trentmkelly/LessWrong-43k huggingface dataset:
More on the Apple Vision Pro
by Zvi — 2024-02-13T17:40:05.388Z

Previously: On the Apple Vision Pro

The reviews are coming in. What say the people, other than the complaining about the two to three hour battery life?

Then later I’ll get to my own thoughts after the demo.

Reviews and Reactions

Ben Thompson reviews the Apple Vision Pro. He continues to find it a technical marvel, but is ultimately disappointed for uses other than entertainment. There is no support for multiple users beyond a highly unwieldy guest mode. There is insufficient width of coverage and inability to support multiple large screens, which is severely limiting to productivity. The eye tracking is a huge improvement over earlier attempts but not ready for such applications.

Ben anticipates that Apple will fail over time to evolve the product to support the things that would enable it to be a killer productivity app, which is what he was most excited about. He loves it for movies and watching sports (and presumably television), especially if new offerings support its features, but especially when the device is hard to share the $3,500 price tag is a tough sell.

Ben frames this as an intentional trade-off to maximize the entertainment experience. I do not get this claim. I see no reason the Vision Pro could not in the future support the entertainment experience it offers now, while also offering a distinct productivity experience that allows streaming multiple screens and using more precise controls and letting you use an iPhone or iPad as an additional control panel and navigation guide.

Andrej Karpathy offers his thoughts on the Vision Pro. Amazingly great in some ways, jank in other ways, including overly long setup. Several complaints here gave me hope, since they are concerns that won’t much matter over time, either you get through it or it gets fixed. Device weight is clearly a major issue. The review was essentially saying this is a device that will be great but has not yet handled the last mile.

Vanity Fair on why Tim Cook bet on the Apple Vision Pro, I would not call it ‘all-in’ since Apple will be fine no matter what. A strange article, worried about future versions being essentially too good. Like Thompson’s review, makes clear that the entertainment mode is well ahead of the productivity mode, although its motives lie elsewhere. The anecdote about having trouble finding apps after moving rooms is telling.

Aaron Slodov says ‘it’s amazing a...
Linear White
by  — 2024-02-13T16:31:46.355Z
Link: https://krez.expert/emotions/2024/02/10/linear-white.html

It is something you feel when you are writing computer programs.

A normal person might experience something like this feeling if they are in a giant hotel filled with a million rooms.

They have to go into every room and ask the occupants if they are happy with the services provided by the hotel. This is the job.

While doing this job, many say they are happy. Some say they are unhappy. You ask them why they are unhappy, they say it is because the Air Conditioning has only one degree of precision in celsius, instead of 4 like they are used to in some other luxury hotel they visited.

So, it is 20.2 Celcius instead of 20.4902 Celcius. They claim this has disturbed their cicardian rhythms and has resulted in less optimal sleep. They leave a one-star rating and say they are never going to visit this hotel again.

You move another twenty thousand rooms of happy customers. And then you find another unhappy customer. They say the iced tea did not have the right prime number of ice cubes. In the previous hotel they were staying at, it had the correct number of ice cubes without them specifying it explicitly. This they said showed some great inattentives of the room service agents.

You wonder if it is even possible to anticipate what prime number of ice cubes some customer likes. But you note this down and move on another five hundred thousand rooms. You find another unhappy customer. They say the smart wall did not change colours in a way they liked. The pictures were too noisy in some way, they claim.

You ask them why was it noisy? They say it is because of the Air Conditioning. They claim the functors of the air currents created by the AC and the screensaver on the smart wall do not match. This creates some pervasive feeling of unpleasantness, they claim.

This is luckily an easier problem to fix than the previous complaint about the prime number of ice cubes, so you note this down.

Then you move another 200 thousand rooms. You find the room empty. You sit down and wait for the room occupant to arrive. Twelve hours later you figure out someone randomly booked this room, and there are no occupants at all. This was some person who was so rich he or she booked the room and forgot about it completely. The hotel you are working at has extremely strict rules about getting feedback from all customers.

