Genericise conference reference (remove SDD 2026 / AI Goes Local)

README.md

@@ -12,13 +12,12 @@ tags:
 
 # LogReg intent classifier (on top of EmbeddingGemma — Nextera demo)
 
-> ⚠️ **Conference demo weights — not production-ready.**
+> ⚠️ **Conference talk demo — not production weights.**
 >
-> This model accompanies the *AI Goes Local — Why the Future of Intelligent
-> Software Runs On-Device* keynote at **SDD 2026 (London, 2026-05-12)**.
-> It is published as a reference for the fine-tuning patterns shown on stage,
-> **not** as a deployable artefact. No security audit, no SLA, pinned to the
-> talk's state.
+> This model accompanies a conference keynote on local on-device AI. It is
+> published as a reference for the fine-tuning patterns shown on stage,
+> **not** as a deployable artefact. No security audit, no SLA, pinned to
+> the talk's state.
 >
 > Source repository:
 > [thinktecture-labs/local-multi-model-agent-slm](https://github.com/thinktecture-labs/local-multi-model-agent-slm)
@@ -30,7 +29,7 @@ tags:
 ## What this is
 
 Fine-tune of [`google/embeddinggemma-300m (via fine-tuned embeddings)`](https://huggingface.co/thinktecture/embeddinggemma-300m-ft-nextera) for the demo's reference scenario
-("Nextera" — a fully synthetic SaaS analytics product invented for the keynote).
+("Nextera" — a fully synthetic SaaS analytics product invented for the talk).
 
 See [`finetune/MODEL_CARDS.md#LogReg`](https://github.com/thinktecture-labs/local-multi-model-agent-slm/blob/main/finetune/MODEL_CARDS.md#logreg)
 in the source repository for the full card — training data, hyperparameters,