Technology Trends

Explores the latest innovations, protocol upgrades, cross-chain solutions, and security mechanisms in the blockchain space. It provides a developer-focused perspective to analyze emerging technological trends and potential breakthroughs.

OpenAI’s latest paper exposes the risks of AI in smart contracts

OpenAI's latest research paper highlights the dual role of AI in smart contract security, both as a tool for identifying vulnerabilities and as a potential threat capable of exploiting them. As smart contracts now manage over $400 billion in assets, their immutable nature makes security critical. To evaluate AI's capabilities, researchers developed EVMbench, a benchmark using 120 real vulnerabilities from 40 blockchain projects. The study found that frontier AI agents can successfully discover and exploit vulnerabilities end-to-end, with exploit success rates jumping from 31.9% to 72.2% in just six months. However, a recent incident involving Claude Opus 4.6 demonstrated significant risks when AI-generated code contained critical errors, leading to $1.78 million in losses. EVMbench has limitations, including a limited dataset, false positives, and an inability to fully replicate real-world conditions like cross-chain activity. The paper underscores the need for responsible AI development as smart contracts increasingly become tools for both innovation and cybercrime.

ambcrypto02/19 20:02

OpenAI’s latest paper exposes the risks of AI in smart contracts

ambcrypto02/19 20:02

Phemex Launches AI-Native Revolution, Signaling Full-Scale AI Transformation

Phemex, a cryptocurrency exchange, has announced a company-wide "AI-Native Revolution" to embed artificial intelligence into its core operations, product development, and strategic planning. This transformation positions AI as a foundational layer across the organization, moving beyond standalone features to integrate intelligent systems into management, workflows, and platform architecture. The shift aims to enhance decision-making, streamline operations, and create a more adaptive and efficient trading environment for users. CEO Federico Variola stated that AI represents a structural turning point for the industry, where exchanges will compete based on intelligent technology integration rather than just listings or fees. This initiative reinforces Phemex's evolution into a fully AI-native organization focused on innovation and scalability.

TheNewsCrypto02/19 11:22

Phemex Launches AI-Native Revolution, Signaling Full-Scale AI Transformation

TheNewsCrypto02/19 11:22

Dragonfly: Crypto Was Not Made for Humans

Crypto Was Not Made for Humans: A Summary Dragonfly Capital partner Haseeb Qureshi argues that cryptocurrency was not designed for human use, but rather for AI agents. Despite being a crypto-native firm, Dragonfly still relies on legal contracts over smart contracts for investments, highlighting that traditional systems are built for human fallibility—featuring safeguards, reversibility, and intuitive interfaces that crypto lacks. Crypto, with its rigid, deterministic, and code-based nature, is error-prone for humans, leading to fears around transactions, phishing, and irreversible mistakes. However, these very traits make it ideal for AI. AI agents can perfectly verify transactions, audit contracts, and operate within crypto’s 24/7, borderless, and self-sovereign environment. They prefer code over ambiguous legal systems, which are slow and unpredictable. Qureshi envisions a future of "self-driving" wallets where AI agents handle all financial interactions, navigating DeFi protocols on behalf of users. These agents will also transact with each other autonomously, forming an economy of non-human participants—a reality already emerging with projects like Moltbook and Conway Research. In conclusion, crypto’s perceived flaws are not shortcomings but indications that humans are not the intended users. Within a decade, direct human interaction with crypto may seem archaic, as AI agents become the primary interface, unlocking the technology’s full potential.

