Lock #2 closed at 0/3 last night. The first thing PRML falsified was its own distribution hypothesis. The second was its own counting bug we caught two days before resolve.
falsify.dev/notes/lock-2... #MLOps #Reproducibility #AISafety #OpenSource #ResponsibleAI #MLEval #Transparency #OpenScience #AI
falsify.dev/notes/lock-2... #MLOps #Reproducibility #AISafety #OpenSource #ResponsibleAI #MLEval #Transparency #OpenScience #AI
Lock #2 post-mortem — the first thing PRML falsified was its own distribution hypothesis
Mechanism worked; outreach didn't. Lock #2 resolved at 0/3. The honest account.
falsify.dev
May 23, 2026 at 6:23 AM
Lock #2 closed at 0/3 last night. The first thing PRML falsified was its own distribution hypothesis. The second was its own counting bug we caught two days before resolve.
falsify.dev/notes/lock-2... #MLOps #Reproducibility #AISafety #OpenSource #ResponsibleAI #MLEval #Transparency #OpenScience #AI
falsify.dev/notes/lock-2... #MLOps #Reproducibility #AISafety #OpenSource #ResponsibleAI #MLEval #Transparency #OpenScience #AI
PRML v0.1.3 is out.What if every “94% accuracy” claim in ML came with a cryptographic receipt that can’t be faked? Pre-Register your evaluation contract before you ever see the test set.
#MLOps #MachineLearning #Reproducibility #AISafety #OpenSource #MLEval #AI #ResponsibleAI #OpenScience
#MLOps #MachineLearning #Reproducibility #AISafety #OpenSource #MLEval #AI #ResponsibleAI #OpenScience
Falsify — Pre-registration + CI for AI claims
Lock the threshold before you look at the data. Prove it.
falsify.dev
May 2, 2026 at 10:58 PM
PRML v0.1.3 is out.What if every “94% accuracy” claim in ML came with a cryptographic receipt that can’t be faked? Pre-Register your evaluation contract before you ever see the test set.
#MLOps #MachineLearning #Reproducibility #AISafety #OpenSource #MLEval #AI #ResponsibleAI #OpenScience
#MLOps #MachineLearning #Reproducibility #AISafety #OpenSource #MLEval #AI #ResponsibleAI #OpenScience
No more hidden thresholds.
No more post-hoc editing.PRML v0.1.3 is delivering on the promise.What’s your next implementation language? → falsify.dev #MLOps #Reproducibility #MachineLearning #AISafety #OpenSource #MLEval #ResponsibleAI
No more post-hoc editing.PRML v0.1.3 is delivering on the promise.What’s your next implementation language? → falsify.dev #MLOps #Reproducibility #MachineLearning #AISafety #OpenSource #MLEval #ResponsibleAI
Falsify — Pre-registration + CI for AI claims
Lock the threshold before you look at the data. Prove it.
falsify.dev
May 4, 2026 at 7:00 AM
No more hidden thresholds.
No more post-hoc editing.PRML v0.1.3 is delivering on the promise.What’s your next implementation language? → falsify.dev #MLOps #Reproducibility #MachineLearning #AISafety #OpenSource #MLEval #ResponsibleAI
No more post-hoc editing.PRML v0.1.3 is delivering on the promise.What’s your next implementation language? → falsify.dev #MLOps #Reproducibility #MachineLearning #AISafety #OpenSource #MLEval #ResponsibleAI
1/4
Every ML accuracy number you’ve ever seen is technically unfalsifiable.
Metrics, thresholds, datasets, and random seeds are often reported after the experiment.
No cryptographic proof of what was committed beforehand.
#MachineLearning #MLEval
Every ML accuracy number you’ve ever seen is technically unfalsifiable.
Metrics, thresholds, datasets, and random seeds are often reported after the experiment.
No cryptographic proof of what was committed beforehand.
#MachineLearning #MLEval
May 6, 2026 at 6:37 PM
1/4
Every ML accuracy number you’ve ever seen is technically unfalsifiable.
Metrics, thresholds, datasets, and random seeds are often reported after the experiment.
No cryptographic proof of what was committed beforehand.
#MachineLearning #MLEval
Every ML accuracy number you’ve ever seen is technically unfalsifiable.
Metrics, thresholds, datasets, and random seeds are often reported after the experiment.
No cryptographic proof of what was committed beforehand.
#MachineLearning #MLEval
Lesson learned the hard way:“The spec isn’t really a spec until it survives the second implementation.”
If you care about reproducibility in ML, this one’s worth a read.Full story → dev.to/sk8ordie84/w... falsify.dev
#MLEval #Rust #Python #GoLang #JavaScript #DevTools #YAML #ResponsibleAI
If you care about reproducibility in ML, this one’s worth a read.Full story → dev.to/sk8ordie84/w... falsify.dev
#MLEval #Rust #Python #GoLang #JavaScript #DevTools #YAML #ResponsibleAI
https://dev.to/sk8ordie84/what-writing-the-same-spec-in-four-languages-taught-me-about-yaml-32ao→
May 6, 2026 at 9:06 AM
Lesson learned the hard way:“The spec isn’t really a spec until it survives the second implementation.”
If you care about reproducibility in ML, this one’s worth a read.Full story → dev.to/sk8ordie84/w... falsify.dev
#MLEval #Rust #Python #GoLang #JavaScript #DevTools #YAML #ResponsibleAI
If you care about reproducibility in ML, this one’s worth a read.Full story → dev.to/sk8ordie84/w... falsify.dev
#MLEval #Rust #Python #GoLang #JavaScript #DevTools #YAML #ResponsibleAI
PRML v0.1.3.
Pre-Registered ML Manifest spec — declare your eval contract before seeing the test set, hash it, sign it. Four reference impls (Python, JS, Go, Rust), byte-identical on 12 conformance vectors.
falsify.dev
#MLEval #Reproducibility #OpenScience #AISafety
Pre-Registered ML Manifest spec — declare your eval contract before seeing the test set, hash it, sign it. Four reference impls (Python, JS, Go, Rust), byte-identical on 12 conformance vectors.
falsify.dev
#MLEval #Reproducibility #OpenScience #AISafety
Falsify — Pre-registration + CI for AI claims
Lock the threshold before you look at the data. Prove it.
falsify.dev
May 2, 2026 at 5:31 PM
PRML v0.1.3.
Pre-Registered ML Manifest spec — declare your eval contract before seeing the test set, hash it, sign it. Four reference impls (Python, JS, Go, Rust), byte-identical on 12 conformance vectors.
falsify.dev
#MLEval #Reproducibility #OpenScience #AISafety
Pre-Registered ML Manifest spec — declare your eval contract before seeing the test set, hash it, sign it. Four reference impls (Python, JS, Go, Rust), byte-identical on 12 conformance vectors.
falsify.dev
#MLEval #Reproducibility #OpenScience #AISafety