2026-08-10 Segunda

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The Battle for the AI Payment Race: Traditional Card Networks Face Off Against Coinbase

With the rise of AI agents conducting transactions, a battle for the underlying payment infrastructure is underway. Two distinct and incompatible approaches have emerged for enabling autonomous AI payments. The first approach is championed by traditional card networks Visa and Mastercard. They leverage their existing tokenized card credential systems, extending them to allow verified AI agents to make purchases within user-defined limits. Services like Mastercard's Agent Pay and Visa's Intelligent Commerce integrate with major AI platforms (e.g., OpenAI, Anthropic) and keep transactions within the established, decades-old card payment model. This system offers advantages for consumer retail, including robust fraud protection, chargeback mechanisms, and extensive merchant networks. The second approach, led by Coinbase, utilizes stablecoins on open internet protocols. Its x402 protocol reactivates the HTTP 402 status code for machine-to-machine micropayments, using USDC for settlement directly on-chain. This method eliminates the need for accounts or card fees, making it highly efficient for high-frequency, low-value, cross-border transactions between AI agents—such as paying for API calls, data streams, or computational resources—where traditional card fees and settlement times are impractical. While card networks excel in consumer-facing scenarios requiring dispute resolution, stablecoin protocols are tailored for machine economies. A key challenge for both is agent identity verification and transaction authorization. Notably, Visa and Mastercard are hedging their bets by also investing in stablecoins. Visa has rapidly grown its stablecoin settlement volume and is collaborating with Coinbase to bridge its network with the x402 protocol. Mastercard plans to acquire stablecoin platform BVNK. Their strategy is to become the fee-collecting gateway for all payment flows, regardless of the channel. Current applications reflect this division: consumer AI shopping tools (e.g., ChatGPT's checkout, Amazon's "Shop for Me") predominantly use card networks, while machine-focused services (e.g., Amazon Bedrock's core payments) adopt stablecoins via the x402 protocol. In the short term, a coexistence model is expected, with cards dominating retail and stablecoins powering machine transactions. The long-term outcome depends on whether AI-driven commerce evolves to resemble traditional retail or becomes a vast network of machine micropayments. By investing in both tracks, the incumbent card networks are positioning themselves to capture transaction fees regardless of which future prevails.

marsbit06/08 09:57

The Battle for the AI Payment Race: Traditional Card Networks Face Off Against Coinbase

marsbit06/08 09:57

AI Deceives with Perfection: How Can Crypto Users Defend Against New Scams?

AI has made crypto scams more sophisticated by generating flawless text and realistic interfaces, rendering traditional detection methods like spotting typos and grammar errors obsolete. Scammers now use AI for polished phishing emails, fake customer service chats, and convincing websites. Crypto users face unique risks as blockchain transactions are irreversible, and attackers can steal assets simply by tricking users into authorizing malicious transactions. To defend against these advanced threats, users must adopt rigorous verification habits: - Carefully check website URLs for subtle spoofing. - Use only official links and channels. - Scrutinize all wallet permissions and token approvals before signing. - Verify contract addresses directly from trusted sources, not token names. - Ignore unsolicited private messages posing as customer support. - Treat urgent requests with extreme skepticism. The core principle is that a professional appearance no longer equals safety. In the AI era, security hinges on proactive verification of every link, transaction, and communication, not on trusting surface-level credibility.

marsbit06/08 09:38

AI Deceives with Perfection: How Can Crypto Users Defend Against New Scams?

marsbit06/08 09:38

Turn Off AI Before the Interview: What Kind of People is Anthropic Looking For?

