Rational Animations

The Power of Intelligence - An Essay By Eliezer Yudkowsky

March 11, 2023 5:59 pm

The Power of Intelligence is an essay published by Eliezer Yudkowsky in 2007.

Now, a few points:

Sorting Pebbles Into Correct Heaps was about the orthogonality thesis. A consequence of the orthogonality thesis is that powerful artificial intelligence will not necessarily share human values.

This video is about just how powerful and dangerous intelligence is. These two insights put together are a cause for concern.

If humanity doesn't solve the problem of aligning AIs to human values, there's a high chance we'll not survive the creation of artificial general intelligence. This issue is known as "The Alignment Problem". Some of you may be familiar with the paperclips scenario: an AGI created to maximize the number of paperclips uses up all the resources on Earth, and eventually outer space, to produce paperclips. Humanity dies early in this process. But, given the current state of research, even a simple goal such as “maximize paperclips” is already too difficult for us to program reliably into an AI. We simply don't know how to aim AIs reliably at goals. If tomorrow a paperclip company manages to program a superintelligence, that superintelligence likely won't maximize paperclips. We have no idea what it would do. It would be an alien mind pursuing alien goals. Knowing this, solving the alignment problem for human values in general, with all their complexity, appears like truly a daunting task. But we must rise to the challenge, or things could go very wrong for us.

You can read The Power of Intelligence and many other essays by Eliezer Yudkowsky on this website: https://www.readthesequences.com/

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Animation Director: https://twitter.com/vezanmatics/Evan

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The True Story of How GPT-2 Became Maximally Lewd

January 18, 2024 9:52 pm

In this video, we recount an incident that occurred at OpenAI while researchers were trying to finetune GPT-2 to be as helpful and ethical as possible. It's narrated that inadvertently flipping a single minus sign led GPT-2 to become the embodiment of a well-known cardinal sin.

#ai #aisafety #alignment

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OpenAI blog post: https://openai.com/research/fine-tuning-gpt-2
OpenAI paper behind the blog post: https://arxiv.org/pdf/1909.08593.pdf
RLHF explainer on Hugging Face: https://huggingface.co/blog/rlhf
RLHF explainer on aisafety.info https://aisafety.info/?state=88FN_904Jr8368r89ZSr
Concrete Problems in AI Safety, by @RobertMilesAI: https://www.youtube.com/playlist?list=PLqL14ZxTTA4fEp5ltiNinNHdkPuLK4778

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What Do Neural Networks Really Learn? Exploring the Brain of an AI Model

June 14, 2024 5:00 pm

Neural networks have become increasingly impressive in recent years, but there's a big catch: we don't really know what they are doing. We give them data and ways to get feedback, and somehow, they learn all kinds of tasks. It would be really useful, especially for safety purposes, to understand what they have learned and how they work after they've been trained. The ultimate goal is not only to understand in broad strokes what they're doing but to precisely reverse engineer the algorithms encoded in their parameters. This is the ambitious goal of mechanistic interpretability. As an introduction to this field, we show how researchers have been able to partly reverse-engineer how InceptionV1, a convolutional neural network, recognizes images.

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This topic is truly a rabbit hole. If you want to learn more about this important research and even contribute to it, check out this list of sources about mechanistic interpretability and interpretability in general we've compiled for you:

On Interpreting InceptionV1:

Feature visualization: https://distill.pub/2017/feature-visualization/
Zoom in: An Introduction to Circuits: https://distill.pub/2020/circuits/zoom-in/
The Distill journal contains several articles that try to make sense of how exactly InceptionV1 does what it does: https://distill.pub/2020/circuits/
OpenAI's Microscope tool lets us visualize the neurons and channels of a number of vision models in great detail: https://microscope.openai.com/models
Here's OpenAI's Microscope tool pointed on layer Mixed3b in InceptionV1: https://microscope.openai.com/models/inceptionv1/mixed3b_0?models.op.feature_vis.type=channel&models.op.technique=feature_vis
Activation atlases: https://distill.pub/2019/activation-atlas/
More recent work applying SAEs to InceptionV1: https://arxiv.org/abs/2406.03662v1

