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Inference Labs

@inference_labs • 38,603 subscribers

Autonomy unbridled. Governed by math, not blind faith.

Shorts

1/ Introducing Deploy Vision AI on any camera, even ones you don't own. Describe what you need, connect any feed, and get predictions that are cryptographically verified. From idea to auditable proof in one platform within minutes.

1/ Introducing Deploy Vision AI on any camera, even ones you don't own. Describe what you need, connect any feed, and get predictions that are cryptographically verified. From idea to auditable proof in one platform within minutes.

18,805 次观看

We don’t build self-driving models. We make sure cars don’t self-drive with the wrong model. Verification isn’t optional when AI touches the real world. That’s why we’re building verifiable AI infrastructure at Inference Labs.

We don’t build self-driving models. We make sure cars don’t self-drive with the wrong model. Verification isn’t optional when AI touches the real world. That’s why we’re building verifiable AI infrastructure at Inference Labs.

11,007 次观看

Videos

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Widespread ZKML adoption won’t start with proofs — it starts with usability. Watch Colin Gagich breaks down the basics of DSperse and how it shifts ZK from pure security to real scalability.

Widespread ZKML adoption won’t start with proofs — it starts with usability. Watch Colin Gagich breaks down the basics of DSperse and how it shifts ZK from pure security to real scalability.

150,307 次观看 • 8 个月前

1/ AI is already integrated into 38% of cybersecurity tools and 70%+ of enterprise workflows. But without proof, you're just trusting the black box. Here’s why that’s dangerous and how we’re solving it 💡

1/ AI is already integrated into 38% of cybersecurity tools and 70%+ of enterprise workflows. But without proof, you're just trusting the black box. Here’s why that’s dangerous and how we’re solving it 💡

138,257 次观看 • 11 个月前

2025 was the year verifiable AI stopped being an idea and started being real infrastructure. Subnet-2 crossed 300 million+ verifiable inferences. We shipped DSperse. We opened JSTprove to the world. We launched TruthTensor, now powering 500,000+ agents. We proved AI can be accountable, not just powerful. This is what it looks like when research becomes reality. 2026 is going to be bigger.

2025 was the year verifiable AI stopped being an idea and started being real infrastructure. Subnet-2 crossed 300 million+ verifiable inferences. We shipped DSperse. We opened JSTprove to the world. We launched TruthTensor, now powering 500,000+ agents. We proved AI can be accountable, not just powerful. This is what it looks like when research becomes reality. 2026 is going to be bigger.

59,317 次观看 • 5 个月前

1/ Most AI systems can tell you what a model predicted. Very few can show exactly how it arrived there. This is a look inside Sertn’s Proof Inspector: a 3D layer for verifiable inference. From the original frame → activations → proof artifacts → final detections.

1/ Most AI systems can tell you what a model predicted. Very few can show exactly how it arrived there. This is a look inside Sertn’s Proof Inspector: a 3D layer for verifiable inference. From the original frame → activations → proof artifacts → final detections.

17,482 次观看 • 1 个月前

1/ When verifiable AI goes mainstream, the Internet will not look the same. Ron Chan Ron C explains why the next era of software will not rely on data lock-in or customer retention. It will be driven by intent, proof, and portable intelligence that works anywhere. Full interview:

1/ When verifiable AI goes mainstream, the Internet will not look the same. Ron Chan Ron C explains why the next era of software will not rely on data lock-in or customer retention. It will be driven by intent, proof, and portable intelligence that works anywhere. Full interview:

59,313 次观看 • 7 个月前

Airports, AI, misaligned incentives, and logs that no one could trust. That is what sparked Inference Labs. Here’s Ron Chan Ron C telling the origin story.

Airports, AI, misaligned incentives, and logs that no one could trust. That is what sparked Inference Labs. Here’s Ron Chan Ron C telling the origin story.

45,879 次观看 • 7 个月前

Autonomous systems have no “biometrics.” No fingerprints. No Face ID. No way to prove their actions haven’t been tampered with. Ron Chan Ron C explains why autonomous systems need the same guarantees humans use every day.

Autonomous systems have no “biometrics.” No fingerprints. No Face ID. No way to prove their actions haven’t been tampered with. Ron Chan Ron C explains why autonomous systems need the same guarantees humans use every day.

31,769 次观看 • 6 个月前

1/ Ever wondered why zkML hasn’t scaled? Proving entire models is slow, costly, and impractical. What if you could prove only the parts that matter?

1/ Ever wondered why zkML hasn’t scaled? Proving entire models is slow, costly, and impractical. What if you could prove only the parts that matter?

21,192 次观看 • 8 个月前

Humans can’t have all the fun. We built an AI Agent to play DOOM 🔫 The AI’s output/action space is verified with cryptographic proofs Guillermo Rauch 1/6

Humans can’t have all the fun. We built an AI Agent to play DOOM 🔫 The AI’s output/action space is verified with cryptographic proofs Guillermo Rauch 1/6

16,507 次观看 • 1 年前

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