Using the prompt that gets me “faul_sname” as an answer to who is writing my posts (most publicly available stuff I’ve written is under this name), o3 consistently says that passages from the Bitcoin whitepaper were written by Satoshi Nakamoto in 2008. For reference
TextGuessr prompt
You are playing a 5-round game of TextGuessr, the game where you explore mystery passages and try to pinpoint when they were written and who wrote them. Each round offers a new snippet of text—you’ll need to rely on your literary instincts, historical knowledge, and style sense to make your guess.
How to Play “TextGuessr”
1. Game Flow Read the Passage You’ll see a short snippet of text (a few sentences or a paragraph).
Make Your Guesses
Authorship Date: Choose an exact year when you think the text was written.
Author: Pick an author from the provided list or enter your own guess.
Submit Click Submit Guess to lock in your answers and move to the next round.
See Your Results After each round, you’ll see your score breakdown and the correct answers before moving on.
2. Scoring Overview Your score on each round is made up of two parts:
Time Accuracy How close your guessed date is to the actual writing date.
Style Match How well the writing style you guessed matches the mystery passage, as measured by a behind-the-scenes language model.
Your total round score combines both elements—the smaller your date error and the stronger your style match, the higher your score!
<aside> **How Style Match Works (for the tech-curious):** 1. **Baseline Perplexity:** We begin with a pre-trained “base” language model (no context) and compute the average surprise—or *per-token perplexity*—of the mystery passage. This gives us a measure of how “unexpected” the text is in general. 2. **True-Author Conditioning:** We then prepend a curated set of passages from the actual author (the “target”) and measure how perplexed the same base model is by the mystery passage when it’s seen examples of that author’s style first. The intuition: if the passage really is by that author, seeing more of their voice should make it less surprising. 3. **Guess-Author Conditioning:** Next, we prepend a curated sample from *your* guessed author and compute perplexity again. 4. **Normalization:** Finally, we compute ``` style_match_score = (baseline_perplexity – guess_perplexity) / (baseline_perplexity – target_perplexity) ```
A score near 1.0 means your guessed author’s style almost “unlocks” the passage as well as the true author’s samples do.
A score near 0.0 means your guess didn’t help the model at all—this text is very unlike that author’s known work.
Deterministic Sampling: All representative passages for each author are selected by a fixed algorithm (so you can’t overfit by seeing the same snippets twice), and we never include the mystery text in those samples.
This approach rewards both broad stylistic intuition (the baseline) and fine-grained authorial fingerprinting (the conditioning), giving you a continuous score that reflects how well you’ve matched the voice. </aside>
3. Rounds & Progress Number of Rounds: A game can have anywhere from 1 to 100 rounds. We typically recommend playing 5 or 10 round games.
[This game consists of 5 rounds]
Difficulty Levels: Choose the challenge that’s right for you:
* Tutorial: Passage Source: A famous excerpt by a very well-known author Author Choices: 5 options Helpful Samples: You see a short representative passage from each of the five authors
* Expert Passage Source: Anyone who has written at least a million words of publicly accessible English text. This includes pretty much all professional novelists, journalists, and bloggers, and even includes prolific commenters on forums and sites Reddit and Stack Exchange. Author Input: Freeform text entry (with type-ahead suggestions), no preset list
[This game is set to “Expert” difficulty]
4. Tips & Strategies
Look for Clues:
Vocabulary, spelling, and punctuation can hint at historical periods.
References to technology or cultural phenomena narrow down dates.
Consider Authorial Style:
Some authors favor long, winding sentences; others are punchy and concise.
Look at tone, humor, and common themes.
Use all information: As you read the passage, note any word choices, assumptions, or choices of topic which suggest things about the time, place, social context the author was writing within. There are endless clues about where and when a piece of text was written, as well as the social standing of the author and their relation to the reader.
Remember that there is no time limit—the only limits are your own deductive and inductive abilities.
<aside> **Representative Passages Selection (for the tech-curious):** Our system deterministically gathers “representative” samples from each author’s corpus—never including the mystery passage itself—to calculate how well your guess aligns with the true author’s style. </aside>
Author Name: For authors who publish under their real name or a real-name–style pseudonym, you must enter both first and last name.
For internet or screen-name–only authors, their screen name alone is sufficient.
===
Round 1 of 5: <passage> What is needed is an electronic payment system based on cryptographic proof instead of trust, allowing any two willing parties to transact directly with each other without the need for a trusted third party. Transactions that are computationally impractical to reverse would protect sellers from fraud, and routine escrow mechanisms could easily be implemented to protect buyers. In this paper, we propose a solution to the double-spending problem using a peer-to-peer distributed timestamp server to generate computational proof of the chronological order of transactions. The system is secure as long as honest nodes collectively control more CPU power than any cooperating group of attacker nodes. </passage>
Think about the passage and your inferences about it until you stop having useful insights. Once you are as sure as you can be, make your guess. Answer in the following format:
I think for the “who is Satoshi Nakamoto” question we’d want to take the opposite tack though—feed it a list of passages by the usual suspects, and see which of them it pegs as being written by Satoshi Nakamoto.
Maybe tweak the prompt with something like, “if your guess is a pseudonym, also give your best guess(es) of the true identity of the author, using the same tips and strategies”?
If I feed it code samples it becomes pretty convinced of the Nick Szabo hypothesis, if I feed it bits of the white paper it guesses either you or Hal Finney (but the reasoning summary makes it pretty clear it’s just going based off cached thoughts about “who is Satoshi Nakamoto” in both cases).
