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README.md
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short_description: Ternary computing & efficient AI | Internectual Labs
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A public research showcase by Cody Dixon, exploring efficient AI, ternary computing, and model compression.
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## Explore
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The app includes an educational five-trit encoder. Cycle values between −1, 0, and +1 to inspect their base-3 encoding and eight-bit representation. It is an illustration of representation, not a model benchmark.
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This Space does not provide TAARDIS model inference. It contains no model weights or private model implementation.
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## Support and collaborate
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Sponsored GPU compute, collaborators, and financial support help create room for training and reproducible evaluation.
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- [Explore Internectual Labs](https://ai.internectual.net/)
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- [Sponsor the work](https://github.com/sponsors/CodeMasterCody3D)
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- [Discuss compute or collaboration](mailto:cody@internectual.com)
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This is a free static Space; no GPU grant or sponsorship award is implied.
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title: Internectual Labs
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short_description: Ternary computing & efficient AI | Internectual Labs
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# Internectual Labs
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The creators of TAARDIS
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A public research showcase by Cody Dixon, exploring efficient AI, ternary computing, and model compression.
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+
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## Explore
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| 21 |
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+
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The app includes an educational five-trit encoder. Cycle values between −1, 0, and +1 to inspect their base-3 encoding and eight-bit representation. It is an illustration of representation, not a model benchmark.
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| 24 |
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+
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This Space does not provide TAARDIS model inference. It contains no model weights or private model implementation.
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+
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## Support and collaborate
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+
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Sponsored GPU compute, collaborators, and financial support help create room for training and reproducible evaluation.
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- [Explore Internectual Labs](https://ai.internectual.net/)
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- [Sponsor the work](https://github.com/sponsors/CodeMasterCody3D)
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- [Discuss compute or collaboration](mailto:cody@internectual.com)
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+
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This is a free static Space; no GPU grant or sponsorship award is implied.
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