Transformer Circuits Thread, the spiritual successor of the circuits thread on InceptionV1. This time on transformers: https://transformer-circuits.pub/
In the video, we cite "Toy Models of Superposition": https://transformer-circuits.pub/2022/toy_model/index.html
We also cite "Towards Monosemanticity: Decomposing Language Models With Dictionary Learning": https://transformer-circuits.pub/2023/monosemantic-features/

More recent progress:

Mapping the Mind of a Large Language Model:
Press: https://www.anthropic.com/research/mapping-mind-language-model
Paper in the transformers circuits thread: https://transformer-circuits.pub/2024/scaling-monosemanticity/index.html

Extracting Concepts from GPT-4:
Press: https://openai.com/index/extracting-concepts-from-gpt-4/
Paper: https://arxiv.org/abs/2406.04093
Browse features: https://openaipublic.blob.core.windows.net/sparse-autoencoder/sae-viewer/index.html

Language models can explain neurons in language models (cited in the video):
Press: https://openai.com/index/language-models-can-explain-neurons-in-language-models/
Paper: https://openaipublic.blob.core.windows.net/neuron-explainer/paper/index.html
View neurons: https://openaipublic.blob.core.windows.net/neuron-explainer/neuron-viewer/index.html

Neel Nanda on how to get started with Mechanistic Interpretability:

Concrete Steps to Get Started in Transformer Mechanistic Interpretability: https://www.neelnanda.io/mechanistic-interpretability/getting-started
Mechanistic Interpretability Quickstart Guide: https://www.neelnanda.io/mechanistic-interpretability/quickstart
200 Concrete Open Problems in Mechanistic Interpretability: https://www.alignmentforum.org/posts/LbrPTJ4fmABEdEnLf/200-concrete-open-problems-in-mechanistic-interpretability

More work mentioned in the video:

Progress measures for grokking via mechanistic interpretability: https://arxiv.org/abs/2301.05217
Discovering Latent Knowledge in Language Models Without Supervision: https://arxiv.org/abs/2212.03827
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning: https://www.nature.com/articles/s41551-018-0195-0

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The Hidden Complexity of Wishes

September 27, 2023 7:34 pm

This video is about AI Alignment. At the moment, humanity has no idea how to make AIs follow complex goals that track human values. This video introduces a series focused on what is sometimes called "the outer alignment problem". In future videos, we'll explore how this problem affects machine learning systems today and how it could lead to catastrophic outcomes for humanity.

The text of this video has been slightly adapted from an original article written by Eliezer Yudkowsky. You can read the original article here: https://www.readthesequences.com/The-Hidden-Complexity-Of-Wishes

If you’d like to skill up on AI Safety, we highly recommend the AI Safety Fundamentals courses by BlueDot Impact at https://aisafetyfundamentals.com

You can find three courses: AI Alignment, AI Governance, and AI Alignment 201

You can follow AI Alignment and AI Governance even without a technical background in AI. AI Alignment 201, instead, presupposes having followed the AI Alignment course first, and equivalent knowledge as having followed university-level courses on deep learning and reinforcement learning.

The courses consist of a selection of readings curated by experts in AI safety. They are available to all, so you can simply read them if you can’t formally enroll in the courses.

If you want to participate in the courses instead of just going through the readings by yourself, BlueDot Impact runs live courses which you can apply to. The courses are remote and free of charge. They consist of a few hours of effort per week to go through the readings, plus a weekly call with a facilitator and a group of people learning from the same material. At the end of each course, you can complete a personal project, which may help you kickstart your career in AI Safety.

BlueDot impact receives more applications that they can take, so if you’d still like to follow the courses alongside other people you can go to the #study-buddy channel in the AI Alignment Slack. You can join by clicking on the first entry on https://aisafety.community

You could also join Rational Animations’ Discord server at discord.gg/rationalanimations, and see if anyone is up to be your partner in learning.

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Animation director: Hannah Levingstone
Writer: Eliezer Yudkowsky
Editor and producer: :3

Line Producer and production manager:
Kristy Steffens

Quality Assurance Lead:
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Animation:
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Everything might change forever this century (or we’ll go extinct)

July 24, 2022 6:00 pm

We could be living in the most important century in history. Here's how Artificial Intelligence might uphold a historical trend of super-exponential economic growth, ushering us into a period of sudden transformation, ending in a stable galaxy-scale civilization or doom. All within the next few decades.

This video is based on Holden Karnofsky’s “most important century” blog post series: https://www.cold-takes.com/most-important-century/

Below, you can find additional sources and further readings.