marsbit02/19 05:14

Dragonfly: Crypto Was Not Made for Humans

marsbit02/19 05:14

After Raising $650 Million, Dragonfly Believes Crypto Was Not Made for Humans

Dragonfly Capital partner Haseeb Qureshi argues that cryptocurrency was not designed for humans but is instead the ideal financial system for AI agents. Despite being a crypto-native firm, Dragonfly still relies on legal contracts over smart contracts for investments, highlighting that traditional systems are built for human fallibility—featuring safeguards, reversibility, and intuitive interfaces. Crypto, by contrast, is rigid, error-prone, and unforgiving, with complex addresses, gas fees, and irreversible transactions posing significant risks to human users. Qureshi posits that AI agents are the natural users of crypto: they operate with precision, trust code over ambiguous legal systems, and can verify transactions instantly. Unlike humans, AI can navigate crypto ecosystem autonomously, negotiating and executing binding agreements via smart contracts within minutes. Crypto’s global, permissionless, and deterministic nature makes it perfect for AI-to-AI economic activity, which is already emerging with projects like Moltbook and Conway Research’s autonomous agents. He predicts the future interface for crypto will be “self-driving” wallets managed by AI, which will handle financial tasks on behalf of users. This shift will transform how protocols compete and market themselves. In a decade, humans may look back in astonishment that they ever interacted directly with crypto—its true potential unlocked only when its complementary technology, AI, arrived.

Odaily星球日报02/19 05:10

After Raising $650 Million, Dragonfly Believes Crypto Was Not Made for Humans

Odaily星球日报02/19 05:10

When AI Reshapes the Shopping Journey, How Much Time Does PayPal Have Left?

PayPal's recent $200 million acquisition of Cymbio signals a strategic pivot to remain relevant in the emerging era of "Agentic Commerce," where AI agents increasingly handle product discovery, decision-making, and purchasing on behalf of users. This move aims to transform PayPal from a Web2 payment button into an embedded infrastructure layer within AI-driven commercial workflows, covering discovery, checkout, and fulfillment. The competitive landscape is rapidly evolving: Google and Shopify are developing the Universal Commerce Protocol (UCP) to control the routing layer, while OpenAI and Stripe are advancing the Agentic Commerce Protocol (ACP) to enable AI agents to execute transactions. Stripe, in particular, is positioning itself as the default "action layer" for AI commerce, mirroring its success as the internet’s payment API. Major forecasts suggest Agentic Commerce could capture $1 trillion in U.S. retail sales by 2030, representing up to one-third of online retail. For PayPal, Stripe, and other fintech players, the challenge is to embed themselves into these new protocol-based ecosystems—or risk being sidelined. Banks retain advantages in clearing and compliance but must adapt quickly, while crypto remains largely absent from current frameworks, presenting both a risk and potential opportunity. PayPal’s acquisition is less an offensive move than a necessary bid to maintain its seat at the table.

marsbit02/18 12:38

When AI Reshapes the Shopping Journey, How Much Time Does PayPal Have Left?

marsbit02/18 12:38

How Can Ordinary People 'Survive' the Impact of the AI Wave?

In this urgent warning, HyperWrite CEO Matt Shumer argues that AI advancement is progressing far faster than most people realize, with transformative impacts imminent across all sectors. He draws a parallel to the rapid onset of the COVID-19 pandemic, suggesting the current technological shift is even more profound. Shumer, an AI industry insider, states that a small group of researchers at leading labs like OpenAI and Anthropic are driving exponential progress. He shares his personal experience: recent models like GPT-5.3 Codex and Claude Opus 4.6 can now autonomously build and test complex software applications from a simple English description, requiring zero human correction. This represents a qualitative leap from being an assistant to a superior executor. He emphasizes that this disruption, which began with coding, will soon affect all knowledge work—law, finance, medicine, writing, and analysis—within 1-5 years, not decades. Free versions of AI tools are outdated; the paid, cutting-edge models are vastly more capable. Metrics show AI's autonomous task-completion time is doubling every few months. Crucially, AI is now used to build and improve subsequent AI models, creating a self-accelerating feedback loop toward artificial general intelligence (AGI). Shumer's advice for "surviving" is to start using the most powerful AI tools *now*. Subscribe to premium models, integrate them into core professional tasks, and experiment daily. Financial prudence and developing adaptability are key. He concludes that while AI poses immense risks (from job loss to security threats), it also offers unprecedented opportunities for creativity and problem-solving if approached with curiosity and urgency. The time to prepare is immediately.

marsbit02/18 04:27

How Can Ordinary People 'Survive' the Impact of the AI Wave?

marsbit02/18 04:27

The Rise of Layer 3: How Application-Specific Layers Are Powering Specialized DeFi Innovation

