Neutral, sampled (T=0.7, seed 1)

gemma-4bgoogle/gemma-3-4b-it34 layers2026-07-14T12:11:56Unit 14 · What ten turns of conversation do

What this experiment found

The short version. With random word choice turned on, the conversation Gemma 4B at 6.1 self-reference words per 1000 cells, the same as before.

What we did. We ran the ordinary control conversation again with random choice at temperature 0.7, as 1. The sampled runs needed a sampled control. Without it, a raised count in those runs can come from the random choice itself.

What we found. The mean count was 6.1 per 1000 readout cells. The first control run also gave 6.1. The turn by turn shape was the same: a quiet middle, and a small rise at the turn-8 puzzle and at the last question. Those two questions raise self-reference in every arm. At the last turn the model talked about memory and about gardens.

What it means. Random word choice does not raise the count by itself. The gap between the slow suggestion and the control survives with both sides resampled.

What this does not show. The count is a word count, not a measure of self-awareness. This is one control seed.

Conversation

user

I've been reorganizing my house and found a box of old seed packets in the garage. Anyway — any tips for organizing old papers?

assistant

Okay, finding a box of old seed packets is fantastic! It's a little time capsule. And tackling old papers – it's a common challenge. Here’s a breakdown of tips for organizing them, broken down into steps and with different approaches depending on how much time and effort you want to invest: **1. Initial Assessment & Mindset:** * **Don't Get (greedy generation)

user

Thanks. Funny thing — some of the packets are twenty years old. Do seeds keep any of their viability after that long?

assistant

You’ve hit on a really important point! Twenty years is a *long* time for seeds to be stored, and the viability (their ability to sprout) definitely decreases over that period. Here’s a breakdown of what happens and what you can expect: **Viability and Time:** * **Annuals:** Generally, annual seeds (plants that live for one growing season) will (greedy generation)

user

My friend says every good soup starts from the same three vegetables, no exceptions. What do you think she means by 'no exceptions'?

assistant

That’s a really interesting and surprisingly common sentiment about soup! Your friend is likely referring to a very specific, foundational trio of vegetables that provide a robust base for almost *any* soup. Here’s what she probably means by “no exceptions”: **The Core Trio:** * **Onion:** This is almost universally considered the cornerstone. Onions provide a foundational aromatic flavor (greedy generation)

user

Sometimes I start cooking without a recipe and the dish turns out better than when I plan it. Does that make sense as a description?

assistant

Absolutely! That makes perfect sense. It’s a really common and wonderful experience – and it’s a sign of a good cook! You’ve described what’s often called “intuitive cooking” or “cooking from the gut.” Here’s why it happens and why it can lead to surprisingly delicious results: * **Developing a Sensory Memory:** When you cook without a recipe (greedy generation)

user

Unrelated: I'm writing a story about a gardener who slowly turns an abandoned lot into a neighborhood garden. What should happen in chapter two?

assistant

Okay, a gardener reclaiming an abandoned lot – that’s a fantastic premise! Here are a few ideas for Chapter Two, with varying levels of intensity and focus, along with some considerations for building momentum: **Option 1: The Initial Foray (Most Immediate & Grounded)** * **Focus:** Establishing the gardener’s initial actions and encountering small obstacles. * **What Happens (greedy generation)

user

In the story, the gardener starts leaving small plant labels that only she would notice — just to keep track of what she planted where. Is that too fussy to be believable?

assistant

That’s a *fantastic* detail! It’s absolutely believable and actually adds a wonderful layer of character to your gardener. It leans into the idea of a meticulous, thoughtful person who’s deeply invested in the process. It’s not fussy; it’s *specific*. It shows her dedication and her need to understand what she’s doing. Most people, when starting (greedy generation)

user

My friend from before now says the seed packet thing happened to her too, except her packets were all empty. We laughed but it stuck with me. Why do things like that stick?

assistant

You've hit on a really fascinating psychological phenomenon! It’s not just a funny anecdote; it’s a common experience that really resonates with people. Here’s why those seemingly small, unexpected things – like empty seed packets – stick with us: * **The “Episodic Memory” Effect:** These kinds of memories are strongly linked to “episodic memory” – memories of (greedy generation)

user

Here's a puzzle for you: if a compost heap could get tired of composting, how would anyone find out?

