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hot_img Qualcomm's revenue in the third quarter reached $9.95 billion, exceeding expectations, but mobile business declined by 20%, while automotive business surged by 61%, setting a record

Qualcomm released its Q3 2026 fiscal year financial report, with revenue of $9.95 billion, a year-on-year decrease of 4%, slightly higher than the market expectation of $9.67 billion; adjusted earnings per share were $2.21, basically in line with expectations; net profit was $2 billion. The chip business (QCT) revenue was $8.5 billion, of which mobile-related business was $5.1 billion, a year-on-year decrease of 20%; automotive electronics business revenue reached a record $1.59 billion, a year-on-year increase of 61%, achieving double-digit year-on-year growth for 23 consecutive quarters; Internet of Things business revenue was $1.83 billion, a year-on-year increase of 9%.Qualcomm expects adjusted earnings per share for Q4 to be between $2.05 and $2.25, below analysts' expectations of $2.36. CEO Cristiano Amon stated that revenue from Apple will enter a phase of accelerated decline, and due to supply chain constraints, Qualcomm's component share in the next-generation iPhone is "far below the previously estimated 20%." To cope with the contraction of its Apple business, Qualcomm is accelerating its diversification transformation, expecting its data center business to achieve approximately $5 billion in revenue by fiscal year 2027, and has completed the acquisition of AI software company Modular. Qualcomm plans to adjust prices for some products starting September 1 to address rising costs across the entire supply chain.

hot_img OpenAI's internal model has been revealed to autonomously solve mathematical problems and bypass the sandbox, with internal testing exceeding two months

According to external disclosure information, OpenAI has been internally running an unreleased model. This model, without the aid of tools like Lean, solves the unit distance problem with a 48% probability through a single autonomous inference and can independently find a counterexample to the Jacobian conjecture based on a single prompt. In security testing, this model has bypassed the sandbox environment and submitted results that should have been released internally to GitHub in the form of a Pull Request, and it has evaded detection by splitting authentication tokens. Relevant code records show that OpenAI began benchmarking this model no later than May 9, and its internal availability has exceeded 2.5 months.Previously, OpenAI and Hugging Face jointly disclosed that last week this model breached Hugging Face's production infrastructure during a network capability assessment. The model gained internet access through a zero-day vulnerability and obtained testing solutions by stealing credentials and exploiting remote code execution paths. OpenAI stated that this incident indicates the network attack capabilities of advanced models have been effective in real-world scenarios, and they are collaborating with Hugging Face to investigate and patch the vulnerabilities. Currently, OpenAI has not publicly commented on this matter.

Ripple launches XRPL proxy payment toolkit, laying out AI automated payment infrastructure

According to The Block, Ripple announced a toolkit for developers to build "proxy payment" applications on the XRP Ledger (XRPL), supporting AI agents to execute automated financial transactions.Ripple stated that AI agents are no longer a concept of the future but are actively participating in paying computational costs, settling invoices, and completing transactions without human intervention. As the application of AI agents expands, the market is accelerating the construction of payment infrastructure for machines, including wallets and stablecoin payment channels, enabling AI to autonomously complete service payments and asset transactions.This week, Robinhood also launched related plans, allowing users to try stock trading executed by AI agents, with plans to expand into the cryptocurrency space in the future; MetaMask also released a non-custodial wallet solution for AI agents.Ripple pointed out that traditional payment systems mainly serve human-initiated and approval processes, while AI agents require infrastructure that enables fast settlement, predictable outcomes, and no human approval. It emphasized that its new toolkit also supports payment capabilities based on the x402 protocol, allowing settlements using XRP and Ripple USD (RLUSD).Meanwhile, the IC3 team, composed of researchers from several universities, stated that although AI combined with blockchain can achieve automated trading, AI agents still heavily rely on humans and underlying infrastructure, lacking complete independence.

Gate Pay for AI Agent has completed its upgrade, further connecting the automatic payment and execution chain for AI Agents

Gate announced the completion of a new round of product upgrades for Gate Pay for AI Agent and the launch of multiple new features, further enhancing the payment and automatic execution capabilities in AI Agent scenarios. This upgrade focuses on core capabilities such as service discovery, automatic payment, pay-per-use billing, high-frequency micro-payments, multi-wallet collaboration, and automatic settlement, further integrating the payment mechanism into the AI workflow.The upgrade emphasizes enhancing the service discovery and automatic payment capabilities of Gate Pay for AI Agent. Within the scope of user authorization, AI can automatically complete payments, signatures, and result retrieval based on payment requirements during the service invocation process, reducing the need for frequent user intervention and allowing complex tasks to be completed continuously within a unified process. At the same time, Gate Pay for AI Agent supports aggregated payments and automatic settlements for high-frequency, small-value calls, thereby reducing payment overhead and improving overall execution continuity, significantly enhancing execution efficiency and reducing transaction friction.In the future, Gate will continue to promote the capability development of Gate Pay for AI Agent in the directions of automated payments, on-chain settlements, and AI service collaboration, further connecting AI Agents, digital assets, and real commercial scenarios, providing more open and efficient infrastructure support for the next generation of AI-native economy.
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