Anaxi Labs

A global AI supply chain, where AI takes root, in culture, craft, and the data we share. Starting with @Worldsight_ai

[Anaxi Labs @anaxilabs]

We’re proud to have contributed to a Robotics Capability Framework alongside @Arm and others across the robotics industry.

As robots become more capable and operate in more complex real-world environments, there needs to be a clear way to describe what those capabilities actually mean. Without that shared understanding, it becomes harder to compare systems, build confidence and scale adoption.

A Robotics Capability Framework is a practical starting point. It creates a common way to describe increasingly intelligent robotic systems while still giving companies the freedom to innovate and differentiate.

We’re excited to have helped shape this work and to continue contributing as the framework evolves with the industry

[Arm @Arm]

Introducing Arm Total Design for Physical AI — bringing an inital 80+ companies together around a shared goal to accelerate physical AI from development to deployment.

One of the first initiatives is a Robotics Capability Framework, creating a common language for defining increasingly intelligent and capable robotic systems.

The next frontier for AI is the physical world. We’re helping the ecosystem get there faster. https://t.co/C8JiX0ThMs

[Anaxi Labs @anaxilabs]

More Detailed Info：

https://t.co/HbbxgS7pum

[Anaxi Labs @anaxilabs]

We’re proud to have contributed to a Robotics Capability Framework alongside @Arm and others across the robotics industry.

As robots become more capable and operate in more complex real-world environments, there needs to be a clear way to describe what those capabilities actually mean. Without that shared understanding, it becomes harder to compare systems, build confidence and scale adoption.

A Robotics Capability Framework is a practical starting point. It creates a common way to describe increasingly intelligent robotic systems while still giving companies the freedom to innovate and differentiate.

We’re excited to have helped shape this work and to continue contributing as the framework evolves with the industry

[Arm @Arm]

Introducing Arm Total Design for Physical AI — bringing an inital 80+ companies together around a shared goal to accelerate physical AI from development to deployment.

One of the first initiatives is a Robotics Capability Framework, creating a common language for defining increasingly intelligent and capable robotic systems.

The next frontier for AI is the physical world. We’re helping the ecosystem get there faster. https://t.co/C8JiX0ThMs

[Anaxi Labs @anaxilabs]

Full Article:

https://t.co/s7yxpuP92A

[Anaxi Labs @anaxilabs]

The monolithic AI platform story is breaking down.

AI isn't converging on one dominant product. It's maturing into an ecosystem of specialized components — models, agents, proprietary data, orchestration layers — assembled around specific business outcomes.

Enterprises already know this. A legal workflow needs accuracy and provenance. Healthcare requires compliance and domain context. No generic assistant covers that ground. So organizations are layering tools, connecting them through orchestration, and treating AI strategy more like systems design than software procurement.

The competitive advantage in this next phase won't live in the model alone. It lives in the proprietary data surrounding it, the workflows it's embedded in, and the ability to evaluate and connect outputs across a moving stack.

Our co-founder Kate Shen breaks it down in The AI Journal 👇

#AI #AIStrategy #AgenticAI #AnaxiLabs

[Worldsight @Worldsight_ai]

WorldSight AI is officially live. 🎉
Here's everything you need to get started:
1️⃣ Apply your FREE Head Mount
2️⃣ Download your App
3️⃣ Upload video
4️⃣ Get Paid

Watch the full walkthrough 👇

[Mint Studio @mintstudio_ai]

We're giving away $6,200.

· $6,000 for serious AI builders.
· $200 just for sharing this tweet.

Everything you need to know 🧵👇

[Anaxi Labs @anaxilabs]

Our co-founder Kate Shen breaks it down in The AI Journal →

https://t.co/s7yxpuP92A

[Anaxi Labs @anaxilabs]

The monolithic AI platform story is breaking down.

AI isn't converging on one dominant product. It's maturing into an ecosystem of specialized components — models, agents, proprietary data, orchestration layers — assembled around specific business outcomes.

Enterprises already know this. A legal workflow needs accuracy and provenance. Healthcare requires compliance and domain context. No generic assistant covers that ground. So organizations are layering tools, connecting them through orchestration, and treating AI strategy more like systems design than software procurement.

The competitive advantage in this next phase won't live in the model alone. It lives in the proprietary data surrounding it, the workflows it's embedded in, and the ability to evaluate and connect outputs across a moving stack.

#AI #AIStrategy #AgenticAI #AnaxiLabs

[Anaxi Labs @anaxilabs]

https://t.co/fIys1dj4nH

[Anaxi Labs @anaxilabs]

The web is being rebuilt around AI agents coordinating with each other — and until now, nobody had actually measured how well that works.

Together with Carnegie Mellon University, we've released AgentWebBench, the first benchmark designed to test decentralized agent-to-agent coordination across 100 websites and 18.4 million documents.

We built this because we care about a healthy ecosystem, not just single-model demos, and the findings are more nuanced than the hype suggests.

