We’re putting $5M behind research and development of smaller, specialized AI models for real-world deployment — Read our manifesto →
    Conscious Engines

    Research and Development

    Experiments in model architecture, training, evaluation, and efficient inference

    All research

    Distribution Matching Is Not Enough: Two Failure Modes in Latent Text Drifting

    Conscious Engines

    A technical postmortem on adapting the Drifting one-step generative framework to text, and the two failure modes that derailed it.

    Probing Latent Directions in Video Diffusion Models

    Conscious Engines

    Testing whether GAN-style linear latent editing transfers to LTX-2, a modern video diffusion model, and what the geometry reveals.

    Built for production

    Put the right-sized intelligence to the work.

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    General intelligence is becoming infrastructure.

    Enterprise advantage will come from how efficiently intelligence is applied, not simply from access to the largest model.

    The best model is the one built around the workload.

    Specialized models can deliver better economics, lower latency, and more predictable performance when the task is clearly defined.

    Enterprise AI should live where the work happens.

    Intelligence should run inside existing products, workflows, and infrastructure, with control over data, deployment, and performance.

    Conscious Engines

    Specialized AI systems engineered around real-world workflows, enterprise data, and production infrastructure.

    Small · Instant · Invisible

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