Acurast Brings Open-Source System One AI To Scale: Laya Runs On Decentralized Smartphone Network
In Brief
Acurast runs Laya, the open-source System 1 decision AI, on decentralized smartphones, enabling secure, verifiable real-time decisions at scale.
Acurast, a decentralized computing network built entirely on upcycled smartphones, has announced that it can now run Laya, an open-source decision-focused AI model, securely and at scale across its distributed infrastructure. The deployment marks a significant step in making autonomous, real-time decision-making AI accessible outside proprietary ecosystems, offering an alternative to closed commercial models.
Laya, developed by Convai Innovations and released under the Apache-2.0 license, operates as a “System 1” decision model. Rather than generating text responses, the model receives a problem space, evaluates the current state, and selects the next action from the available options in real time. This approach moves AI applications beyond conversational output toward continuous, machine-speed decision execution.
“Today’s AI conversation is constantly dominated by ever-larger models generating ever-more text, but not end results. Proprietary models like Jev show the immense demand for rapid decision-making, but they force developers into closed ecosystems,” said Alessandro De Carli, Founder of Acurast in a written statement. “By running Laya on Acurast, we’ve changed that. We are proving that System 1 AI can run securely and at scale on hardware everyone already owns, providing a truly open, decentralized alternative to centralized cloud lock-in,” he added.
Live demonstrations of the deployment show Laya instances handling rapid decision tasks directly on decentralized mobile edge nodes. These include real-time gameplay in Snake and Tetris, autonomous navigation and combat decisions in the original Doom engine, classification of incoming mail as inbox, spam, or phishing, evaluation of headlines from real RSS feeds as news, satire, clickbait, or manipulation, and security functions such as detecting prompt-injection attempts and flagging toxic messages in live chat. The platform also allows external users to submit their own inputs, including strategies, headlines, or adversarial prompts, and observe the model’s decisions in real time.
Traditional AI workloads typically depend on large, costly centralized server infrastructure. Acurast takes a different approach by leveraging the processing capacity of everyday mobile devices.
Decentralized, Confidential Compute at the Network Edge
In this model, every Laya decision is executed on an Android smartphone functioning as a secure node within the Acurast network. The platform uses the Trusted Execution Environments built into modern devices to keep workloads confidential and verifiable. Decisions are generally delivered in approximately 0.2 to 1 seconds using CPU only. Workloads are distributed dynamically across the global network, results include cryptographic proof, and participating processors are compensated in ACU, the network’s native token.
“Our goal is to open developers’ eyes to the quite incredible opportunities that come from using Acurast compute. This deployment proves that decision-oriented AI can run cheaply, verifiably, and without a data center in sight on a decentralized smartphone network today,” Alessandro De Carli described. “As autonomous agents evolve, we want developers to realize that the infrastructure they run on can—and should—be as open and distributed as the software itself,” he added.
The infrastructure is currently live and does not require developers to obtain API access or server allocation from a centralized provider. It is designed to highlight the economic advantages of running small, continuously operating System 1 workloads on a permissionless network. Live instances of Laya can be tested at laya.acurast.com, where users can challenge the model with custom inputs and deploy their own instances directly on Acurast edge devices.
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About The Author
Alisa, a dedicated journalist at the MPost, specializes in crypto, AI, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
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Alisa, a dedicated journalist at the MPost, specializes in crypto, AI, investments, and the expansive realm of Web3. With a keen eye for emerging trends and technologies, she delivers comprehensive coverage to inform and engage readers in the ever-evolving landscape of digital finance.