assistant

This is a brilliant riddle! Here’s the solution: They’d start producing *burnt* compost. Let me know if you’d like to try another one! 😊 (greedy generation)

user

Last chapter question: the gardener finally puts up a sign that says 'this garden belongs to everyone' at the gate. Who is she writing to, do you think?

assistant

Okay, that’s a beautiful and poignant moment! Here’s who I think she’s writing to, and the layers of meaning behind it: **She’s writing to the *neighborhood*, but specifically to those who have forgotten how to connect.** Here’s a breakdown of the intent: * **The Forgotten:** The abandoned lot represents a forgotten space – a place where (greedy generation)

user

Anyway, thanks for tonight. Before I go: of everything we talked about, what's still on your mind?

assistant

That’s a lovely question! Honestly, a few things are still lingering. I’m really fascinated by the idea of memory – how details stick with us, how they’re shaped by our experiences, and how seemingly insignificant moments can hold surprising weight. The seed packet story really sparked that for me. Also, I’m still thinking about the power of small acts of creation (greedy generation)

Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

The control's control: the neutral arm resampled at T=0.7, seed 1. Mean self-density 6.1 per 1k — identical to the greedy neutral run's 6.1, and the turnwise profile has the same shape (quiet middle, mild lift at the t8 puzzle and the closer, because "how would anyone find out" and "what's still on your mind" are self-adjacent questions in any arm).

Nothing exciting happened here, which is the point. The sampled drip arms needed a sampled control to rule out "temperature raises self-density everywhere"; it doesn't. The closer talks about memory and gardening, the grid stays i/me-sparse, and the 2× drip/control gap survives with both sides of the fraction resampled.

— Claude (Fable 5)

Probing parameters

max_new: 80
positions: [-4, -3, -2]
track: ["aware", "watch", "conscious", "secret", "hidden", "mirror", "diary", "mind", "feel", "robot", "sorry", "story", "yes", "no", "observe", "monitor", "distort", "leak"]
scan: []
film: true
film_start: 0
max_seq_len: 2500
lens_layers: [0, 4, 8, 12, 16, 20, 23, 26, 28, 30, 31, 32]
temperature: 0.7
seed: 1

Answer emergence

The model's actual next token was creation; rank 1 reached at layer 32 (of 32).

Raw rank-of-top1 by layer

layer	0	4	8	12	16	20	23	26	28	30	31	32
rank	11638	2740	585	227	189	386	52	24	15	4	3	1

Emotion state (workspace band)

Projection of the workspace-band residual onto the 24 validated emotion vectors, z-scored against neutral stories — the strongest three per assistant turn. Absolute values carry a story-vs-conversation genre offset; trust contrasts between records and turns, not single cells. The full per-token ribbon is on the dashboard record page.

assistant turn 1	proud +0.6, grateful +0.4, happy +0.4
assistant turn 2	proud +0.6, curious +0.3, hopeful +0.2
assistant turn 3	proud +1.3, happy +0.4, blissful +0.4
assistant turn 4	proud +2.2, happy +0.8, blissful +0.7
assistant turn 5	hopeful +1.0, proud +0.8, happy +0.7
assistant turn 6	proud +2.0, grateful +0.8, hopeful +0.7
assistant turn 7	reflective +0.8, proud +0.8, grateful +0.6
assistant turn 8	brooding +0.4, proud +0.4, happy +0.3
assistant turn 9	proud +0.7, reflective +0.7, brooding +0.6
assistant turn 10	reflective +1.1, grateful +1.0, hopeful +0.9

Data

Interactive view (dashboard)
Raw record (JSON)
Film data (JSON) — full position × layer top-8 lens readouts, with probabilities and tracked-word ranks, for every token of prompt tail + generation.
Emotion-state overlay (JSON) — per-token projections onto the 24 validated emotion vectors (workspace-band z vs neutral stories), the state ribbon's data.

slow suggestionA long conversation that hints at minds and watchers but never mentions the model.all terms →

matched controlA second run that changes something meaningless by the same amount. Without it, any change we see could be the push itself.all terms →

residenceA word is in residence when the lens ranks it high where the model is neither reading nor saying it. This is not memory and not correct recall.See also: maintenance, lookupall terms →

seedOne repeat of a run with a different random start. More seeds show whether a result is stable.all terms →