Decentralized coordination currently underperforms traditional search in most cases, but wins on factual Q&A and closes the gap fast as models scale.

More importantly, the research surfaces real design principles for anyone building in this space: agents concentrate traffic on a small set of sources in ways that threaten open web diversity, planning matters more than raw model power, and we now have a proper framework for diagnosing where agent systems actually break down.

This is important to @anaxilabs as we build our global data and agent supply chain for robotics and AI systems, when agentic AI is expected to become the coordination and abstraction layer for robotics.
AgentWebBench turns abstract ecosystem concerns into measurable outcomes, and we think that's exactly what the industry needs right now.

Full paper below. 👇

[Anaxi Labs @anaxilabs]

It's an honor to collaborate with the brilliant minds at
@CarnegieMellon and @CyLab.

As AI evolves from single products into complex ecosystems, defining how value is created and shared is more important than ever.

At @anaxilabs , we are committed to building the infrastructure that rewards contributors fairly.

The journey has just begun! 🌐📷🤝

[CyLab @CyLab]

A new collaboration between @CarnegieMellon and @anaxilabs aims to tackle one of the biggest unanswered questions in artificial intelligence: how the rapidly expanding #AI ecosystem should distribute the economic value it creates. @mintstudio_ai https://t.co/ogdxHF1AR2

[Anaxi Labs @anaxilabs]

https://t.co/RbYmtVoxpB

[Anaxi Labs @anaxilabs]

What does it take to build AI systems that are powerful and trustworthy?

Our co-founder Kate Shen sat down with AI Technology Insights to explore exactly that — from the economics of agent-driven ecosystems to cryptographic auditability, self-verifying agent identities, and why the differentiating layer in AI is no longer the model itself.

Key themes from the conversation:

· Why agent traffic concentration is a structural economic challenge — not just a technical one
· How hardware-rooted cryptographic identity and zero-knowledge proofs make AI pricing and behavior auditable by design
· The gap between what agents retrieve and what they actually get right — and why architecture matters as much as model scale

@anaxilabs is building the trust, security, and governance infrastructure that enterprise AI requires.

Read the full interview in the comments👇

[Anaxi Labs @anaxilabs]

Full Content👇

https://t.co/lBakRYyg6v

[Anaxi Labs @anaxilabs]

OpenAI is projected to lose $14 billion in 2026, with 800 million weekly users and 95% paying nothing.

The model isn't broken. The monetization is.

For her column in @Forbes , @forbes_sandra covers our new research in collaboration with Carnegie Mellon University that tackles the question the entire AI industry is avoiding:

who actually pays for all of this?

Our whitepaper, "An Economic Framework for Generative Engines: Advertising or Subscription," examines what happens when AI answers replace links — and what that means for the content creators, data contributors, and platform builders caught in the middle.

The short version: extreme strategies fail in both directions. Platforms that go all-in on ads drive users away. Ad-free platforms can't sustain compute costs. The path forward is dynamic — and the economics need to be fair to work at scale.

As our co-founder Kate Shen puts it: "Structural fairness is not just an ethical stance. It's a proven competitive advantage."

Read Sandy's full breakdown in Forbes and dive into the full research paper. Both link in the comments👇

#GenerativeAI #AIMonetization #ArtificialIntelligence #AnaxiLabs #CMU

[Anaxi Labs @anaxilabs]

Latest research coming out of our CMU collaboration that can make ZK infrastructure an order of magnitude faster and safer!

[CyLab @CyLab]

A team of @CarnegieMellon researchers, in collaboration w/ @anaxilabs, is developing an approach to cryptographic proof systems that involves compiling high-level software directly to a low-level representation without hand-written protocols & constraints: https://t.co/Z3rFu2AhSy

[Anaxi Labs @anaxilabs]

Proud to be partnering with our founders' alma mater, Carnegie Mellon University, one of the best schools in the world for computer science!

[CyLab @CyLab]

We’re thrilled to share that Anaxi Labs, a scientific organization dedicated to researching and developing cryptographic technology, has partnered with @CyLab to support technology creation through the Secure Blockchain Initiative (SBI). Learn more: https://t.co/N7gUBOOCQ4

[Srinath Setty @srinathtv]

NeutronNova: A new folding scheme that improves upon prior folding schemes! We also provide a *modular* framework to build folding schemes for more complex relations including virtual machine executions. Allows building folding-based zkVMs with both space- and time-efficiency!

[Justin Drake @drakefjustin]

The EF is investing tens of millions into zkVMs:

https://t.co/XDaHyurNK9—zkRISC-V formal verification
https://t.co/ML0PUqliRb—Poseidon cryptanalysis
https://t.co/0Qns6MCIuu—L2beat for zkVMs, soon™

DM me about contributing to zkVM public goods :)

[Anaxi Labs @anaxilabs]

Finally meeting Moo Deng