The share declines were sparked by AI firms such as Anthropic, the company behind the chatbot Claude, releasing new tools. The share declines were sparked by AI firms such as Anthropic, the company behind the chatbot Claude, releasing new tools. But, after second day of Wall Street falls, analysts say sell-off'may overstate AI's immediate risk to complex deal-making' Shares in commercial property services companies have tumbled, in the latest sell-off driven by fears over disruption from artificial intelligence. After steep declines on Wall Street, European stocks in the sector were hit on Thursday. The estate agent Savills' shares fell 7.5% in London, while the serviced office provider International Workplace Group, which owns the Regus brand, lost 9%.

The technical failure coincided with TikTok's ownership transition, leading users to question whether videos criticizing ICE raids in Minnesota were being intentionally censored. TikTok is currently experiencing a widespread service outage in the US, causing disruptions for millions of users only a few days after the company officially transferred control of its American business to a group of majority-US investors . The technical issues led many TikTok users to speculate about whether the app's new owners were intentionally suppressing videos about political topics, particularly content related to recent federal immigration operations in Minnesota. TikTok has denied the allegations, attributing the problems to a power outage. TikTok users began reporting on Sunday that they were having trouble uploading videos to the app as well as viewing content that had already been posted on the platform.

Technology can be a powerful force for good. It can also be an enormous factory for harmful ideas. We tried to keep both of those things in mind when creating the 10 Breakthrough Technologies of 2026. The billionaire investor Peter Thiel (or maybe his ghostwriter) once said, " We were promised flying cars, instead we got 140 characters ." That quip originally appeared in a manifesto for Thiel's venture fund in 2011. All good investment firms have a manifesto, right?

LG TVs add'delete' option for Copilot The blackout knocked out traffic lights, causing the robo-taxis to get stuck at intersections. Waymo has resumed its robo-taxi service in San Francisco after a power outage stranded vehicles around the city, reported. The blackout, caused by a Pacific Gas & Electric (PG&E) substation fire, caused traffic light disruptions that affected Waymo's automated driving systems. Yesterday's power outage was a widespread event that caused gridlock across San Francisco, with non-functioning traffic signals and transit disruptions, a Waymo spokesperson told CNBC in a statement. While the failure of the utility infrastructure was significant, we are committed to ensuring our technology adjusts to traffic flow during such events.

Welcome to our annual list of the worst, least successful, and simply dumbest technologies of the year. We like to think there's a lesson in every technological misadventure. But when technology becomes dependent on power, sometimes the takeaway is simpler: it would have been better to stay away. Here are some of the more notable ones . Each time you've heard a borderline outlandish idea of what AI will be capable of, it often turns out that Sam Altman was, if not the first to articulate it, at least the most persuasive and influential voice behind it. For more than a decade he has been known in Silicon Valley as a world-class fundraiser and persuader.

Supply chains are integral to global economic stability, yet disruptions can swiftly propagate through interconnected networks, resulting in substantial economic impacts. Accurate and timely inference of supply chain resilience--the capability to maintain core functions during disruptions--is crucial for proactive risk mitigation and robust network design. However, existing approaches lack effective mechanisms to infer supply chain resilience without explicit system dynamics and struggle to represent the higher-order, multi-entity dependencies inherent in supply chain networks. These limitations motivate the definition of a novel problem and the development of targeted modeling solutions. To address these challenges, we formalize a novel problem: Supply Chain Resilience Inference (SCRI), defined as predicting supply chain resilience using hypergraph topology and observed inventory trajectories without explicit dynamic equations. To solve this problem, we propose the Supply Chain Resilience Inference Hypergraph Network (SC-RIHN), a novel hypergraph-based model leveraging set-based encoding and hypergraph message passing to capture multi-party firm-product interactions. Comprehensive experiments demonstrate that SC-RIHN significantly outperforms traditional MLP, representative graph neural network variants, and ResInf baselines across synthetic benchmarks, underscoring its potential for practical, early-warning risk assessment in complex supply chain systems.