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Most important:

Holden Karnofsky’s “most important century” blog post series: https://www.cold-takes.com/most-important-century/

Ajeya Cotra’s report on AI timelines: https://drive.google.com/drive/u/1/folders/15ArhEPZSTYU8f012bs6ehPS6-xmhtBPP

More sources:

Our World in Data, page on population growth: https://ourworldindata.org/world-population-growth

Our World in Data, page on democracy: https://ourworldindata.org/democracy

Our World in Data, population of England: https://ourworldindata.org/grapher/population-of-england-millennium

Our World in Data, World GDP over the last two millennia: https://ourworldindata.org/grapher/world-gdp-over-the-last-two-millennia?time=1967..2015

Estimates of World GDP, One Million B.C – Present, by J. Bradford De Long: https://delong.typepad.com/print/20061012_LRWGDP.pdf

An Essay on the Principle of Population, by Thomas Malthus: https://www.medicina.univr.it/documenti/OccorrenzaIns/matdid/matdid170841.pdf

Population Growth and Technological Change: One Million B.C. to 1990* Michael Kremer: https://robobees.seas.harvard.edu/files/pegroup/files/kremer1993_2.11.pdf

Modeling the Human Trajectory, by David Roodman: https://www.openphilanthropy.org/research/modeling-the-human-trajectory/

GDP Growth (annual %), from The World Bank: https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG

2016 Expert survey on progress in AI: https://aiimpacts.org/2016-expert-survey-on-progress-in-ai/

Robert Miles’ (our narrator) YouTube channel on AGI alignment: https://www.youtube.com/c/RobertMilesAI

Trends in the cost of computing, by AI Impacts: https://aiimpacts.org/trends-in-the-cost-of-computing/

Animation at minute 31:50 inspired by the cover of the book "Facing the Intelligence Explosion", by Luke Muehlhasuer: https://www.amazon.com/Facing-Intelligence-Explosion-Luke-Muehlhauser-ebook/dp/B00C7YOR5Q/ref=sr_1_3?crid=1JDT2NEC4KCVC&keywords=Luke+Muehlhauser&qid=1658663037&s=books&sprefix=luke+muehlhauser%2Cstripbooks-intl-ship%2C172&sr=1-3

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Writer: Matthew Barnett
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Chapters:

0:00 - A Very Unusual Time Period
4:29 - The 21st Century Could Be Much Weirder Than We Imagine
10:08 - The Duplicator
14:55 - The Most Important Invention Ever?
15:53 - When Will Advanced AI Arrive?
20:29 - Ajeya Cotra's Report on AI Timelines
27:54 - What Does This All Ultimately Mean? ...

S-Risks: Fates Worse Than Extinction

May 4, 2024 5:30 pm

The worst futures that could come about aren't ones in which humanity goes extinct. This video explores an even worse category of risks: risks from astronomical suffering, or "S-Risks", which involve an astronomical number of beings suffering terribly. Researchers on this topic argue that S-risks have a significant chance of occurring and that there are ways to lower that chance.

▀▀▀▀▀▀▀▀▀SOURCES & READINGS▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀

Existential Risk Prevention as Global Priority: https://existential-risk.com/concept.pdf

Reducing Risks of Astronomical Suffering: A Neglected Priority https://longtermrisk.org/reducing-risks-of-astronomical-suffering-a-neglected-priority

S-risks: An introduction: https://centerforreducingsuffering.org/research/intro/

Moral circle expansion: A promising strategy to impact the far future: https://doi.org/10.1016/j.futures.2021.102756

Superintelligence as a Cause or Cure for Risks of Astronomical Suffering: https://longtermrisk.org/files/Sotala-Gloor-Superintelligent-AI-and-Suffering-Risks.pdf

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Specification Gaming: How AI Can Turn Your Wishes Against You

December 1, 2023 8:50 pm

When we specify goals for AIs, we must ensure that our specifications truly capture what we want. Otherwise, the behavior of AI systems will be different from what we want them to do. This can be catastrophic in high-stakes situations and at high levels of AI capability. If you watched our video "The Hidden Complexity of Wishes", you'll recognize these problems as the same kind of failure.

