This post is a not a so secret analogy for the AI Alignment problem. Via a fictional dialog, Eliezer explores and counters common questions to the Rocket Alignment Problem as approached by the Mathematics of Intentional Rocketry Institute.
MIRI researchers will tell you they're worried that "right now, nobody can tell you how to point your rocket’s nose such that it goes to the moon, nor indeed any prespecified celestial destination."
The history of science has tons of examples of the same thing being discovered multiple time independently; wikipedia has a whole list of examples here. If your goal in studying the history of science is to extract the predictable/overdetermined component of humanity's trajectory, then it makes sense to focus on such examples.
But if your goal is to achieve high counterfactual impact in your own research, then you should probably draw inspiration from the opposite: "singular" discoveries, i.e. discoveries which nobody else was anywhere close to figuring out. After all, if someone else would have figured it out shortly after anyways, then the discovery probably wasn't very counterfactually impactful.
Alas, nobody seems to have made a list of highly counterfactual scientific discoveries, to complement wikipedia's list of multiple discoveries.
To...
A few adjacent thoughts:
Here we have some technology that is basically ready to use (Haskell or Clojure), but people decide to mostly not use them. And w...
OC ACXLW Sat April 27 Argumentation and College Admissions
Hello Folks! We are excited to announce the 63rd Orange County ACX/LW meetup, happening this Saturday and most Saturdays after that.
Host: Michael Michalchik Email: michaelmichalchik@gmail.com (For questions or requests) Location: 1970 Port Laurent Place (949) 375-2045 Date: Saturday, April 27 2024 Time 2 pm
Conversation Starters:
Text link: https://www.currentaffairs.org/2018/11/you-can-make-an-argument-for-anything
Questions for discussion: a) The article suggests that people often do not investigate arguments very closely, and are...
For the last month, @RobertM and I have been exploring the possible use of recommender systems on LessWrong. Today we launched our first site-wide experiment in that direction.
(In the course of our efforts, we also hit upon a frontpage refactor that we reckon is pretty good: tabs instead of a clutter of different sections. For now, only for logged-in users. Logged-out users see the "Latest" tab, which is the same-as-usual list of posts.)
A core value of LessWrong is to be timeless and not news-driven. However, the central algorithm by which attention allocation happens on the site is the Hacker News algorithm[1], which basically only shows you things that were posted recently, and creates a strong incentive for discussion to always be...
Disappointing to see this is the approach y'all are taking to making ai tools for the site, but I guess it does make sense that you'd want to outsource it. I'd strongly appreciate a way to opt out of having my data sent off-site for this or any future reason.
TL;DR All GPT-3 models were decommissioned by OpenAI in early January. I present some examples of ongoing interpretability research which would benefit from the organisation rethinking this decision and providing some kind of ongoing research access. This also serves as a review of work I did in 2023 and how it progressed from the original ' SolidGoldMagikarp' discovery just over a year ago into much stranger territory.
Some months ago, when OpenAI announced that the decommissioning of all GPT-3 models was to occur on 2024-01-04, I decided I would take some time in the days before that to revisit some of my "glitch token" work from earlier in 2023 and deal with any loose ends that would otherwise become impossible to tie up after that date.
This abrupt termination...
Thanks!
I agree. This is unfortunately often done in various fields of research where familiar terms are reused as technical terms.
For example, in ordinary language "organic" means "of biological origin", while in chemistry "organic" describes a type of carbon compound. Those two definitions mostly coincide on Earth (most such compounds are of biological origin), but when astronomers announce they have found "organic" material on an asteroid this leads to confusion.
My credence: 33% confidence in the claim that the growth in the number of GPUs used for training SOTA AI will slow down significantly directly after GPT-5. It is not higher because of (1) decentralized training is possible, and (2) GPT-5 may be able to increase hardware efficiency significantly, (3) GPT-5 may be smaller than assumed in this post, (4) race dynamics.
TLDR: Because of a bottleneck in energy access to data centers and the need to build OOM larger data centers.
Update: See Vladimir_Nesov's comment below for why this claim is likely wrong, since decentralized training seems to be solved.
Thank for the great comment!
Do we know if distributed training is expected to scale well to GPT-6 size models (100 trillions parameters) trained over like 20 data centers? How does the communication cost scale with the size of the model and the number of data centers? Linearly on both?
After reading for 3 min this:
Google Cloud demonstrates the world’s largest distributed training job for large language models across 50000+ TPU v5e chips (Google November 2023). It seems that scaling is working efficiently at least up to 50k GPUs (GPT-6 would be like 2.5...
Concerns over AI safety and calls for government control over the technology are highly correlated but they should not be.
There are two major forms of AI risk: misuse and misalignment. Misuse risks come from humans using AIs as tools in dangerous ways. Misalignment risks arise if AIs take their own actions at the expense of human interests.
Governments are poor stewards for both types of risk. Misuse regulation is like the regulation of any other technology. There are reasonable rules that the government might set, but omission bias and incentives to protect small but well organized groups at the expense of everyone else will lead to lots of costly ones too. Misalignment regulation is not in the Overton window for any government. Governments do not have strong incentives...
I don't think staging a civil war is generally a good way of saving lives. Moreover, ordinary aging has about a 100% chance of "killing literally everyone" prematurely, so it's unclear to me what moral distinction you're trying to make in your comment. It's possible you think that:
In the case of...
(Half-baked work-in-progress. There might be a “version 2” of this post at some point, with fewer mistakes, and more neuroscience details, and nice illustrations and pedagogy etc. But it’s fun to chat and see if anyone has thoughts.)
There’s a neuroscience problem that’s had me stumped since almost the very beginning of when I became interested in neuroscience at all (as a lens into AGI safety) back in 2019. But I think I might finally have “a foot in the door” towards a solution!
What is this problem? As described in my post Symbol Grounding and Human Social Instincts, I believe the following:
Tangentially related: some advanced meditators report that their sense that perception has a center vanishes at a certain point along the meditative path, and this is associated with a reduction in suffering.