As posts on social media increase rapidly, analyzing the sentiments embedded in image-text pairs has become a popular research topic in recent years. Although existing works achieve impressive accomplishments in simultaneously harnessing image and text information, they lack the considerations of possible low-quality and missing modalities. In real-world applications, these issues might frequently occur, leading to urgent needs for models capable of predicting sentiment robustly. Therefore, we propose a Distribution-based feature Recovery and Fusion (DRF) method for robust multimodal sentiment analysis of image-text pairs. Specifically, we maintain a feature queue for each modality to approximate their feature distributions, through which we can simultaneously handle low-quality and missing modalities in a unified framework. For low-quality modalities, we reduce their contributions to the fusion by quantitatively estimating modality qualities based on the distributions. For missing modalities, we build inter-modal mapping relationships supervised by samples and distributions, thereby recovering the missing modalities from available ones. In experiments, two disruption strategies that corrupt and discard some modalities in samples are adopted to mimic the low-quality and missing modalities in various real-world scenarios. Through comprehensive experiments on three publicly available image-text datasets, we demonstrate the universal improvements of DRF compared to SOTA methods under both two strategies, validating its effectiveness in robust multimodal sentiment analysis.

We present ChronoGraph, a graph-structured multivariate time series forecasting dataset built from real-world production microservices. Each node is a service that emits a multivariate stream of system-level performance metrics, capturing CPU, memory, and network usage patterns, while directed edges encode dependencies between services. The primary task is forecasting future values of these signals at the service level. In addition, ChronoGraph provides expert-annotated incident windows as anomaly labels, enabling evaluation of anomaly detection methods and assessment of forecast robustness during operational disruptions. Compared to existing benchmarks from industrial control systems or traffic and air-quality domains, ChronoGraph uniquely combines (i) multivariate time series, (ii) an explicit, machine-readable dependency graph, and (iii) anomaly labels aligned with real incidents. We report baseline results spanning forecasting models, pretrained time-series foundation models, and standard anomaly detectors. ChronoGraph offers a realistic benchmark for studying structure-aware forecasting and incident-aware evaluation in microservice systems.

Artificial Intelligence is reshaping America's \$9.4 trillion labor market, with cascading effects that extend far beyond visible technology sectors. When AI transforms quality control tasks in automotive plants, consequences spread through logistics networks, supply chains, and local service economies. Yet traditional workforce metrics cannot capture these ripple effects: they measure employment outcomes after disruption occurs, not where AI capabilities overlap with human skills before adoption crystallizes. Project Iceberg addresses this gap using Large Population Models to simulate the human-AI labor market, representing 151 million workers as autonomous agents executing over 32,000 skills and interacting with thousands of AI tools. It introduces the Iceberg Index, a skills-centered metric that measures the wage value of skills AI systems can perform within each occupation. The Index captures technical exposure, where AI can perform occupational tasks, not displacement outcomes or adoption timelines. Analysis shows that visible AI adoption concentrated in computing and technology (2.2% of wage value, approx \$211 billion) represents only the tip of the iceberg. Technical capability extends far below the surface through cognitive automation spanning administrative, financial, and professional services (11.7%, approx \$1.2 trillion). This exposure is fivefold larger and geographically distributed across all states rather than confined to coastal hubs. Traditional indicators such as GDP, income, and unemployment explain less than 5% of this skills-based variation, underscoring why new indices are needed to capture exposure in the AI economy. By simulating how these capabilities may spread under scenarios, Iceberg enables policymakers and business leaders to identify exposure hotspots, prioritize investments, and test interventions before committing billions to implementation

Thousands of Airbus planes are being returned to normal service after being grounded for hours due to a warning that solar radiation could interfere with onboard flight control computers. The aerospace giant - based in France - said around 6,000 of its A320 planes had been affected with most requiring a quick software update. Some 900 older planes need a replacement computer. French Transport Minister Philippe Tabarot said the updates went very smoothly for more than 5,000 planes. Fewer than 100 aircraft still needed the update, Airbus had told him, according to local media.