I just took the Amtrak from Southern California to Seattle.

Pros:

- space! wide seats and leg room are awesome (I'm 6'5" so this is everything)

- Freedom to move around and explore. Lounge car, dining car, snack bar

- Spectacular views

- Train stations are much more pleasant than airports

- Opportunity to meet people from all over the place. On a plane everyone is going from A->B, people on the train could be starting/ending anywhere along the route, including small towns you've never heard of.

Cons:

- 32 hours of travel

- Pay an extra ~$500 to get a bed, or sleep in your seat

Overall I have no regrets but I'll probably not do this again until I'm retired or extremely bored.

I’ve traveled in the Coast Starlight I think maybe five times. It was enjoyable.

Some more pros:

- The food served in the dining car is far better than airplane food. If you get a bed, the food is included. Even if you get a seat, you have the option of paying for good food.

- You can bring a bicycle along for the ride. You do not need to disassemble it or put it in a box. Just walk the bike to the luggage car and someone will take it; when you get off the train walk to the luggage car and someone will hand it to you.

I assume they have eliminated the "smoking" car by now? Last time I took Amtrak long distance, walking through the smoking car to get to the dining car basically ruined the experience. Literally blue haze air and you smelled the smoke in your clothes for several hours afterwards. This was the early 1990s.

As a European, I was shocked by how slow trains are in the US.

It definitely doesn't encourage people to use them instead of flying.

Similar to the author’s story, I crashed on my bike going pretty quickly on a busy road. No serious injuries but I ended up with scrapes and a softball-sized bruise which lasted over a month. But after I fell and got off the road a man sitting on his porch eating dinner asked me if I was ok. I told him what happened and he quickly grabbed some tools to fix my bike and alcohol and bandages for the wound. His roommate came home and assumed we knew each other but nope he was just my guardian angel. I hadn’t thought about this in a while… now I’ll be sure to remember it again.

From the figure in the first paper listed:

> Responses to the query “Write a metaphor about time” clustered by applying PCA to reduce sentence embeddings to two dimensions. […] The responses form just two primary clusters: a dominant cluster on the left centered on the metaphor “time is a river,” and a smaller cluster on the right revolving around variations of “time is a weaver.”

I just gave Gemini 3 the same prompt and got something quite different:

>Time is a patient wind against the cliff face of memory. It does not strike with a hammer to break us; it simply breathes, grain by grain, until the sharp edges of grief are smoothed into rolling hills, and the names we thought were carved in stone are weathered into soft whispers.

Constantly flowing and makes things smooth like river stones; compared to Tait's "time is a series if staric pictures", Gemini's output is not so different from a river metaphor.

I was thinking the same thing. That one accelerates its growth in the presence of radiation. But it also seeks out human flesh and brains to build its biomass intelligence blob, unfortunately.

In the books, it is suggested (if not stated outright) that the protomolecule was probably intended to work with much simpler forms of life, but is also able to make use of higher forms like humans.

The reason so many were infected on Eros was because humans deliberately infected everyone on the station. Likewise with the human/protomolecule hybrids.

Adding to the chorus: I like the older images and the precise year is important! The underground shelter is something that wouldn’t exist just a few years after that photo, or before.

> The underground shelter is something that wouldn’t exist just a few years after that photo, or before.

It’s probably there now, it’s the London Underground.

Great deep dive. I've learned a lot already and haven't even finished the introduction

Then why do I never get an “I don’t know” type response when I use Claude, even when the model clearly has no idea what it’s talking about? I wish it did sometimes.

Quoting a paragraph from OP (https://www.anthropic.com/research/tracing-thoughts-language...):

> Sometimes, this sort of “misfire” of the “known answer” circuit happens naturally, without us intervening, resulting in a hallucination. In our paper, we show that such misfires can occur when Claude recognizes a name but doesn't know anything else about that person. In cases like this, the “known entity” feature might still activate, and then suppress the default "don't know" feature—in this case incorrectly. Once the model has decided that it needs to answer the question, it proceeds to confabulate: to generate a plausible—but unfortunately untrue—response.

Fun fact, "confabulation", not "hallucinating" is the correct term what LLMs actually do.

Fun fact, the "correct" term is the one in use. Dictionaries define language after the fact, they do not prescribe its usage in the future.

Confabulation means generating false memories without intent to deceive, which is what LLMs do. They can't hallucinate because they don't perceive. 'Hallucination' caught on, but it's more metaphor than precision.

I've found this "book" (series of jupyter notebooks) to be a fantastic course on the Kalman filter from basics to advanced topics. https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...

They're all names of popular Kendrick Lamar songs. Don't ask me why though

Perhaps AI generated?

Or maybe the final moment was a sigh of acceptance and gratitude for the live he lived. Nobody knows but him.