If you’d like to skill up on AI Safety, we highly recommend the AI Safety Fundamentals courses by BlueDot Impact at https://aisafetyfundamentals.com

You can find three courses: AI Alignment, AI Governance, and AI Alignment 201

You can follow AI Alignment and AI Governance even without a technical background in AI. AI Alignment 201, instead, presupposes having followed the AI Alignment course first, and equivalent knowledge as having followed university-level courses on deep learning and reinforcement learning.

The courses consist of a selection of readings curated by experts in AI safety. They are available to all, so you can simply read them if you can’t formally enroll in the courses.

If you want to participate in the courses instead of just going through the readings by yourself, BlueDot Impact runs live courses which you can apply to. The courses are remote and free of charge. They consist of a few hours of effort per week to go through the readings, plus a weekly call with a facilitator and a group of people learning from the same material. At the end of each course, you can complete a personal project, which may help you kickstart your career in AI Safety.

BlueDot impact receives more applications that they can take, so if you’d still like to follow the courses alongside other people you can go to the study-buddy channel in the AI Alignment Slack. You can join by clicking on the first entry on https://aisafety.community

You could also join Rational Animations’ Discord server at discord.gg/rationalanimations, and see if anyone is up to be your partner in learning.

#ai #aisafety #alignment

▀▀▀▀▀▀▀▀▀SOURCES & READINGS▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀

9 Examples of Specification Gaming by @RobertMilesAI: https://youtu.be/nKJlF-olKmg

Specification gaming: the flip side of AI ingenuity by Victoria Krakovna, Jonathan Uesato, Vladimir Mikulik et al. (2020): https://www.deepmind.com/blog/specification-gaming-the-flip-side-of-ai-ingenuity

Learning from Human Preferences by Paul Christiano, Alex Ray and Dario Amodei (2017): https://openai.com/blog/deep-reinforcement-learning-from-human-preferences/

Learning to Summarize with Human Feedback by Jeffrey Wu, Nisan Stiennon, Daniel Ziegler et al. (2020): https://openai.com/blog/learning-to-summarize-with-human-feedback/

What failure looks like by Paul Christiano (2019): https://www.alignmentforum.org/posts/HBxe6wdjxK239zajf/what-failure-looks-like

The alignment problem from a deep learning perspective by Richard Ngo, Soeren Mindermann and Lawrence Chan (2022): https://arxiv.org/abs/2209.00626

The Hidden Complexity of Wishes: https://youtu.be/gpBqw2sTD08

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That Alien Message

September 7, 2024 4:33 pm

This video is an adaptation of "That Alien Message", a short story published by Eliezer Yudkowsky in 2008. The text has been adapted, and you can find the original here: https://www.lesswrong.com/posts/5wMcKNAwB6X4mp9og/that-alien-message

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Sorting Pebbles Into Correct Heaps - A Short Story By Eliezer Yudkowsky

January 10, 2023 6:00 pm

Sorting Pebbles Into Correct Heaps is a short story published by Eliezer Yudkowsky in the year 2008. It is about... what is it about again?

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The Parable of the Dagger

July 29, 2023 4:02 pm

This is an animation of The Parable of the Dagger by Eliezer Yudkowsky. You can read the original here: https://www.readthesequences.com/The-Parable-Of-The-Dagger

It's the beginning of a series of essays about language. We highly recommend them, and you can read them here: https://www.readthesequences.com/A-Humans-Guide-To-Words-Sequence

You can read many more essays and stories by Eliezer Yudkowsky at https://readthesequences.com

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Will AI kill everyone? Here's what the godfathers of AI have to say

August 19, 2023 5:27 pm

In this video, we examine the perspectives of the "godfathers of AI"—Geoffrey Hinton, Yoshua Bengio, and Yann LeCun—about whether AI poses an existential risk to humanity. Additionally, we explore the views of the top three leading AI labs: Anthropic, Google DeepMind, and OpenAI. We conclude with a quote from Alan Turing, the father of computer science.

