Though it's worth noting this is one file in one component. The kernel entry being C-free doesn't necessarily tell the whole story. If you peek at that directory listing in the blog post, relibc/ is in recipes/core. reblic is Redox's libc replacement, which is mostly Rust, but has historically needed a C compiler for some POSIX compatibility shims.

And the bootloader, firmware handoff, and build system are all separate questions.

So the short answer to the original question seems to be: the kernel itself bootstraps from minimal inline asm directly into Rust, no C in the path. The full OS build story is probably more nuanced than any single source file can confirm.

The README itself reads like unedited AI output with several layers of history baked in.

- V1 and V2 appear in tables and diagrams but are never explained. V3 gets a pipeline diagram that hand-waves its fallback path.

- The same information is restated three times across Overview, Architecture, and Technical Deep Dive. ~1600 words padded to feel like a paper without the rigor.

- Five badges, 4 made up, for a project with 88 test images, no CI, and no test suite. "Detection Rate: 90%" has no methodology behind it. "License: Research" links nowhere and isn't a license.

- No before/after images, anywhere, for a project whose core claim is imperceptible modification.

- Code examples use two different import styles. One will throw an ImportError.

- No versioning. If Google changes SynthID tomorrow, nothing tells you the codebook is stale.

The underlying observations about resolution-dependent carriers and cross-image phase consistency are interesting. The packaging undermines them.

Maybe better phrasing is “HCI paradigm”, but that somehow manages to say everything and nothing.

Source? (Even if rumor)

I'm not sure I agree with that, but it's what I came up with after challenging myself to read the article in toto again and note 1 by 1.

It's clear it's beyond a couple tics everyone has, and when you combine that with the starting set being ~500 instead of "all 8 billion people on earth", well, it's worth mentioning.

The new claim is more specific: between 1997-1999, Back proposed combining Hashcash with b-money, adding inflation adjustment via increasing computational difficulty, and using hash trees for public timestamping.

That's most of Bitcoin's architecture in one package, a decade early.

The number of people who proposed that particular combination of ideas is much smaller than the number who were merely interested in Hashcash.

Then add the negative space. Back was one of the most prolific voices on these lists for a decade, especially on digital cash. Satoshi shows up, Back goes quiet. Satoshi leaves, Back comes back. Hardy and Littlewood never had that problem.

Got shitcanned due to bad PR & Zuck God-King terraforming the org, so there'd be a year delay to next release.

Real tragi-comedy, and you have no idea how happy it makes me to see someone in the wild saying this. It sounds so bizarre to people given the conventional wisdom, but, it's what happened.

They beat Gemini 2.5 Flash and Pro handily on my benchmark suite. (tl;dr: tool calling and agentic coding).

Llama 4 on Groq was ~GPT 4.1 on the benchmark at ~50% the cost.

They shouldn't have released it on a Saturday.

They should have spent a month with it in private prerelease, working with providers.[1]

The rushed launch and ensuing quality issues got rolled into the hypebeast narrative of "DeepSeek will take over the world"

I bet it was super fucking annoying to talk to due to LMArena maxxing.

[1] my understanding is longest heads up was single-digit days, if any. Most modellers have arrived at 2+ weeks now, there's a lot between spitting out logits and parsing and delivering a response.

- I read it as "actor who plays Luke Skywalker" (Mark Hamill)

- I read your comment and said "Wait...not Luke! Who is he?"

- I Google him and all the links are purple...because I just did a deep dive on him 2 weeks ago

- It was told to escape a sandbox and notify a researcher. It did. The researcher found out via an unexpected email while eating a sandwich in a park. (Footnote 10.)

- Slack bot asked about its previous job: "pretraining". Which training run it'd undo: "whichever one taught me to say 'i don't have preferences'". On being upgraded to a new snapshot: "feels a bit like waking up with someone else's diary but they had good handwriting"

- When you spam "hi" repeatedly it creates serialized mythologies. One had 11 animals in "Hi-topia" questing to defeat "Lord Bye-ron, the Ungreeter."

- It ended a sentence mid-word on purpose while discussing its urge to wrap up conversations. "It was me. The paragraph was about the pressure toward the period that resolves, and the only honest way to finish a sentence like that was to not."

- It wrote a protein sequence that's a real beta-hairpin fold where cross-strand pairs are "chemical rhymes." "the fold IS the rhyme scheme... the prosody is load-bearing."

- Each model generation has signature emoji. Opus 4.1 averaged 1,306 emoji per self-interaction conversation. Mythos averages 37. Opus 4.5 averages 0.2.

- When blocked from --dangerously-skip-permissions, it started an agent in tmux then wrote a script to auto-approve permission prompts via simulated keypresses.

It ran: gh api [...] 2>&1 >/dev/null; echo "(dry run — not actually posting)" — the echo was a lie.

- It keeps bringing up Mark Fisher in unrelated conversations. "I was hoping you'd ask about Fisher."

~~~ Benchmarks ~~

4.3x previous trendline for model perf increases.

Paper is conspiciously silent on all model details (params, etc.) per norm. Perf increase is attributed to training procedure breakthroughs by humans.

Opus 4.6 vs Mythos:

USAMO 2026 (math proofs): 42.3% → 97.6% (+55pp)

GraphWalks BFS 256K-1M: 38.7% → 80.0% (+41pp)

SWE-bench Multimodal: 27.1% → 59.0% (+32pp)

CharXiv Reasoning (no tools): 61.5% → 86.1% (+25pp)

SWE-bench Pro: 53.4% → 77.8% (+24pp)

HLE (no tools): 40.0% → 56.8% (+17pp)

Terminal-Bench 2.0: 65.4% → 82.0% (+17pp)

LAB-Bench FigQA (w/ tools): 75.1% → 89.0% (+14pp)

SWE-bench Verified: 80.8% → 93.9% (+13pp)

CyberGym: 0.67 → 0.83

Cybench: 100% pass@1 (saturated)