So you track down their phone number and call them. They do not pick up. If you do n...
Causality is Everywhere
by silentbob — 2024-02-13T13:44:49.952Z

Tl;dr: Everything in our world is causally connected in countless ways, which means causal effects are everywhere, and practically anything has systematic effects on almost everything else – it’s just that most of these effects are very close to (but not quite) zero. Studies often fail to measure small effects due to being underpowered, which frequently leads people to believe that some effect “does not exist” (i.e. is 0). I argue that this is a mistake, that almost no effect is truly 0, and that it’s worthwhile to be nuanced about this for a variety of reasons.

In the quest for understanding the world, we often fall into the dichotomy of asking whether X affects Y. Does diet influence mood? Does music affect productivity? Is there a relationship between the stars' positions at your birth and your personality? The common thread in these questions is our search for causality, mapping the invisible lines that shape reality.

Yet, the pursuit often narrows our vision, framing our questions in a binary of effects versus no effects. This binary is a simplification, perhaps a reasonable one for many practical concerns, but a simplification nonetheless. What if, instead of asking if there is an effect, we assumed there always is one, and made an effort to ask for effect sizes and their sign, rather than mere existence? When asking “is there an effect”, we imply that there’s a significant chance of the answer being “no” – that X simply has no impact on Y whatsoever. But this, I argue, is a mistake. A mistake that hints at a fundamental misconception about the nature of causality in our infinitely interconnected world.

Causality is everywhere. Of course we all know well that correlation is not causation, and most causal effects may indeed be swamped by confounding effects, or by noise, or by any of the countless biases working against science’s effective pursuit of truth seeking. Yet, the fact that we have a hard time seeing causality, doesn’t make it less real. As gwern

explains

, correlation is everywhere. I argue that the same holds for causation (even if on a much lower scale).

Everything is connected. Not in the esoteric way, but rather in the most physical way possible: as long as two happenings in the universe are within each other’s light cone, they will almost always have some causal connection, and usually quite a number of them. Th...
Technologies and Terminology: AI isn't Software, it's... Deepware?
by Davidmanheim — 2024-02-13T13:37:10.364Z

A few weeks ago, I (David) tried to argue that AI wasn’t software. In retrospect, I think I misstated the case by skipping some inferential steps, and based on some feedback from that article, and on an earlier version of this article, with a large assist by Abram Demski, I’m going to try again.

The best response to my initial post, by @gjm, explained the point more succinctly and better than I had; “An AI system is software in something like the same way a human being is chemistry.” And yes, of course the human body is chemistry. So in that sense, I was wrong - arguing that AI isn’t software is, in some sense, arguing that the human body isn’t chemistry. But the point was that we don’t think about humans in terms of chemistry.

“

The Categories Were Made For Man, Not Man For The Categories

.” That is, what we call things is based on inference about which categories should be used, and what features are definitive or not. And any categorization has multiple purposes, and so the question of whether to categorize things together or separately is collapsing many questions together.

The prior essay spent time arguing that Software and AI are different. The way software is developed is different from the way AI is developed, and the way software behaves and how it fails is different from how AI behaves and fails. Here, I’ll add two more dimensions; that the people and the expertise for AI is different than that for software, and that AI differs from software in ways similar to how software differs from hardware. In between those two, I’ll introduce a conceptual model from Abram Demski explaining that AI is a different type of tool than software that captures much more of the point.

Based on that, we’ll get to the key point that was obscured initially; if AI is a different type of thing, what does that imply about it - and less importantly, what should we name the new category?

Who does what?

If we ask a stranger what they do, and they say chemistry, we would be surprised to learn that they were a medical doctor. On the other hand, if someone is a medical doctor, we expect them to know a reasonable amount about biochemistry.

