LessWrong (Curated & Popular)

Example 1: The Viking 1 lander

In the 1970s, NASA sent a pair of probes to Mars, Viking 1 and Viking 2 missions, at a total cost of 1 billion dollars[1970], equivalent to about 7 billion dollars[2025]. The Viking 1 probe operated on Mars's surface for six years, before its battery began to seriously degrade.

One might have thought a battery problem like that would spell the irrevocable end of the mission. The probe had already launched and was now on Mars, very far away and out of reach of any human technician's fixing fingers. Was it not inevitable, then, that if any kind of technical problem were to be discovered long after the space launch in August 1975, nothing could possibly be done?

But the foresightful engineers of the Viking 1 probe had devised a plan for just this class of eventuality, which they had foreseen in general, if not in exact specifics. They had built the Viking 1 probe to accept software updates by radio receiver, transmitted from Earth.

On November 11, 1982, Earth sent an update to the Viking 1 lander's software, intended to make sure the battery only discharged down to a minimum voltage level [...]

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Outline:

(00:13) Example 1: The Viking 1 lander

(04:25) Example 2: The Mars Observer

(11:37) Example 3: The Maginot Line

(15:37) Other supposed refutations of oneshotness

(24:16) On the extraordinary efforts put forth to misinterpret the idea of oneshotness

(33:52) The secret sauce of competent engineers in Murphy-cursed fields: only trying projects so incredibly straightforward as to be actually possible.

The original text contained 7 footnotes which were omitted from this narration.

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First published:

May 4th, 2026


Source:

https://www.lesswrong.com/posts/fbrz9xhKpEeTKw5zL/irretrievability-or-murphy-s-curse-of-oneshotness-upon-asi

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Narrated by TYPE III AUDIO.

How much do cows suffer in the production of milk? I can’t answer that; understanding animal experience is hard. But I can at least provide some facts about the conditions dairy cows live in, which might be useful to you in making your own assessment. My biggest conclusion is that cows made better choices than chickens by making their misery financially costly to farmers.

Life Cycle

The life of a dairy cow starts as a calf. She is typically separated from her mother a few hours to a few days after birth and, to reduce disease risk, held in isolation. Cutting edge farms will sometimes house calves in pairs. This isolation is clearly stressful for a baby herd mammal and her mother, but I didn’t find any quantification of that stress that I trusted.

Calves will be bottlefed until weaning at 6-8 weeks (4-6 months earlier than beef calves). After weaning and vaccinations they can be introduced into a herd. At large farms (where most cows live), they will move in and out of different herds through their lifecycle. This is more stressful than being embedded with your friends for life, but again, I found no [...]

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Outline:

(00:44) Life Cycle

(02:43) How much time do dairy cows spend outside?

(04:21) By humaneness standard

(06:00) When indoors, how confined are dairy cows?

(06:33) What is the disease load of dairy cows?

(08:15) Euthanasia

[... 5 more sections]

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First published:

May 3rd, 2026


Source:

https://www.lesswrong.com/posts/r3PKfvKCjy6jok4qm/dairy-cows-make-their-misery-expensive-but-their-calves-can

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Narrated by TYPE III AUDIO.

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I spent my last two months playing around with LLMs. I’m a beginner, bumbling and incorrect, but I want to share some takes anyhow.[1]

Take 1. Everything with computers is so so much easier than it was a year ago. 

This puts much “playing with LLMs” stuff within my very short attention span. This has felt empowering and fun; 10/10 would recommend.

There's a details box here with the title "Detail:". The box contents are omitted from this narration. Take 2. There's somebody home[2] inside an LLM. And if you play around while caring and being curious (rather than using it for tasks only), you’ll likely notice footprints.

I became personally convinced of this when I noticed that the several short stories I’d allowed[3] my Claude and Qwen instances to write all hit a common emotional note – and one that reminded me of the life situation of LLMs, despite featuring only human characters. I saw the same note also in the Tomas B.-prompted Claude-written story I tried for comparison. (Basically: all stories involve a character who has a bunch of skills that their context has no use for, and who is attentive to their present world's details [...]

