This article is from |Delphi Digital

Compiled by｜Odaily Planet Daily (@OdailyChina）_

Translator｜Azuma (@azuma_eth）_

Editor's note: After several days of sluggishness, the AI sector finally experienced a violent rebound today, with the framework project arc surging 80% in a single day, leading the entire sector. The most direct clue to this surge may be arc's official announcement today of "a new token issuance mechanism focused on capturing ecosystem potential." However, looking back at the past fluctuations in the AI sector, arc seems to consistently exhibit a stronger upward momentum.

The content of this article is a paid research report on arc originally published by Delphi Digital on January 28. On February 8, the institution selected and updated the core content and published it again on the X platform — within just three days, arc has rebounded strongly from a low of $0.13 to $0.32.

The following is the original content from Delphi Digital, compiled by Odaily Planet Daily.

AI Agents are no longer just experimental products. To succeed in real-world applications, they need a framework built for scale and performance.

How does arc perform compared to its competitors? Let’s break it down step by step.

arc Overview

arc is a Rust-based agent platform designed for speed, reliability, and security. With hardware-level execution speed, built-in memory error protection, and secure concurrency mechanisms, arc can help high-demand applications in finance, healthcare, and real-time systems further enhance reliability and scalability.

The architecture of arc allows it to stand out in areas where ElizaOS and ZerePy perform relatively poorly. arc's decentralized workflow supports trustless, low-latency operations, making it an ideal choice for applications like DeFi arbitrage agents.

arc's real-time performance also meets the demands for sub-millisecond latency in applications such as robotics, autonomous vehicles, and IoT systems.

Core Innovations of Rig

Note from Odaily: Rig is the name of arc's token framework.

• Performance: Rig can be compiled directly into machine code, achieving near-native speed, surpassing Eliza's JavaScript runtime.

• Memory Safety: Rust prevents crashes by capturing memory errors before the project runs, making it very suitable for critical systems like healthcare and aerospace.

• Concurrency: Rust allows programs to multitask without crashing or causing errors, even when multiple tasks attempt to use the same data simultaneously.

• Determinism: Rust maintains predictable performance by avoiding delays caused by cleaning up unused memory, making it very suitable for high-demand tasks like autonomous navigation.

Developer Adoption Metrics

arc's focus on the Rust language makes it a strong competitor in the AI agent framework space. Here’s a comparison of the number of GitHub stars for other leading AI frameworks:

• TensorFlow (Python/C++): 188,000 stars;

• LangChain (Python): 99,900 stars;

• PyTorch (Python): 86,600 stars;

While ElizaOS leads in star count and contributors among crypto agent frameworks, arc's focus on high-performance, decentralized applications makes it a strong competitor in the niche market.

Recent Developments

Recently, arc announced a partnership with the Solana Foundation to accelerate AI innovation on Solana. Through this collaboration, arc will be able to provide funding and guidance for projects building Rust-based agents on Rig.

arc has also released the Rig Onchain Kit, designed to provide agents with on-chain capabilities, such as automatic portfolio rebalancing or voting on proposals.

This opens up new possibilities, allowing agents to become DeFi collaborators that can interact with smart contracts.

arc Partners

• Arbitrum: Building developer tools to facilitate development on the Stylus and Rig frameworks.

• Abstract Chain: Bringing EVM compatibility to Rig.

• MongoDB: Providing enterprise-level data orchestration, enhancing RAG (Retrieval-Augmented Generation) capabilities.

• Shuttle: Offering a Rust-native cloud platform to simplify the deployment and management of the Rig framework.

• Eternal AI: Implementing decentralized reasoning to enhance autonomy and security.

• Hyperbolic: Enabling agents built on Rig to access Hyperbolic's extensive model library and high-performance computing resources.

• SendAI: Cross-chain AI deployment, enhancing communication and interoperability.

Market Positioning

• DeAI Growth: As DeFAI and DAOs expand, the demand for open-source AI agents will surge.

• High-Performance Niche: arc is leading in high-demand areas such as robotics, IoT, and real-time analytics.

• DePIN: Supporting trustless, low-latency operations, optimizing decentralized physical infrastructure such as energy networks, supply chains, and telecommunications networks.

Potential Challenges and Outlook

• Learning Curve: Rust is relatively complex, but arc mitigates this issue through templated workflows and developer tools provided by Shuttle.

• Ecosystem Maturity: Promoting the growth of Rust AI libraries through incentives like funding and hackathons.

• Competitive Landscape: Although frameworks like ElizaOS and TensorFlow currently dominate the AI space, arc can focus on niche markets, developer communities, and Rust to highlight its value proposition.

arc's RIG framework is redefining AI infrastructure by leveraging Rust's performance advantages. As the applications of decentralized and high-performance AI continue to grow, arc is poised to play a significant role in shaping the future of AI agents.

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