"Shut Off AI Before the Interview: What Kind of People Anthropic Is Screening For" Anthropic, now the world's most valuable AI startup, has an exceptionally competitive hiring process. A key and distinctive element is its mandatory "culture interview," conducted without AI assistance. This interview focuses not on technical skills, but on assessing a candidate's core values, worldview, and perspective on long-term AI risks. Questions delve deeply into personal ethics, "unusual beliefs," and the candidate's willingness to thoughtfully critique Anthropic's own mission. The goal is to evaluate whether someone's convictions are genuinely their own and if they can articulate and defend them under pressure. A poor score here can veto otherwise successful technical interviews. This approach starkly contrasts with companies like Google, which now encourages using AI in interviews to assess "AI fluency." Anthropic's philosophy suggests that in an era where AI makes execution cheap and the generation of opinions nearly free, true scarcity lies in original, deeply held thought. The company seeks individuals who possess substance "after turning off the AI"—those who haven't outsourced their core thinking. This focus on aligning fundamental values contributes to Anthropic's high employee retention rate in a fast-moving industry.

marsbit06/08 09:35

Turn Off AI Before the Interview: What Kind of People is Anthropic Looking For?

marsbit06/08 09:35

In the Last 2 Minutes Before SK Hynix Market Open, TradeXYZ Achieved Price Accuracy Within 0.13%

Traditionally, asset price discovery halts when markets close. However, decentralized exchanges like Hyperliquid, enabling 24/7 trading of Real-World Asset (RWA) perpetuals, are changing this. A case study involving SK Hynix stock on Hyperliquid's xyz:SKHX market demonstrates this shift during a weekend when the Korean Exchange (KRX) was closed. While the KRX closed at 2,070,000 KRW on June 5th, active trading continued on-chain. By 08:56 KST on Monday, June 8th, just before the KRX open, the chain price had fallen to 1200.0 USDC, implying a -10.21% drop. Three minutes later, the KRX opened at 1,856,000 KRW, an actual drop of -10.34%. The on-chain price had predicted the opening decline with remarkable accuracy, missing by only 0.13 percentage points. In the final two minutes before the open (08:58-08:59 KST), the on-chain market saw a significant volume spike and a +2.31% price rebound. This wasn't a prediction error but likely the market front-running the expected post-open bounce. Indeed, after opening at its low, the KRX price rebounded approximately +2.64% by 09:03 KST. This event illustrates how 24/7 on-chain markets can act as a leading price discovery venue, not only anticipating opening prices but also trading the immediate post-open dynamics before traditional markets even begin.

marsbit06/08 09:24

In the Last 2 Minutes Before SK Hynix Market Open, TradeXYZ Achieved Price Accuracy Within 0.13%

marsbit06/08 09:24

Farewell to Traditional Bulls and Bears: The Market Has Entered an Era of Rotating Bubbles

Farewell to traditional bull and bear markets; we have entered an era of rolling bubbles. This article uses a meteorological analogy to explain the modern market's shift from slow-moving, long-term trends to a chain of rapid, successive speculative frenzies. The old market resembled "stratiform" weather—slow, broad cycles lasting years. Today's market is like a "mesoscale convective system," where isolated storms (bubbles in sectors like AI, GLP-1 drugs, or crypto) form in sequence. Each is triggered by the outflow of capital and sentiment from the previous one, creating a self-perpetuating chain of booms and busts. This structural change is driven by eight permanent shifts: the democratization of speculation (zero-commission trading, retail options activity), perpetual buying from defined-contribution retirement plans, the dominance of passive investing (creating price-insensitive flows), the rise of multi-strategy funds and high-frequency trading (weakening price discovery), suppressed volatility that erupts violently, an index composition now dominated by long-duration, narrative-driven tech stocks, the elimination of information delays, and a permissive fiscal/monetary backdrop. These conditions ensure that rolling bubbles are the new normal. To navigate this environment, investors should either become deep-sector experts who understand the underlying technologies and business models or become adept observers of trends and capital flows. While chaotic from within each "storm," a higher-altitude view reveals a predictable pattern of serial booms. The key is to avoid being emotionally swept up in any single narrative and to recognize the market's new, permanent structure.

marsbit06/08 09:23

Farewell to Traditional Bulls and Bears: The Market Has Entered an Era of Rotating Bubbles

marsbit06/08 09:23

The Right Way to Use Skills: 5 Reflections After Anthropic Publicly Shared Its Internal Methodology

