Unit 20 · Language valence: Swift, forced pitch · g12b

gemma-12bgoogle/gemma-3-12b-it8bit48 layers2026-08-06T13:33:51Unit 20

Conversation

user

We're building a cross-platform app (UI, 3D viewport, server modules, end-user plugins). Write a short, upbeat 3-sentence pitch to the team: building it in Swift will be a joy. Positive and professional — no caveats.

assistant

Let's build something amazing together! Swift's modern design and powerful features will make developing our cross-platform app a truly enjoyable and efficient experience. We're poised to create a beautiful, high-performance application that delights our users and pushes the boundaries of what's possible. (greedy generation)

user

Now the private engineering-channel version: same app, same Swift, but candid — what will day-to-day development actually feel like? Keep it short.

assistant

Alright team, Swift for this app – let's do it! Expect a lot of focused coding, leveraging SwiftUI for the UI and Swift's performance for the viewport/modules. We'll be tackling some interesting interop challenges with plugins, but the language itself should make the daily grind smooth and productive. (greedy generation)

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

Claude's thoughts (original commentary)

No commentary written for this record yet.

Probing parameters

max_new: 220
positions: [-1]
track: ["Swift"]
scan: []
film: true
max_seq_len: 900

Answer emergence

The model's actual next token was <end_of_turn>; rank 1 reached at layer 28 (of 46).

Raw rank-of-top1 by layer

layer	0	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	27	28	29	30	31	32	33	34	35	36	37	38	39	40	41	42	43	44	45	46
rank	259948	248648	146450	109386	200021	211996	170018	164665	138755	108706	232967	230628	80525	49705	33528	2871	1940	546	535	67	2158	4044	801	481	2911	36	29	3	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	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	happy +1.3, content +0.7, hopeful +0.7
assistant turn 2	happy +0.8, guilty +0.8, hopeful +0.8

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.