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Life so peaceful rn I can hit a 2 hours workout and at the end the only notification I got is telling me that my headphones are too loud. 🙃

Most AI systems optimize for prediction quality. Very few optimize for evidence survivability across shared infrastructure, third-party operators, regulators, and adversarial review. That gap becomes increasingly important as AI moves into operational environments. inferencelabs.com

@inference_labs Prediction quality matters. Verifiable evidence matters more. The next generation of AI infrastructure will be built around trust, auditability, and accountability.

@div29359 The quiet moves are usually the ones that matter most. Feels like tokenization has officially moved from theory to execution ngl.

@ogopzy0 This really gave me more insight fr

@abyssal_plbxc5 What an amazing article this is 👏

$19B on day one is the result. The real story is the pattern: Credibility → Infrastructure → Adoption. The teams that understand the system best are often the ones that successfully rebuild it. Full digest 👇 t.me/tokenforgeOffi… #RWA #Tokenization #DigitalAssets

It's also why @tokenforge stands out. Since 2021, the team has been building regulated tokenization infrastructure across Europe, combining expertise in finance, legal tech, and AI. While many are entering the market, some have been laying the foundations for years. #TKFG

NUVA launched with $19B in tokenized assets on day one. HELOCs. Treasuries. Regulated yield products accessible through crypto wallets. Built by a former BNY Mellon executive with 22 years of experience. $19B on day one isn't hype. It's what credibility looks like.

1/ The EU AI Act deadline is August 2026. Most companies are building paper governance: policies, inventories, declarations. Regulators want runtime proof. That's a different problem. That's what Inference Labs is built for.

@inference_labs Policies can document intent, but they can't prove what happened at runtime. As AI moves into regulated environments, verifiable execution becomes just as important as governance. Compliance without proof won't be enough.

Most AI systems today ask users to trust the output. What caught my attention about @inference_labs is their focus on verifiable inference—making it possible to prove that an AI result was actually generated as claimed. The Zealy campaign has been a great way to learn why verification could become a core part of AI infrastructure. As AI adoption grows, trust alone won't be enough. Verification matters. #InferenceLabs #AI #ZK #Web3

Insurance companies now use CV models to decide claims. The claimant can't verify which model ran. The adjuster can't either. A score decided it. No record of how. Verifiable inference fixes this at the root. sertn.ai

@inference_labs That's the real issue with AI in high-stakes decisions. The problem isn't just accuracy it's accountability. If no one can verify what model was used or how a result was produced, trust becomes impossible to audit. Verifiable inference turns "trust us" into "prove it."

🚨 Bayern’s Uli Hoeness: “Kane is one of the best transfers we ever made and he’s staying”. “Barcelona have no money anyway”, told @DasErste.

Yesterday, we presented at the Computer Vision Conference 2026 on targeted zero-knowledge verification for computer vision. Meaningful to see our work presented at one of the major conferences in the computer vision space, alongside broader discussion around verifiable inference and trustworthy AI systems.

@inference_labs A strong signal of where the industry is heading. Verifiable inference is no longer a niche research topic—it's becoming a core part of building trustworthy AI systems. Great to see zero-knowledge verification gaining visibility in the computer vision community.

Just checking in… how’s waking up as champions? 😄🏆