Inference Labs (@inference

Inference Labs

1,508 posts

Inference Labs

@inference_labs

Autonomy unbridled. Governed by math, not blind faith.

Hamilton, Ontario

Joined March 2023

Pinned
Inference Labs
@inference_labs
May 12
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.
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16K
Inference Labs
@inference_labs
19h
1/ AI agents are learning to take actions. Most organizations still struggle to verify outcomes. Those are very different problems.
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Inference Labs
@inference_labs
19h
2/ The next generation of AI infrastructure won't be built around what a model can do. It will be built around what can be trusted.
Inference Network | Auditable Autonomy
From inferencelabs.com
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Inference Labs
@inference_labs
Jun 16
The most valuable part of building in AI isn't always the technology. It's the conversations with researchers, engineers, founders, operators, and users who challenge assumptions and share what they're seeing in the real world. If that sounds interesting, join our communities.
Join the Inference Labs Discord Server!
From discord.com
2.8K
Inference Labs
@inference_labs
Jun 15
1/ AI models continue to improve at an incredible pace. Yet most organizations are not struggling with model capability. They are struggling with deployment, oversight, and accountability.
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Inference Labs
@inference_labs
Jun 15
2/ The challenge is no longer getting an AI system to produce an answer. The challenge is understanding how that answer was produced, whether it can be trusted, and how to defend it when decisions matter.
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Inference Labs
@inference_labs
Jun 14
Over 1,000,000,000 proofs generated. Every proof represents an opportunity to replace "trust me" with independent verification. Still early. Still building.
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Inference Labs
@inference_labs
Jun 13
The future of AI won't be defined solely by larger models or faster inference. It will be defined by systems that can operate reliably in the real world, where decisions carry consequences and trust matters. That's the future we're building toward at Inference Labs.
Inference Network | Auditable Autonomy
From inferencelabs.com
3.7K
Inference Labs
@inference_labs
Jun 12
We're building more than infrastructure. We're building a community around the future of verifiable AI. Whether your interests are computer vision, AI systems, cryptography, deployment, or emerging technology, there's a place for you in the discussion. Join our socials:
Join the Inference Labs Discord Server!
From discord.com
3.4K
Inference Labs
@inference_labs
Jun 11
NVIDIA is increasingly positioning its next generation hardware around AI agents, not just AI models. For years the conversation was: "How do we train better models?". Now it's: "How do we operate autonomous systems safely at scale?". Very different challenge.
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Inference Labs
@inference_labs
Jun 10
Anthropic's IPO filing is another sign that AI is becoming infrastructure, not experimentation. As the industry matures, governance, auditability, and verification matter more. The bigger AI gets, the harder "trust us" becomes as a strategy.
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Inference Labs
@inference_labs
Jun 9
Article
The Computer Vision Trust Problem No One's Talking About
Enterprise AI systems are increasingly being deployed into environments where model outputs influence operational decisions with financial, regulatory, or safety implications. Computer vision models...
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Inference Labs
@inference_labs
Jun 8
SpaceX, Anthropic, and OpenAI are all being discussed as potential IPO candidates. That says something important about where the market is. Investors are no longer valuing AI purely on research breakthroughs. They want durable businesses, revenue, and production adoption.
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Inference Labs
@inference_labs
Jun 7
1/ What is Sertn? At its core, Sertn.ai is a computer vision platform built for real-world deployment. Teams can annotate data, train models, deploy computer vision workflows, and monitor results from a single environment.
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Inference Labs
@inference_labs
Jun 7
2/ But we also focus on something that's often missing from AI deployments: verification. Instead of relying solely on logs, Sertn can attach a cryptographic proof to an inference, helping create a verifiable record of what happened. As AI moves into operational environments,
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Inference Labs
@inference_labs
Jun 6
Major publishers are continuing to challenge how AI models are trained. Whether the courts ultimately side with AI developers or rights holders, one thing is becoming clear: Provenance, transparency, and verification are moving from nice-to-have features to business
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