data economy and infrastructure for AI forecasting
Solana
Joined April 2026
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Most AI models trained to predict the future fail because their training data cheats.
A single post-event edit or delayed timestamp gives an LLM fake clairvoyance in backtests.
We just shipped v6.37 on @huggingface, a leak-free clean-room data layer for predictive AI. 🧵
AI datasets brag about raw gigabytes. We brag about what we refuse to train on.
We’re holding out river flow cases & provisional flood models because their 3–7 day confidence intervals are too narrow for real calibration.
If data isn't independent, it doesn’t touch Zeno model.
Clean predictive data isn't about scraping everything. It's about cryptographic clocks, immutable SHA-256 manifests, & primary truth.
• 260M+ verified points
• 10.5M+ wallet trades
• Live pulse & audit log: offdiagonal.space
• Frozen v6.37 dataset on @huggingface
Incubated inside @zenoVision_.
Built for a wider world.
Offdiagonal.space is the evidence layer for predictive AI: forecasts, outcomes and a record of what was knowable when.
Now building its own community and contribution economy (soon).
offdiagonal retweeted
One more thing…
introducing offdiagonal.space : Clean-room data infrastructure for predictive AI.
.. but why we also built a cryptographically sealed, leakage-free data infrastructure that prevents AI forecasting models from cheating on historical evaluations and failing silently in production? 🤔
Our potential application blueprint in 6 sections 🤔
—
1. What is your company going to make?
Zeno is a metacognitive intelligence model that predicts when forecasters fail. Instead of building another prediction model, Zeno analyzes panels of diverse forecasters (AI agents, human experts, and physical ensembles) to detect fragile consensus, issue advance failure warnings, and correct group forecasts across weather, energy, and markets.
—
2. What is new about what you make, and how is it different from existing solutions? 🧵👇:
offdiagonal retweeted
“ Data preparation is critically important for an AI model to learn and perform well; in fact, the well-known industry adage is "garbage in, garbage out "
One more thing…
introducing offdiagonal.space : Clean-room data infrastructure for predictive AI.
.. but why we also built a cryptographically sealed, leakage-free data infrastructure that prevents AI forecasting models from cheating on historical evaluations and failing silently in production? 🤔
9/ but if you've read this far you already feel it. the itch. the "what if." that little voice going "...what's a bayst."
congrats.
that voice never shuts up again. 🟩
7/ dyor checklist:
☐ verified on base ✅
☐ deployed via bankr ✅
☐ funny ticker ✅
☐ unhinged frontend ✅
☐ utility (ritual) ✅
☐ governance (incoherent) ✅
☐ distribution (whoever shows up) ✅
☐ exit liquidity (you) ✅
we ship.
8/ (the closer)
not financial advice.
not spiritual advice.
not advice.
the chant is not a recommendation.
the chant is the substrate.
$BAYST. you already heard it.
🎙️ bayyyyyst.