interstice

Comments

Economic Class

Interesting(and funny!). I would appreciate more posts on this topic or other "gears-y rundown from a lawyer" type posts.

I'm still mystified by the Born rule

My own most recent pet theory is that the process of branching is deeply linked to thermalization, so to find model systems we should look to things modeling the flow of heat/entropy -- e.g. a system coupled to two heat baths at different temperatures.

I'm still mystified by the Born rule

It’s easy enough to get a single sensory datum — sample a classical state according to the Born probabilities, sample some coordinates, pretend that there’s an eyeball at those coordinates, record what it sees. But once we’ve done that, how do we get our next sense datum?

This doesn't seem like it should be too hard -- if you have some degrees of freedom which you take as representing your 'eyeball', and a preferred basis of 'measurement states' for that eyeball, repeatedly projecting onto that measurement basis will give sensible results for a sequence of measurements. Key here is that you don't have to project e.g. all the electrons in the universe onto their position basis -- just the eyeball DOF onto their preferred 'measurement basis'(which won't look like projecting the electrons onto their position basis either), and then the relevant entangled DOF in the rest of the universe will automatically get projected onto a sensible 'classical-like' state. The key property about the universe's evolution that would make this procedure sensible is non-interference between the 'branches' produced by successive measurements. i.e. if you project onto two different eyeball states at time 1, then at time 2, those states will be approximately non-interfering in the eyeball basis. This is formalized in the consistent histories approach to QM.

What's somewhat trickier is identifying the DOF that make a good 'eyeball' in the first place, and what the preferred basis should be. More broadly it's not even known what quantum theories will give rise to 'classical-like' states at all. The place to look to make progress here is probably the decoherence literature, also quantum darwinism and Jess Riedel's work.

Are the Born probabilities really that mysterious?

If you view the laws of physics as the minimal program capable of generating our observations, the Born rule is no more problematic than any other part of the laws of physics. If our universe was sampled according to a different rule, it would look completely different, just the same as if the terms in the Lagrangian were changed.

Deepmind has made a general inductor ("Making sense of sensory input")

If a thing has two main distinct parts, it seems reasonable to say that the thing is half part-1 and half part-2. This does not necessarily imply that the parts are equally difficult to create, although that would be a reasonable prior if you didn't know much about how the parts worked.

Deepmind has made a general inductor ("Making sense of sensory input")

I mean, it's not exactly provable from first principles, but using the architecture of AIXI as a heuristic for what a general intelligence will look like seems to make sense to me. 'Do reinforcement learning on a learned world model' is, I think, also what many people think a GAI may end up in fact looking like, e.g., and saying that that's half decision theory and half predictive model doesn't seem too far off.

Deepmind has made a general inductor ("Making sense of sensory input")

Is there any evidence that this is actually a general inductor, i.e. that as a prior it dominates some large class of functions? From skimming the paper it sounds like this could be interesting progress in ILP, but not necessarily groundbreaking or close to being a fully general inductor. At the moment I'd be more concerned about the transformer architecture potentially being used as (part of) a general inductor.

However to think about Newcomb’s problem entails “casting yourself” as the agent and predictor both, with a theoretically unlimited amount of time to consider strategies for the agent to defeat the predictor, as well as for the predictor to defeat the agent.

I don't think so. Newcomb's problem is meant to be a simple situation where an agent must act in an environment more computationally powerful than itself. The perspective is very much meant to be that of the agent. If you think that figuring out how to act in an environment more powerful than yourself is uninteresting, you must be pretty bored, since that describes the situation all of us find ourselves in.

Are you claiming that the problem arises when the agent tries to predict its own behavior, or when the predictor tries to predict the agent's behavior? Either way, I don't think this makes Newcomb incoherent. Even if the agent can't solve the halting problem in general, there are programs that can solve it in specific cases, including for themselves. And the predictor can be assumed to have greater computational resources than the agent, e.g. it can run for longer, or has a halting oracle if you really want the type of the agent to be 'general Turing machine', which means it can avoid self-reference paradoxes.

Senior quote ideas

Recognition code 927, I am a potato.

Load More