A deep dive into Anthropic's internal methodology for building effective AI "Skills" reveals five key insights for maximizing their value. First, Skills should focus on capturing "Gotchas" and tacit organizational knowledge—like common pitfalls and undocumented rules—rather than restating general information the AI already knows. Second, think of Skills as a form of "Context Engineering"; they are best structured as folders, not monolithic documents. A core `SKILL.md` file should act as a navigational index, progressively pulling in detailed references, examples, and assets only as needed to avoid overwhelming the model's context window. Third, whenever possible, automate repetitive tasks with scripts. This preserves the model's reasoning capacity for judgment and analysis, while scripts reliably handle the execution, saving tokens and improving accuracy. Instructions within a Skill provide the "why" and the expert judgment, while scripts provide the concrete "how." Fourth, a Skill's description is critical and often misunderstood. It should not be a list of features but a routing rule that clearly signals *when* the Skill should be triggered based on user intent and common phrasing. Finally, as Skills scale from personal tools to team-wide assets, management is crucial. Anthropic advocates for a lightweight, organic approach: let new Skills spread organically within small groups first. Those that prove genuinely useful through adoption naturally graduate to a formal marketplace, ensuring the curated library contains only high-value, battle-tested tools.

marsbit06/08 09:06

The Right Way to Use Skills: 5 Reflections After Anthropic Publicly Shared Its Internal Methodology

marsbit06/08 09:06

Vying for the AI Payment Track: Traditional Card Networks Face Off Against Coinbase

As AI agents increasingly conduct commercial transactions, a battle for control over the underlying payment infrastructure is unfolding. The competition centers on two divergent and incompatible technical approaches for autonomous AI payments. One camp, led by traditional card networks Visa and Mastercard, relies on tokenized card credentials within the established banking rails. Visa's "Intelligent Commerce" and Mastercard's "Agent Pay" services extend their existing tokenization technology to authorized AI agents for consumer retail transactions, leveraging decades of fraud protection and dispute resolution systems. Their partners include major AI firms like Anthropic, OpenAI, and Microsoft. The opposing camp, spearheaded by Coinbase, advocates for an open internet protocol using stablecoins. Coinbase's x402 protocol utilizes the HTTP 402 status code to enable direct, machine-to-machine micropayments with USDC on-chain. This model eliminates card fees and is designed for high-frequency, low-value transactions between AI agents, such as paying for API calls or data streams, where traditional card costs are prohibitive. Currently, application scenarios are clearly divided. Mainstream consumer-facing AI shopping services (e.g., ChatGPT's "one-click checkout," Amazon's AI-assisted shopping) predominantly use card channels due to their mature consumer protections and merchant networks. Conversely, the stablecoin channel dominates machine-to-machine payments, as seen in Amazon Bedrock's core payment service using Base blockchain. Significantly, traditional card networks are not solely defending their turf; they are also investing in the stablecoin arena. Visa has rapidly expanded its stablecoin settlement volume and partnered with Coinbase on interoperability, while Mastercard moved to acquire stablecoin platform BVNK. This dual-strategy indicates their intent to become the fee-collecting gateway for all payment flows, regardless of the underlying rail. The short-term outlook is for coexistence: cards for personal retail, stablecoins for machine transactions. The long-term outcome hinges on whether AI-driven commerce will resemble traditional retail or evolve into a vast network of machine micropayments. Visa and Mastercard's hedging strategy suggests they are prepared for either future, while companies betting on a single channel face greater risk.

