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Independent publisher

David Hidary

DavidHidary

Empirical science of deep learning, emergent behaviors of complex systems, physics and neuroscience inspired ML techniques, JEPAs and world modeling, topics in probabilistic ML and representation learning.

Models in Library3
Datasets in Library1
Models on Hugging Face28
Followers1

Compare the published evidence

This profile connects the 4 model and dataset records shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Public original checkpoint shards with full persistent model/optimizer state and publication metadata. Includes existing ~10B-input-token milestones and finals; this is not a claim that cancelled or ongoing runs finished. Source inventories pin regions, object generations, byte counts and available receipt SHA256 hashes. Per-object upload receipts distinguish verified delivery from planned scope. Historical data and scientific settings are not rewritten.

Open weights

Public original checkpoint shards with full persistent model/optimizer state and publication metadata. Includes existing ~10B-input-token milestones and finals; this is not a claim that cancelled or ongoing runs finished. Source inventories pin regions, object generations, byte counts and available receipt SHA256 hashes. Per-object upload receipts distinguish verified delivery from planned scope. Historical data and scientific settings are not rewritten.

Open weights

Public original checkpoint shards with full persistent model/optimizer state and publication metadata. Includes existing ~10B-input-token milestones and finals; this is not a claim that cancelled or ongoing runs finished. Source inventories pin regions, object generations, byte counts and available receipt SHA256 hashes. Per-object upload receipts distinguish verified delivery from planned scope. Historical data and scientific settings are not rewritten.

Open weights

Datasets

NCA current-campaign original-byte archive Private dataset cache, manifests, rule pools and stream provenance. All GCS datasets remain intact. Source inventories pin regions, object generations, byte counts and available receipt SHA256 hashes. Per-object upload receipts distinguish verified delivery from planned scope. Historical data and scientific settings are not rewritten.

Publicly accessible