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Outline:

(00:20) Take 1. Everything with computers is so so much easier than it was a year ago.

(00:44) Take 2. Theres somebody home inside an LLM. And if you play around while caring and being curious (rather than using it for tasks only), youll likely notice footprints.

(02:05) Take 3. Its prudent to take an interest in interesting things. And LLMs are interesting things.

(03:25) Take 4. Theres a surprisingly deep analogy between humans and LLMs

(04:20) Examples of the kind of disanalogies I mightve expected, but havent (yet?) seen:

(06:02) Human-LLM similarities I do see, instead:

(06:08) Functional emotions

(06:33) Repeated, useful transfer between strategies I use with humans, and strategies that help me with LLMs

(08:02) Take 5. Friendship-conducive contexts are probably better for AI alignment

(08:46) Why are humans more likely to attempt deep collaboration if treated fairly and kindly?

(10:23) Friendship as a broad attractor basin?

(10:49) Does the deep intent of todays models matter?

(12:09) Concretely

(14:56) Friendship isnt enough

The original text contained 8 footnotes which were omitted from this narration.

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First published:

April 28th, 2026


Source:

https://www.lesswrong.com/posts/K8JMjE4PCqMkkCDsd/takes-from-two-months-as-an-aspiring-llm-naturalist

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The future is going to be different from the present. Let's think about how.

Specifically, our expectations about what's reasonable are downstream of our past experiences, and those experiences were downstream of our options (and the options other people in our society had). As those options change, so too our experiences, and our expectations of what's reasonable. I once thought it was reasonable to pick up the phone and call someone, and to pick up my phone when it rang; things have changed, and someone thinking about what's possible could have seen it coming. So let's try to see more things coming, and maybe that will give us the ability to choose what it will actually look like.

I think lots of people's intuitions and expectations about "privacy" will be violated, as technology develops, and we should try to figure out a good spot to land. This line of thinking was prompted by one of Anthropic's 'red lines' that they declined to cross, which got the Department of War mad at them; the idea of "no domestic bulk surveillance." I want to investigate that in a roundabout way, first stepping back and asking what is even possible to expect [...]

The original text contained 6 footnotes which were omitted from this narration.

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First published:

April 1st, 2026


Source:

https://www.lesswrong.com/posts/rNpGFodLTFvhqLmK6/intelligence-dissolves-privacy

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Written as part of the MATS 9.1 extension program, mentored by Richard Ngo.

From March 9th to 15th 2016, Go players around the world stayed up to watch their game fall to AI. Google DeepMind's AlphaGo defeated Lee Sedol, commonly understood to be the world's strongest player at the time, with a convincing 4-1 score.

This event “rocked” the Go world, but its impact on the culture was initially unclear. In Chess, for instance, computers have not meaningfully automated away human jobs. Human Chess flourished as a pseudo-Esport in the internet era whereas the yearly Computer Chess Championship is followed concurrently by no more than a few hundred nerds online. It turns out that the game's cultural and economic value comes not from the abstract beauty of top-end performance, but instead from human drama and engagement. Indeed, Go has appeared to replicate this. A commentary stream might feature a complementary AI evaluation bar to give the viewers context. A Go teacher might include some new intriguing AI variations in their lesson materials. But the cultural practice of Go seemed to remain largely unaffected.

Nascent signs of disharmony in Europe became nevertheless visible in early 2018, when the online [...]

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Outline:

(09:23) AI users never find out they havent got it.

(13:36) Appendix A: No, Go players arent getting stronger

(14:41) Appendix B: Why this article exists

The original text contained 2 footnotes which were omitted from this narration.

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First published:

May 1st, 2026


Source:

https://www.lesswrong.com/posts/nR3DkyivzF4ve97oM/how-go-players-disempower-themselves-to-ai

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Narrated by TYPE III AUDIO.