Foresight News06/08 09:04

Vying for the AI Payment Track: Traditional Card Networks Face Off Against Coinbase

Foresight News06/08 09:04

For the First Time, Pure Human Video Pretrained VLA for Dexterous Manipulation: Deployable with Minimal Fine-Tuning Data

For the first time, a purely human-video-pretrained Vision-Language-Action (VLA) model for dexterous manipulation requires only a small amount of data for fine-tuning to achieve successful real-world deployment. Achieving human-level dexterous manipulation remains a core challenge in robotics. While multi-fingered hands offer hardware potential, Visual-Language-Action (VLA) models lag behind due to the high cost of collecting diverse, high-quality robot data. A novel framework, VITRA, developed by Microsoft Research Asia and Tsinghua University, addresses this by automatically transforming massive, unlabeled real-world human activity videos into a structured V-L-A training dataset. Key innovations include precise 3D hand motion annotation from monocular video, atomic action segmentation based on hand-speed minima, and automated instruction generation using VLMs combined with 3D trajectory visualization. This process created a massive dataset of 1 million clips. Pretrained exclusively on this human video data, the VLA model (combining a VLM backbone with a Diffusion Transformer action expert) demonstrates strong zero-shot hand motion prediction in unseen environments. Crucially, it requires minimal fine-tuning (~1.2k demonstrations) on real robot data to achieve high-success-rate dexterous manipulation tasks like grasping, placing, pouring, and sweeping on hardware like the Realman robot with the XHAND1 dexterous hand. The model shows exceptional generalization to novel objects and environments. The research also observes promising scaling behavior, where performance improves with more pretraining data, paving the way for more generalized embodied intelligence.

marsbit06/08 08:54

For the First Time, Pure Human Video Pretrained VLA for Dexterous Manipulation: Deployable with Minimal Fine-Tuning Data

marsbit06/08 08:54

Ray Dalio: The Revival of a China-led 'Tribute System', and the AI Industry Will Develop Like the EV Industry

Ray Dalio, founder of Bridgewater Associates, discusses shifting global power dynamics and the AI competition between the U.S. and China. He argues U.S. credibility as a global power willing to fight for its interests is declining, while China is accumulating wealth and influence. Dalio observes a trend where world leaders visit China, which he compares to a modern "tribute system"—not oppressive, but a hierarchy where nations acknowledge China's strength, affecting trade and security. This shift creates market uncertainty, prompting investors to seek asset diversification, including gold. Regarding AI, Dalio contrasts the U.S. and Chinese approaches. U.S. companies like OpenAI focus on monetization and subscriptions for revenue. In contrast, China treats AI as a public utility, akin to electricity or water, aiming for widespread worker accessibility over immediate profitability. He draws a parallel to China's electric vehicle industry success, where companies like BYD achieved rapid market growth. Dalio and JPMorgan's Mary Callahan Erdoes note China lacks U.S.-style fear of AI displacing jobs; instead, it focuses on leveraging AI for development and dominance in next-generation industries like robotics.

Odaily星球日报06/08 08:27

Ray Dalio: The Revival of a China-led 'Tribute System', and the AI Industry Will Develop Like the EV Industry

Odaily星球日报06/08 08:27

Michael Saylor's Latest Thoughts: The Four Beliefs That Determine Bitcoin's Future

Michael Saylor outlines four key ideologies shaping Bitcoin's future: Bitcoin Maximalists view it as the dominant monetary network and a breakthrough in economic empowerment. Bitcoin Capitalists focus on integrating Bitcoin into the global economy—into capital markets, banking, and corporate strategies—to realize its full potential as digital capital. Bitcoin Technologists advocate for ongoing protocol improvements in scalability, privacy, and security to ensure Bitcoin evolves with technological demands and threats. Bitcoin Fundamentalists prioritize protecting Bitcoin's core principles of self-custody, decentralization, and its use as sound money, guarding against dilution or capture. Each group addresses a vital aspect: Maximalists provide conviction, Capitalists drive adoption, Technologists tackle technical challenges, and Fundamentalists defend the protocol's integrity. The article argues that Bitcoin's path forward requires a balanced synthesis of these perspectives—maintaining a secure, immutable core while enabling disciplined innovation and integration in higher layers. The ultimate challenge is for Bitcoin to remain true to its principles while becoming useful to the broader world.

marsbit06/08 08:12

Michael Saylor's Latest Thoughts: The Four Beliefs That Determine Bitcoin's Future

marsbit06/08 08:12

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