The model is getting larger, and its capabilities are getting stronger, but there is one problem that is also amplifying! Verification is struggling to keep up with the speed and complexity of inference. As the inference process becomes increasingly opaque, the source of the model becomes gradually blurred, the execution path cannot be restored, and trust will naturally collapse. It’s not because the system is faulty, but because no one can prove that it hasn’t made a mistake. This is the essence of the "verification gap." It’s not that AI isn’t advanced enough, but rather the lack of a way to confirm what model each output comes from, under what conditions, and whether it follows the expected rules. The vision of Inference Labs is actually quite simple. Every AI output should carry its own cryptographic fingerprint. Not an after-the-fact explanation, nor vendor endorsement, but a proof that anyone can independently verify and trace over the long term. Identity, source, and execution integrity should all be locked in at the moment the output is generated. This is the foundation of auditable autonomy; when a system can be verified, it can be trusted; when trust is provable, autonomous systems can truly scale. This is the future they are building!