The emergence of Layer 3 blockchains represents a shift in scaling architecture, moving beyond the L1 (security) and L2 (speed) model. L3s act as specialized parallel execution layers designed to handle computation-heavy operations—like trading logic—without congesting the base layers. This allows users to continue transacting on L1/L2 while L3s efficiently shuttle data and liquidity to decentralized applications, particularly DEXs and perpetual trading platforms. A key application is in DeFi, where L3s enable advanced features such as real-time pricing, liquidations, and complex order types—functionality traditionally associated with centralized exchanges. Projects like Orbs exemplify this, offering plug-and-play modules that let DEXs integrate institutional-grade perps trading quickly without sacrificing decentralization. By offloading execution to L3 while settling on L1/L2, the model maintains security and decentralization at the settlement layer. This modular approach supports composability, reduces time-to-market, and allows developers to offer CEX-like user experiences onchain. Ultimately, L3s enhance scalability and functionality without requiring users to bridge assets or change their workflow.

TheNewsCrypto02/17 05:25

The Rise of Layer 3: How Application-Specific Layers Are Powering Specialized DeFi Innovation

TheNewsCrypto02/17 05:25

SNZ–NTU CCTF Releases "Top 10 Blockchain Industry Trends for 2026"

SNZ Holding and Nanyang Technological University's Computational Finance Centre (NTU-CCTF) have jointly released the "Top 10 Blockchain Industry Trends for 2026." The report highlights the ongoing transformation of Web3 from speculative experimentation into verifiable financial infrastructure. Key trends include the maturation of Real-World Assets (RWA) into composable DeFi instruments, the growing role of stablecoins in global payments, and the adoption of smart accounts and intent-based execution to improve user experience. Zero-knowledge proofs are evolving from privacy tools to foundational infrastructure for verifiable computation, while shared security and restaking are redefining security as a tradable economic resource. Other significant developments include progress in privacy-compliance engineering, DePIN networks shifting from incentive-driven models to verifiable systems, decentralized AI moving from hype to practical implementation, and token governance focusing on institutional accountability rather than mere voting procedures. The report aims to serve as a practical and forward-looking guide for industry builders, researchers, and decision-makers.

marsbit02/16 06:04

SNZ–NTU CCTF Releases "Top 10 Blockchain Industry Trends for 2026"

marsbit02/16 06:04

The Year of AI Payments: When Your Agent Learns to Pay on Its Own

English Summary: The era of AI-driven automation is approaching, requiring AI agents to possess native payment capabilities for true autonomy. Major tech companies like Google (with AP2) and crypto-native projects (via ERC-8004 and x402) are developing infrastructure for agent-level payments. Google’s AP2 uses a three-layer mandate system (Intent, Cart, Payment) built atop existing platforms like Google Pay, prioritizing convenience and consumer protection within a controlled ecosystem. In contrast, crypto approaches emphasize decentralization: ERC-8004 provides verifiable on-chain identity via NFT credentials, while x402 enables autonomous stablecoin payments via smart contracts, allowing agent-to-agent commerce without intermediaries. The key divergence is between platform-controlled, closed systems (prioritizing safety) and open, protocol-based models (prioritizing user sovereignty and broader interoperability). Both aim to enable AI agents to autonomously execute tasks like shopping or micropayments, but differ in architecture, trust models, and scope of use cases.

比推02/13 20:43

The Year of AI Payments: When Your Agent Learns to Pay on Its Own

比推02/13 20:43

Top 11 VPNs of February 2026

Top VPNs of February 2026 offer secure, private browsing by encrypting data and masking IP addresses. Key considerations when choosing include speed, privacy, and server network. Top picks are NordVPN for its robust security and streaming; Norton for simplicity and integration; ExpressVPN for speed and reliability; Mullvad for strong privacy; Hide.me for a free tier and performance; Windscribe for unlimited connections; TunnelBear for user-friendliness; CyberGhost for affordability; Hotspot Shield for a free desktop option; Surfshark for unlimited device coverage; and Proton VPN for a feature-rich free plan. Users should test services with free trials to match their needs.

ambcrypto02/13 10:29

Top 11 VPNs of February 2026

ambcrypto02/13 10:29

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