quite likely be worthwhile for others as well -- but I don't think I'm ready. I did one round of prep that lasted three weeks or so and was a huge success for me, but I don't think that's quite enough "contact with reality". I think there's a risk that, after more "contact with reality", it proves to be not nearly as useful as it currently seems. So yeah, ...
Since there are basically no alignment plans/directions that I think are very likely to succeed, and adding "of course, this will most likely not solve alignment and then we all die, but it's still worth trying" to every sentence is low information and also actively bad for motivation, I've basically recalibrated my enthusiasm to be centered around "does this at least try to solve a substantial part of the real problem as I see it". For me at least this is the most productive mindset for me to be in, but I'm slightly worried people might confuse this for ...
SLT and phase transitions
The morphogenetic SLT story says that during training the Bayesian posterior concentrates around a series of subspaces with rlcts and losses . As the size of the data sample is scaled the Bayesian posterior makes transitions trading off higher complexity (higher ) for better accuracy (lower loss ).
This is the radical new framework of SLT: phase transitions happen i...
Alignment by Simulation?
I've heard this alignment plan that is a variation of 'simulate top alignment researchers' with an LLM. Usually the poor alignment researcher in question is Paul.
This strikes me as deeply unserious and I am confused why it is having so much traction.
That AI-assisted alignment is coming (indeed, is already here!) is undeniable. But even somewhat accurately simulating a human from textdata is a crazy sci-fi ability, probably not even physically possible. It seems to ascribe nearly magical abilities to LLMs.
Predicting...
There should be a PDF version of Ajeya Cotra's BioAnchors report on Arxiv. Having it only as a Google Drive folder (https://drive.google.com/drive/u/1/folders/15ArhEPZSTYU8f012bs6ehPS6-xmhtBPP) makes it very hard to find and cite.
Most justice systems seem to punish theft on a log scale. I'm not big on capital punishment, but it is actually bizarre that you can misplace a billion dollars of client funds and escape the reaper in a state where that's done fairly regularly. The law seems to be saying: "don't steal, but if you do, think bigger."
Hm, I hadn't thought about it that way. I was just thinking that the goal of the fine is some combination of 1) punitive and 2) deterrent, and neither of those goals are accomplished if you fine Bill Gates $200. But yeah, I guess if you make the fine large enough such that the state is ambivalent, maybe it all works out.
Since Raemon's Thinking Physics exercise I've been toying with writing physics puzzles along those lines. (For fun, not because I'm aiming to write better exercise candidates.) If you assume an undergrad-level background and expand to modern physics and engineering there are interesting places you can go. I think a lot about noise and measurement, so that's where my mind has been. Maybe some baseline questions could look like the below? Curious to hear anyone's thoughts.
Pushing a thermal oscillator
You're standing at one end of a grocery aisle. In your cart...
Molecular electromechanical switch
You've attached one end of a conductive molecule to an electrode. If the molecule bends by a certain distance at the other end, it touches another electrode, closing an electrical circuit. (You also have a third electrode where you can apply a voltage to actuate the switch.)
You're worried about the thermal bending motion of the molecule accidentally closing the circuit, causing an error. You calculate, using the Boltzmann distribution over the elastic potential energy in the molecule, that the probability of a ...
I'm looking for AI safety projects with people with some amount of experience. I have 3/4 of a CS degree from Caltech, one year at MIRI, and have finished the WMLB and ARENA bootcamps. I'm most excited about making activation engineering more rigorous, but willing to do anything that builds research and engineering skill.
If you've published 2 papers in top ML conferences or have a PhD in something CS related, and are interested in working with me, send me a DM.
I’m not the person you are looking for, but I think it’s a great idea to put this out there and try to find collaborators, especially in the case of independent researchers. I’ll be actively trying to do the same.
I’m often reminded of a productivity tip by Spencer Greenberg:
...4. Involve other people in projects in such a way that they rely on you to get your parts done.
For me personally, this is probably the most powerful technique I've ever discovered for getting work done efficiently. When I know someone needs something by 2pm, and will be waiting if
On applying generalization bounds to AI alignment. In January, Buck gave a talk for the Winter MLAB. He argued that we know how to train AIs which answer on-distribution questions at least as well as the labeller does. I was skeptical. IIRC, his argument had the following structure:
...Premises:
1. We are labelling according to some function f and loss function L.
2. We train the network on datapoints (x, f(x)) ~ D_train.
3. Learning theory results give (f, L)-bounds on D_train.
Conclusions:
4. The network should match f's labels on the rest of D_train, on av
Huh, well that's something.
I'm curious, who else got this? And if yes, anyone click the link? Why/why not?
I got both mails (with a different virtue). I clicked on it.
I think this is a meta-petrov, where everyone has the choice to make their preference (likely all in the minority, or stated as such even if not) the winner, or to defer to others. I predict that it will eventually be revealed that the outcome would be better if nobody clicked the second link. I defected, because pressing buttons is fun.
For the record, to mods: I waited till after petrov day to answer the poll because my first guess upon receiving a message on petrov day asking me to click something is that I'm being socially engineered. Clicking the next day felt pretty safe.
Does anybody know if consensus algorithms have been proposed that try to reduce centralization by requiring quick coordination across large parts of the network, i.e., it doesn't work well to have machines only in one place?
you can only prove upper bounds on latency
Have them prove an upper bound on latency to something across the globe?
Thought: It's better to link to tag pages rather than blog posts. Like Reversed Stupidity Is Not Intelligence instead of Reversed Stupidity Is Not Intelligence.
This is super rough and unrefined, but there's something that I want to think and write about. It's an epistemic failure mode that I think is quite important. It's pretty related to Reversed Stupidity is Not Intelligence. It goes something like this.
You think 1. Alice thinks 2. In your head, you think to yourself:
Gosh, Alice is so dumb. I understand why she thinks 2. It's because A, B, C, D and E. But she just doesn't see F. If she did, she'd think 1 instead of 2.
Then you run into other people being like:
...Gosh, Bob is so dumb. I understand why he thinks 1.
Falling birthrates is the climate change of the right: