Born
Applied Intelligence

From the lab

Written in the open.
No ghost-writing.

Technical notes, opinions, and research updates from the people building Born. Everything is tied to real work in the repo, not anonymous filler.

AllLaunchSystemsEssayResearchTechnicalOpinionPractice
LaunchFeatured

Born-9B Preview is finally here

The launch note for Born-9B Preview: Repath at the controls, GPT-5.5 Codex managing the run, the datasets, failures, benchmarks, and the public adapter.

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17 May 2026 · 14 min
Launch7 min

Born Chat is open: PromptKit UI, live model lanes, and the public training loop

What shipped in Born Chat, how the Born and comparison lanes are organized, why the training notice is explicit, and what Born Chat Pro is meant to become.

Read 17 May 2026
Systems11 min

Why Codex GPT-5.5 Operated Born-9B

The operating model behind the run: Codex GPT-5.5 High, Repath Ray Khan at the controls, and a model release managed through evidence, caveats, and repository state.

Read 15 May 2026
Essay6 min

How Born-9B Learned to Breathe

The origin story of Born-9B told from the real notes: the cheap first run, the honest tie, the many teachers, and the million-token second inhale.

Read 14 May 2026
Research8 min

Born-9B v1: Distillation at the edge of 9 billion parameters

How we built a competitive coding-agent model in public: the data, the teachers, and the honest eval results. What worked, what did not, and every number we tracked.

Read 14 May 2026
Technical12 min

Building the Ring teacher mix: six models, one student

The data pipeline, teacher selection criteria, and quality filters behind Born-9B's training corpus. Why we chose six teachers and how their outputs were weighted.

Read 28 Apr 2026
Opinion5 min

Why evaluation-first is the only honest way to ship AI

Benchmark theater is easy. Evidence you can trust is hard. Here is how Born thinks about measurement, and why we publish evals before we publish claims.

Read 20 Apr 2026
Technical10 min

QLoRA on a single RTX 6000 Ada: what is actually possible

A practical account of running QLoRA fine-tuning on 48 GB VRAM. Memory budgets, gradient checkpointing, batch size tradeoffs, and measured throughput.

Read 12 Apr 2026
Practice7 min

Dataset provenance: why every training row needs a paper trail

We document where every row in Born-9B's dataset came from. This post explains the tooling, the YAML manifests, and why provenance matters more than row count.

Read 5 Apr 2026