I have a friend who was interested in business, but did a bachelors in scientific computational methods. He went on to get an MBA, and did research on real time pricing in electrical markets - a field where his background was essential...
Lsusr's Rationality Dojo
by lsusr — 2024-02-13T05:52:03.757Z

Why aren’t there dojos that teach rationality?

―The Martial Art of Rationality by Eliezer Yudkowsky

For the last 6 months, I've been running a dojo that teaches rationality.

Why

I was at an ACX meetup and met an acolyte who grew up in an evangelical Christian community. He had recently discovered the Sequences and was really excited about this whole Rationality thing. He was very confident in Yudkowsky's teachings.

I asked him a couple questions and he realized his beliefs were full of holes. He wondered how he could have understood so little. After all, he had read all of Yudkowsky's Sequences.

"I have read 100 books about chess," I said, "Surely I must be a grandmaster by now."

At that moment, he was enlightened.

The problem

The objective of rationality is to become right instead of wrong. Being wrong feels exactly like being right. We are not aware of our own biases. We are not aware of our own mistakes. We are not aware of the lies we tell ourselves. This is almost a tautology.

Other people are not tautologically blind to our mistakes in the same way. The simplest way to become less wrong is to have someone else point out your mistakes to you. Except this doesn't actually work. If I say "I'm right," and you say "you're wrong", then we get nowhere. The more we argue, the more frustrated we get.

The solution

There is a better way. I call it rhetorical aikido. Rhetorical aikido is a Daoist form of Socratic dialogue. The simplest form of rhetorical aikido has three steps:

You let someone confidently state a belief A that you know is wrong.
You let that same someone confidently state a belief B that contradicts A.
You let them notice that A contradicts B.

Examples:
[I'm the guy in the dark green chair on your right.]

Notice that this technique follows Dale Carnegie's guidelines. You smile. You agree. You show genuine interest in the other person. You don't say "You're wrong". You never even say your own beliefs (unless asked). There's nothing for the person to get angry at because you never attacked them. Instead of criticizing, you point out errors indirectly, via a joke. You cheer them on as they dig their own grave. After all, you're trying to lose too.

Perhaps more importantly, this technique makes password-guessing impossible. You're playing the bastard offspring of chess + Calvinball. There is no password to guess.

The right conditio

...
Where is the Town Square?
by Gretta Duleba — 2024-02-13T03:53:18.205Z

I am seeking crowdsourced wisdom.

Suppose I[1] want to influence public opinion on a complicated, nuanced topic.[2]

And further suppose that one of the ways I want to do that is by participating actively in public discourse: posting short-form content, reacting to other people's short-form content, signal boosting good takes, thoughtfully rebutting bad takes, etc.

Suppose that the people I most want to reach are those who make and influence policy in places like the US, EU, UK, and China; the general voting public (because they vote for legislators); and the intelligentsia in fields related to my topic (because some of them advise policymakers).

On what platform(s)/in what outlet(s) should I be doing this in 2024? "And, since I can't do everything: what popular platforms shouldn't I prioritize?

And more specifically, does Twitter/X still matter, and how much? I am aware that many people have moved to mastodon or bluesky or whatever. Is there critical mass anywhere?

^

who happen to be the Communications Manager at MIRI

^

The topic is AI x-risk.
My cover story in Jacobin on AI capitalism and the x-risk debates
by garrison — 2024-02-12T23:34:16.526Z
Link: https://jacobin.com/2024/01/can-humanity-survive-ai

Google cofounder Larry Page

thinks

superintelligent AI is “just the next step in evolution.” In fact, Page, who’s worth about $120 billion, has reportedly

argued

that efforts to prevent AI-driven extinction and protect human consciousness are “speciesist” and “

sentimental nonsense

.”

In July, former Google DeepMind senior scientist Richard Sutton — one of the pioneers of reinforcement learning, a major subfield of AI —

said

that the technology “could displace us from existence,” and that “we should not resist succession.” In a

2015 talk

, Sutton said, suppose “everything fails” and AI “kill[s] us all”; he asked, “Is it so bad that humans are not the final form of intelligent life in the universe?”

