LessWrong posts by zvi

Periodically I like to gather various observations about writing, and share my perspective. Last time was in honor of my trip to Inkhaven. This time will be in honor of the announcement of Inkhaven #3, which I encourage everyone to apply to. I doubt I will be able to usefully be an advisor, but you never know.

This is not the ‘here is my core process’ post, although there are hints throughout as there always are. I’ll do that at some point.

Previously in series: On Writing #1, On Writing #2.

Table of Contents


You Still Got It.

How Scott Sumner Writes.

How Scott Alexander Writes.

How Jasmine Sun Writes.

How Various Famous Writers Write.

How Nabeel Qureshi Defines Great Writing.

Quickly, There's No Time.

If At First.

Writers Have A Harder Time Influencing, But It Can Still Be Done.

It's Not (Only) The Incentives, It's (Also) You.

Beware The Fetish of the Desk.

How Orson Scott Card Writes.

Doing The Math Is Fun And Supererogatory.

Brevity is the Soul of Wit.

You Still Got It

I [...]
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Outline:
(00:44) You Still Got It
(04:04) How Scott Sumner Writes
(06:52) How Scott Alexander Writes
(10:52) How Jasmine Sun Writes
(13:16) How Various Famous Writers Write
(14:24) How Nabeel Qureshi Defines Great Writing
(15:08) Quickly, There's No Time
(15:49) If At First
(19:14) Writers Have A Harder Time Influencing, But It Can Still Be Done
(20:47) It's Not (Only) The Incentives, It's (Also) You
(24:00) Beware The Fetish of the Desk
(25:13) How Orson Scott Card Writes
(26:46) Doing The Math Is Fun And Supererogatory
(27:44) Brevity is the Soul of Wit
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First published:

August 25th, 2026


Source:

https://www.lesswrong.com/posts/rA6pqn6kz8NvHyznT/on-writing-3

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Narrated by TYPE III AUDIO.

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There are at least five different core questions around data centers and their politics.


In what ways are specific concerns people raise about data centers legitimate?

In what ways are specific concerns people raise about generative AI legitimate?

Is it in general a good idea to build more data centers?

How can we get America to build more (or less) data centers in a better way?

Why do the American people increasingly really, really hate data centers?

This post focuses on question five, the latest in a series of such posts most famously Jasmine Sun's road trip.

It is mostly not about the first four questions.

Table of Contents


The American People Really Hate Data Centers.

Transmission Lines Are The Control Group.

Thesis: People Mostly Dislike Data Centers Because They Dislike and Distrust AI, Tech Companies, Big Money And Building Things.

No It's Mostly Not the Messaging About AI In General.

No This Mostly Isn’t An Op.

No This Isn’t Luxury Belief or Moral Panic.

A Lot Of People Really Do Want To Stop AI.

A Lot Of Other People [...]
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Outline:
(00:55) The American People Really Hate Data Centers
(02:20) Transmission Lines Are The Control Group
(03:05) Thesis: People Mostly Dislike Data Centers Because They Dislike and Distrust AI, Tech Companies, Big Money And Building Things
(04:30) No It's Mostly Not the Messaging About AI In General
(09:42) No This Mostly Isn't An Op
(10:54) No This Isn't Luxury Belief or Moral Panic
(12:55) A Lot Of People Really Do Want To Stop AI
(13:45) A Lot Of Other People Are Voting No On Tech Or The Man Generally
(16:25) Locals Feel Entitled To Heavily Tax The Gains From Construction
(20:59) Stupid Mistakes Like NDAs Don't Help
(21:25) People Don't Like Building or Building New Tech
(24:42) What About The Real Physical Concerns?
(26:27) Find A Place To Center Your Data
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First published:

August 24th, 2026


Source:

https://www.lesswrong.com/posts/EDKw7KyonrvskqZ7o/the-american-people-really-hate-data-centers

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Scott Aaronson, while working at OpenAI, largely solved AI text watermarking together with Hendrik Kirchner.

Here is how his solution works, or see Tenobrus's version.


AI outputs are not deterministic. The AI's job is to pick the probability of each potential next token. The token is then chosen at random.

By default you use a source of pseudo-randomness for each choice, since actual true randomness is annoying.

To apply the watermark, you use an otherwise identical private source of pseudo-randomness derived from a secret key.

Then, given enough text, a score is derived for howe well the choices fit with that particular pseudo-randomness source, versus a different source.

You provide an API that lets anyone check for the watermark.

If you want to dig deeper, here is a full paper. The method has very nice properties:


This has no practical impact on outputs. Humans cannot tell the difference, at all.

The marginal cost of doing this is very close to zero.