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▀▀▀▀▀▀▀▀▀SOURCES▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀

How Rogue AIs may Arise, by Yoshua Bengio: https://yoshuabengio.org/2023/05/22/how-rogue-ais-may-arise/

Statements from Geoffrey Hinton: https://edition.cnn.com/2023/05/01/tech/geoffrey-hinton-leaves-google-ai-fears/index.html

Yann LeCun's Tweets:
- https://twitter.com/ylecun/status/1651944213385453570
- https://twitter.com/ylecun/status/1642206111464927239

Demis Hassabis' interview with Time: https://time.com/6246119/demis-hassabis-deepmind-interview/

Anthropic's "Core Views on AI Safety": https://www.anthropic.com/index/core-views-on-ai-safety

OpenAI's "Planning for AGI and Beyond": https://openai.com/blog/planning-for-agi-and-beyond

Intelligent Machinery, A Heretical Theory, by A.M. Turing: https://rauterberg.employee.id.tue.nl/lecturenotes/DDM110%20CAS/Turing/Turing-1951%20Intelligent%20Machinery-a%20Heretical%20Theory.pdf

▀▀▀▀▀▀▀▀▀SOCIAL & DISCORD▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀

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רם רינגל

▀▀▀▀▀▀▀CREDITS▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀

Animation director: Evan Streb
Writer: Jai
Producer: :3

Production Managers:
Grey Colson
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Line Producer:
Kristy Steffens

Quality Assurance Lead:
Lara Robinowitz

Animation:
Grey Colson
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Jodi Kuchenbecker
Jay McMichen
Skylar O'Brien
Vaughn Oeth
Lara Robinowitz

Background Art:
Olivia Wang

Compositing:
Grey Colson

Voices:
Robert Miles - Narrator

VO Editing:
Tony Di Piazza

Sound Design and Music:
Epic Mountain ...

How to Upload a Mind (In Three Not-So-Easy Steps)

November 7, 2023 11:09 pm

Welcome to our tutorial on mind uploading. Follow all the steps, and you should be good to go.

▀▀▀▀▀▀▀▀▀PATREON, MEMBERSHIP, KO-FI▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀

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▀▀▀▀▀▀▀▀▀SOURCES & READINGS▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀

Turing, A.M. (1937), On Computable Numbers, with an Application to the Entscheidungsproblem. Proceedings of the London Mathematical Society, s2-42: 230-265. https://doi.org/10.1112/plms/s2-42.1.230

Sandberg, A. & Bostrom, N. (2008): Whole Brain Emulation: A Roadmap, Technical Report 2008‐3, Future of Humanity Institute, Oxford University https://www.fhi.ox.ac.uk/brain-emulation-roadmap-report.pdf

Francesco Randi, Anuj K Sharma, Sophie Dvali, and Andrew M Leifer (2022): Neural signal propagation atlas of C. elegans, arXiv:2208.04790 [q-bio.NC]

Rafi Letzter, “After Break with MIT, Nectome clarifies it has no immediate plans to upload brains”
https://www.livescience.com/62212-nectome-grant-mit-founder.html

Eth, D., Foust, J., & Whale, B. (2013). The Prospects of Whole Brain Emulation within the next Half-Century. Journal of Artificial General Intelligence, 4(3) 130-152. DOI: 10.2478/jagi-2013-0008

“Dendritic computations captured by an effective point neuron model”, Songting Li et. al. 2019 https://doi.org/10.1073/pnas.1904463116

NVIDIA ADA GPU ARCHITECTURE, https://images.nvidia.com/aem-dam/Solutions/geforce/ada/nvidia-ada-gpu-architecture.pdf

Beniaguev, D., Segev, I., & London, M. (2021). Single cortical neurons as deep artificial neural networks. Neuron, 109(17), 2727-2739.e3. https://doi.org/10.1016/j.neuron.2021.07.002

Joseph Carlsmith, 2020. “How Much Computational Power Does It Take to Match the Human Brain?”
https://www.openphilanthropy.org/research/how-much-computational-power-does-it-take-to-match-the-human-brain/

Top supercomputers 2022: https://www.top500.org/lists/top500/2022/06/
Projections of top supercomputing power: https://www.top500.org/statistics/perfdevel/


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▀▀▀▀▀▀▀CREDITS▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀
Producer: :3

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Jay McMichen
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Animation Director: Evan Streb

QA Lead: Lara Robinowitz
Grey Colson
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Background Art: Olivia Wang

Compositing:
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Narrator: Robert Miles

VO Editor: Tony DiPiazza

Sound Design and Music: Epic Mountain


▀▀▀▀▀▀▀CHAPTERS▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀
Chapters:

0:00 - The masterplan
1:30 - Scanning
4:25 - Interpretation
6:25 - Running the emulation
8:38 - Which one first? ...