This is how I begin the

cover story

for Jacobin’s winter issue on AI. Some very influential people openly welcome an AI-driven future, even if humans aren’t part of it.

Whether you're new to the topic or work in the field, I think you'll get something out of it.

I spent five months digging into the AI existential risk debates and the economic forces driving AI development. This was the most ambitious story of my career — it was informed by interviews and written conversations with three dozen people — and I’m thrilled to see it out in the world. Some of the people include:

Deep learning pioneer and Turing Award winner Yoshua Bengio
Pathbreaking AI ethics researchers Joy Buolamwini and Inioluwa Deborah Raji
Reinforcement learning pioneer Richard Sutton
Cofounder of the AI safety field Eliezer Yudkowksy
Renowned philosopher of mind David Chalmers
Sante Fe Institute complexity professor Melanie Mitchell
Researchers from leading AI labs

Some of the most powerful industrialists and companies are plowing enormous amounts of money and effort into increasing the capabilities and autonomy of AI systems, all while acknowledging that superhuman AI could literally wipe out humanity:

Bizarrely, many of the people actively advancing AI capabilities think there’s a significant chance that doing so will ultimately cause the apocalypse. A

2022 survey

of machine learning researchers found that nearly half of them thought there was at least a 10 percent chance advanced AI could lead to “human extinction or [a] similarly permanent and severe disempowerment” of humanity. Just months before he cofounded OpenAI, Altman

said

, “AI will probably most likely lead to the end of the world, but in the m

...
What is Ontology?
by martinkunev — 2024-02-12T23:01:35.632Z

This is my attempt at an intuitive explanation of the term "ontology". This article is not going to say anything new, only provide a (maybe) different view point on known concepts.

There are tons of definitions for "ontology". In my experience, those definitions do not help in understanding the concept - one I heard at university is "Ontology is the explicit specification of conceptualization". Instead of giving definitions, I'm going to give an example of two AI agents with different ontologies.

AI agent Susan

Susan is an AI agent that can add integers. Susan is asked to play a game against another AI agent: The players take turns to select an integer between 1 and 9 and remember it (each integer can be selected only once). The first player to have exactly three integers that sum to 15 wins. If no player has three integers summing to 15, the game is a draw.

1 2 3 4 5 6 7 8 9

Here is an example play:

agent0 selects 2
agent1 selects 8
agent0 selects 6 (it has: 2, 6)
agent1 selects 7 (it has: 8, 7)
agent0 selects 4 (it has: 2, 4, 6)
agent1 selects 5 (it has: 8, 7, 5)
agent0 selects 9 (win because 9 + 4 + 2 = 15)

AI agent Greg

Greg is an AI agent that can find patterns in 2D grids. Greg is asked to play a game of tic-tac-toe against another AI agent: The players take turns - one places "x" and the other "o" in an empty cell of a 3x3 grid. The first player to complete a line of three (horizontal, vertical or diagonal) wins. If no player completes a line, the game is a draw. You're probably familar with the game, but here is an example play:

x

o
x

x	o
x

x	o
x
o

x	o
x	x
o

x	o
x	x	o
o

x	o
x	x	o
x	o

Susan and Greg playing against each other

At first glance it may appear that the two agents have very different capabilities but in fact the two games are isomorphic. The isomorphism can be represented by a common language. If both agents speak this language, they can play with each other. Consider a language with just 9 words: a b c d e f g h i. Each word corresponds to a possible move.

For Susan, each word has the meaning of selecting the following integer:

a	b	c	d	e	f	g	h	i
1	3	5	7	9	2	4	6	8

For Greg, each word has the meaning of selecting the following grid cell:

f	d	h
e	c	a
g	b	i

Now, each action and observation can be represented b...
Thank you for triggering me
by Cissy — 2024-02-12T20:09:44.987Z
Link: https://www.moremyself.xyz/p/triggered

This essay is the first in a series on why turning towards what activates us is the path to setting ourselves free. The rest of the series will feature modalities & tools for working with our triggers and welcoming suppressed emotions.