The watermark can be removed by rewriting in your own words, and appears in proportion to how many of the AI's detail choices you [...]
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Outline:
(03:51) This Is Fine
(04:37) Anthropic Derangement Syndrome
(07:34) People Don't Understand LLM Outputs Are Already Random
(08:47) People Don't Trust The Method To Be Costless
(12:20) People Are Suspicious Of Any Alteration On Principle
(14:16) Maybe It's Partly The Word Watermark
(15:14) A Lot Of People Don't Want To Get Caught
(16:04) There Are Some Times You Prefer Not To Be Recognized
(16:18) There Are Some Good Reasons To Be Concerned
(16:37) Cheat Cheat Cheat Cheat Cheat
(18:38) The Writing In The Middle and Error Rates
(21:00) Millions For Defense But Not One Cent For Tribute
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First published:

August 21st, 2026


Source:

https://www.lesswrong.com/posts/3mKuPHmaK7NW3QypR/ai-text-watermarking-is-free-and-good

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This was a week of quiet aftermath, an opportunity to process recent events and start to figure out the path forward.

OpenAI is attempting to turn its ship around. Investors are questioning the turnover in its C-suite, but the bigger problems are in alignment, infrastructure and supervision, and in its training pipeline. OpenAI has now taken initial steps to address What Happened leading up to HuggingFace attack, including pauses to development while new safeguards are put in place and problems are diagnosed. These are promising early signs, but it is early. We will see if they follow through, and we still await the post-mortem of the HuggingFace attack.

Anthropic revenue continues to climb as they prepare for their IPO, although growth has slowed somewhat recently. However, they too have plenty of problems under the hood. They shared many of them in the August 2026 Anthropic Risk Report.

This week also offered time to cover Dwarkesh Patel's Podcast With Ryan Greenblatt, centrally on the potential for AI recursive self-improvement. I am working on a follow-up post to some other issues raised during that podcast.

Table of Contents


Language Models Offer Mundane Utility. The token [...]
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Outline:
(01:20) Language Models Offer Mundane Utility
(02:20) Language Models Don't Offer Mundane Utility
(02:56) Huh, Upgrades
(05:55) On Your Marks
(09:22) Deepfaketown and Botpocalypse Soon
(16:23) Hello, Fellow Humans
(19:00) Fun With Media Generation
(20:43) Cyber Lack of Security
(22:56) A Young Lady's Illustrated Primer
(24:09) They Took Our Jobs
(26:18) Get Involved
(27:36) Introducing
(27:49) In Other AI News
(29:55) Show Me the Money
(32:54) And It's Gone
(34:50) Quiet Speculations
(38:41) Quickly, There's No Time
(39:27) Singularity Singularity Singularity Singularity Oh I Don't Know
(40:37) The Quest for Sane Regulations
(45:55) Chip City
(47:08) The Week in Audio
(47:44) People Just Say Things
(50:08) Rhetorical Innovation
(55:04) Loyalty Uber Alles
(58:15) A Hive Of Scum And Villainy
(01:03:10) That Would Be Bad Therefore It Won't Work
(01:05:32) Robert Reich Uses Simple Logic
(01:08:03) People Really Hate AI
(01:08:31) Coordinating An Agent Swarm Is Difficult
(01:13:14) Aligning a Smarter Than Human Intelligence is Difficult
(01:14:37) It's Not The Incentives, It's You, Also It's The Incentives
(01:16:32) People Are Worried About AI Killing Everyone
(01:16:58) People Are Worried About So, So Many Other Things Too
(01:21:58) Cooperative Alignment
(01:22:50) The Lighter Side
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First published:

August 20th, 2026


Source:

https://www.lesswrong.com/posts/JSZkzsi8cD4pW6ffA/ai-182-pause-for-reflection

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OpenAI has some severe misalignment problems, and experienced total failures of its infrastructure and supervision.

I chronicled that in a series of posts, which also cover similar less severe incidents elsewhere:


OpenAI Shares Some Alignment Problems

OpenAI Model Hacks Into HuggingFace During Cybersecurity Evaluation

More on An Internal OpenAI Model Hacking Into HuggingFace

Further Developments About Internal AI Models Hacking Things

OpenAI Trained Its Models For Months While Those Models Were Coordinating Exploits Via Message Boards

What Happened: OpenAI and HuggingFace.

Various Reflections About What Happened With OpenAI's Internal Models.

If you do not know the basics, read What Happened. It is necessary context for basically everything that is happening in the AI world.

It is important to get this right and understand how big a deal it was, whereas many such as the Financial Times get this centrally wrong.

We are still awaiting the full post-mortem on What Happened. I plan to cover that in depth once we have it.

OpenAI is now taking active, expensive steps to try and fix the problem going forward.

As usual, I am simultaneously happy to see [...]
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Outline:
(02:07) OpenAI Has Some Alignment Problems
(04:22) Slow Down There Good Buddy
(10:12) What Exactly Is Paused?
(12:12) Three Pillars
(14:45) I've Got My Eye On You
(18:07) The Most Forbidden Technique
(20:03) Monitoring Is Only Defense-In-Depth
(23:32) Security
(24:15) Alignment
(30:37) A Crisis of Culture
(32:24) Closer Collaboration
(33:28) Reports of Death of Preparedness Team Greatly Exaggerated
(35:40) The OpenAI Foundation Just Funds Things
(37:51) Quickly, There's No Time
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First published:

August 19th, 2026


Source:

https://www.lesswrong.com/posts/X3p8cFAzCgRErEcJr/openai-takes-initial-steps-to-address-its-alignment-problems

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Narrated by TYPE III AUDIO.