2026-04-24 Sexta

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Embodied Intelligence Breakthrough: Amap Fully Open-Sources Universal Robot Base Model ABot-M0

Embodied Intelligence Breakthrough: AutoNavi Open-Sources Universal Robot Base Model ABot-M0 AutoNavi has announced the full open-source release of ABot-M0, the world's first unified architecture-based embodied manipulation base model. This model is designed to enable "one general brain to adapt to multiple forms of robots," aiming to break down barriers between heterogeneous hardware and accelerate the adoption of embodied intelligence in industrial and household settings. ABot-M0 demonstrated exceptional performance in industry tests, achieving a task success rate of 80.5% on the Libero-Plus benchmark—a nearly 30% improvement over the previous benchmark, Pi0. It also set new state-of-the-art records on benchmarks like Libero and RoboCasa. The open-source release addresses long-standing challenges in the field, such as data isolation and deployment difficulties, by providing resources across three key dimensions: - **Data:** The UniACT dataset, the largest of its kind, with over 6 million real operation trajectories and full data pipeline tools. - **Algorithm:** The model architecture and training framework, featuring innovative components like Action Manifold Learning (AML) and a dual-stream perception architecture. - **Model:** End-to-end pre-trained models and a complete toolchain for out-of-the-box deployment, significantly lowering the barrier to adaptation. According to AutoNavi's ABot-M0 technical lead, this open-source initiative aims to build a bridge between academic research and industrial application, enabling robots of various forms to possess a smart, reliable, and universal "brain."

marsbit04/01 08:19

Embodied Intelligence Breakthrough: Amap Fully Open-Sources Universal Robot Base Model ABot-M0

marsbit04/01 08:19

Will Middle Management Be Replaced by AI? What Will the Future Company Structure Look Like

The article explores whether AI will eliminate middle management and reshape future corporate structures. It traces the historical evolution of organizations—from Roman military units to modern corporations—showing how hierarchical systems emerged to manage information flow under the constraint of limited "span of control." Middle management, matrix structures, and bureaucratic systems were all solutions to coordination challenges in information-scarce environments. AI, however, challenges this foundational premise. By enabling real-time modeling, understanding, and distribution of information, AI could replace human-centric coordination mechanisms. Examples like the AI firm "Moon Dark Side" illustrate radical experiments: no departments, titles, or traditional KPIs, with co-founders directly managing large teams and AI agents handling tasks from data processing to code generation. Block (founded by Jack Dorsey) is presented as a case study in building an "intelligent company." This model relies on two core components: a "company world model" (a real-time understanding of internal operations via digital traces) and a "customer world model" (built from real behavioral data, especially financial transactions). An intelligence layer uses these models to dynamically combine capabilities (e.g., payments, lending) to serve customers proactively, without pre-defined product roadmaps. In this structure, traditional roles shift. Middle managers are replaced by a system that handles coordination, while humans focus on individual contributions (ICs), direct responsibility (DRIs), or player-coach roles. The organization becomes flatter, faster, and more adaptive. The article concludes that AI is not just a tool for efficiency but a transformative force that could redefine organizational design, moving companies from human-led hierarchies to system-driven intelligence.

marsbit04/01 08:11

Will Middle Management Be Replaced by AI? What Will the Future Company Structure Look Like

marsbit04/01 08:11

Stripe Rises, PayPal Falls: The New King of Payments Ascends the Throne

Stripe, the global payments infrastructure giant, surged to a $159 billion valuation in February 2026, marking a 74% increase from the previous year. It processed $1.9 trillion in annual transaction volume, accounting for 1.6% of global GDP. In contrast, PayPal, the legacy payments leader, faced stagnation with just 4.3% revenue growth in 2025, a sharp decline in core checkout growth, and flat active user numbers. Reports emerged that Stripe is considering acquiring PayPal. Stripe’s success is driven by strategic bets on next-generation technologies: it acquired stablecoin infrastructure firm Bridge and crypto wallet provider Privy, and co-developed the Tempo blockchain, capable of over 100,000 TPS. It also partnered with OpenAI to create the Agent Commerce Protocol, enabling AI agents to conduct micro-payments via stablecoins. These moves position Stripe at the center of AI and crypto-powered transaction growth. Meanwhile, PayPal struggled with innovation. Its stablecoin PYUSD held less than 0.5% market share, and its management acknowledged execution failures. While PayPal remains a cash-generating business with 439 million active accounts, it has been slow to adapt to shifting industry paradigms. The divergence highlights a fundamental strategic difference: Stripe is building the infrastructure for the future of payments—on-chain settlement, AI economies, and programmable money—while PayPal has been optimizing within an outdated framework. The industry is now racing toward stablecoin and blockchain-based payments, a transition Stripe began leading nearly two years ahead of competitors like Visa and Mastercard.

marsbit04/01 06:39

Stripe Rises, PayPal Falls: The New King of Payments Ascends the Throne

marsbit04/01 06:39

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