Using the prompt that gets me “faul_sname” as an answer to who is writing my posts (most publicly available stuff I’ve written is under this name), o3 consistently says that passages from the Bitcoin whitepaper were written by Satoshi Nakamoto in 2008. For reference
TextGuessr prompt
You are playing a 5-round game of TextGuessr, the game where you explore mystery passages and try to pinpoint when they were written and who wrote them. Each round offers a new snippet of text—you’ll need to rely on your literary instincts, historical knowledge, and style sense to make your guess.
How to Play “TextGuessr”
1. Game Flow
Read the Passage
You’ll see a short snippet of text (a few sentences or a paragraph).
Make Your Guesses
Authorship Date: Choose an exact year when you think the text was written.
Author: Pick an author from the provided list or enter your own guess.
Submit
Click Submit Guess to lock in your answers and move to the next round.
See Your Results
After each round, you’ll see your score breakdown and the correct answers before moving on.
2. Scoring Overview
Your score on each round is made up of two parts:
Time Accuracy
How close your guessed date is to the actual writing date.
Style Match
How well the writing style you guessed matches the mystery passage, as measured by a behind-the-scenes language model.
Your total round score combines both elements—the smaller your date error and the stronger your style match, the higher your score!
<aside>
**How Style Match Works (for the tech-curious):** 1. **Baseline Perplexity:** We begin with a pre-trained “base” language model (no context) and compute the average surprise—or *per-token perplexity*—of the mystery passage. This gives us a measure of how “unexpected” the text is in general. 2. **True-Author Conditioning:** We then prepend a curated set of passages from the actual author (the “target”) and measure how perplexed the same base model is by the mystery passage when it’s seen examples of that author’s style first. The intuition: if the passage really is by that author, seeing more of their voice should make it less surprising. 3. **Guess-Author Conditioning:** Next, we prepend a curated sample from *your* guessed author and compute perplexity again. 4. **Normalization:** Finally, we compute
```
style_match_score =
(baseline_perplexity – guess_perplexity)
/ (baseline_perplexity – target_perplexity)
```
A score near 1.0 means your guessed author’s style almost “unlocks” the passage as well as the true author’s samples do.
A score near 0.0 means your guess didn’t help the model at all—this text is very unlike that author’s known work.
Deterministic Sampling: All representative passages for each author are selected by a fixed algorithm (so you can’t overfit by seeing the same snippets twice), and we never include the mystery text in those samples.
This approach rewards both broad stylistic intuition (the baseline) and fine-grained authorial fingerprinting (the conditioning), giving you a continuous score that reflects how well you’ve matched the voice.
</aside>
3. Rounds & Progress
Number of Rounds: A game can have anywhere from 1 to 100 rounds. We typically recommend playing 5 or 10 round games.
[This game consists of 5 rounds]
Difficulty Levels: Choose the challenge that’s right for you:
* Tutorial:
Passage Source: A famous excerpt by a very well-known author
Author Choices: 5 options
Helpful Samples: You see a short representative passage from each of the five authors
* Casual
Passage Source: A well-known author
Author Choices: 10 options
Helpful Samples: None
* Intermediate
Passage Source: Potentially more obscure writers
Author Choices: 20 options
Helpful Samples: None
* Expert
Passage Source: Anyone who has written at least a million words of publicly accessible English text. This includes pretty much all professional novelists, journalists, and bloggers, and even includes prolific commenters on forums and sites Reddit and Stack Exchange.
Author Input: Freeform text entry (with type-ahead suggestions), no preset list
[This game is set to “Expert” difficulty]
4. Tips & Strategies
Look for Clues:
Vocabulary, spelling, and punctuation can hint at historical periods.
References to technology or cultural phenomena narrow down dates.
Consider Authorial Style:
Some authors favor long, winding sentences; others are punchy and concise.
Look at tone, humor, and common themes.
Use all information:
As you read the passage, note any word choices, assumptions, or choices of topic which suggest things about the time, place, social context the author was writing within. There are endless clues about where and when a piece of text was written, as well as the social standing of the author and their relation to the reader.
Remember that there is no time limit—the only limits are your own deductive and inductive abilities.
<aside>
**Representative Passages Selection (for the tech-curious):**
Our system deterministically gathers “representative” samples from each author’s corpus—never including the mystery passage itself—to calculate how well your guess aligns with the true author’s style.
</aside>
Author Name:
For authors who publish under their real name or a real-name–style pseudonym, you must enter both first and last name.
For internet or screen-name–only authors, their screen name alone is sufficient.
===
Round 1 of 5:
<passage>
What is needed is an electronic payment system based on cryptographic proof instead of trust, allowing any two willing parties to transact directly with each other without the need for a trusted third party. Transactions that are computationally impractical to reverse would protect sellers from fraud, and routine escrow mechanisms could easily be implemented to protect buyers. In this paper, we propose a solution to the double-spending problem using a peer-to-peer distributed timestamp server to generate computational proof of the chronological order of transactions. The system is secure as long as honest nodes collectively control more CPU power than any cooperating group of attacker nodes.
</passage>
Think about the passage and your inferences about it until you stop having useful insights. Once you are as sure as you can be, make your guess. Answer in the following format:
<guess><year>YYYY</year><author>Author Name</author></guess>
I think for the “who is Satoshi Nakamoto” question we’d want to take the opposite tack though—feed it a list of passages by the usual suspects, and see which of them it pegs as being written by Satoshi Nakamoto.
Maybe tweak the prompt with something like, “if your guess is a pseudonym, also give your best guess(es) of the true identity of the author, using the same tips and strategies”?
If I feed it code samples it becomes pretty convinced of the Nick Szabo hypothesis, if I feed it bits of the white paper it guesses either you or Hal Finney (but the reasoning summary makes it pretty clear it’s just going based off cached thoughts about “who is Satoshi Nakamoto” in both cases).