Turning inward — taking our shadows, insecurities, and relationship dynamics into our own hands — and resolving our inner conflict day in and day out is the first step in walking the path towards collective flourishing.

Whenever I commit my energy to writing about an area of my life I’m grappling with, it’s as if I’m tempting the universe to pressure test how deeply I’ve integrated it in my life. As I wrote

A lifetime of should-ing

, I found myself in the throes of shoulding myself. As I shaped

Year of doing the damn thing

, every ounce of my being seemed to resist doing the damn thing. After I published

The mourning of a new dawn

, I was hit by the most intense waves of grief I’ve experienced in a long time.

A few weeks ago, I decided to write about turning towards our triggers and how my relationship with triggers has evolved meaningfully. I used to think that “self-improvement” was about mindset work and focusing on the positive. All I needed to do was control my thoughts and then I wouldn't feel nervous, anxious, incompetent, fill-in-negative-emotion.

Now, I know that tuning into our bodies and shining a light on our unwelcome feelings is the path towards understanding ourselves more deeply. As I began drafting this essay, the universe took it as a sign to stress test whether I was really ready to thank my triggers and whether I’ve truly embodied the wisdom of being activated.

The past month has brought about a lot of change. Our move to a new neighborhood coincided with the start of the year, a time of hitting reset and starting fresh. I had anticipated that the new year and a new environment would create space for cultivating new routines and beliefs, allowing me to shed old habits that no longer served me. Our new apartment and upgraded routines would be up and running in no time. Or so I thought.

Instead, I found myself floating in the liminal space, unsettled and ungrounded. Like a plant that’s outgrown its pot, I uprooted my life and repotted myself in a new planter, expecting myself to acclimate and flourish immediately.

What I underestimated was how it would feel to be pulled out of the familiar. I forgot that with a new...
Interpreting Quantum Mechanics in Infra-Bayesian Physicalism
by Yegreg — 2024-02-12T18:56:03.967Z

This work was inspired by a question by Vanessa Kosoy, who also contributed several of the core ideas, as well as feedback and mentorship.

Abstract

We outline a computationalist interpretation of quantum mechanics, using the framework of infra-Bayesian physicalism. Some epistemic and normative aspects of this interpretation are illuminated by a number of examples and theorems.

1. Introduction

Infra-Bayesian physicalism was introduced as a framework to investigate the relationship between a belief about a joint computational-physical universe and a corresponding belief about which computations are realized in the physical world, in the context of "infra-beliefs". Although the framework is still somewhat tentative and the definitions are not set in stone, it is interesting to explore applications in the case of quantum mechanics.

1.1. Discussion of the results

Quantum mechanics has been notoriously difficult to interpret in a fully satisfactory manner. Investigating the question through the lens of computationalism, and more specifically in the setting of infra-Bayesian physicalism provides a new perspective on some of the questions via its emphasis on formalizing aspects of metaphysics, as well as its focus on a decision-theoretic approach. Naturally, some questions remain, and some new interesting questions are raised by this framework itself.

The toy setup can be described on the high level as follows (with details given in Sections 2 to 4). We have an "agent": in this toy model simply consisting of a policy, and a memory tape to record observations. The agent interacts with a quantum mechanical "environment": performing actions and making observations. We assume the entire agent-environment system evolves unitarily. We'll consider the agent having complete Knightian uncertainty over its own policy, and for each policy the agent's beliefs about the "universe" (the joint agent-environment system) is given by the Born rule for each observable, without any assumption on the correlation between observables (formally given by the free product). We can then use the key construction in infra-Bayesian physicalism — the bridge transform — to answer questions about the agent's corresponding beliefs about what copies of the agent (having made different observations) are instantiated in the given universe.

In light of the falsity of Claims 4.15 and 4.17, we can think of ...