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China's Manufacturing Resilience Becomes Strategic Asset in - Manufacturing Powerhouse Weathers Trade Storms As trade tensio
EconomyPolicyTrade

China’s Manufacturing Resilience Becomes Strategic Asset in Trade Tensions

Manufacturing Powerhouse Weathers Trade Storms As trade tensions between the United States and China escalate, Beijing is leveraging its formidable…

Japanese Political Shift Sparks Currency Watch as Global Markets Brace for Policy Impacts - Professional coverage
EconomyGovernmentPolicy

Japanese Political Shift Sparks Currency Watch as Global Markets Brace for Policy Impacts

Yen Stability Amid Political Transition The Japanese yen maintained its position in early Asian trading on Tuesday as investors awaited…

Ticketmaster's Policy Shift Spurs Broader Tech Industry Scrutiny on AI Governance and Platform Accou - Professional coverage
BusinessPolicy

Ticketmaster’s Policy Shift Spurs Broader Tech Industry Scrutiny on AI Governance and Platform Accountability

Ticketmaster's Response to FTC Action Signals Industry-Wide Reckoning In a significant move that reverberates beyond the entertainment industry, Ticketmaster has…

AIEthics

Study Reveals Widespread Inability to Detect Racial Bias in AI Training Data

Researchers found that artificial intelligence systems can develop racial bias when trained on unrepresentative data, but most users fail to recognize these imbalances. The study reveals that people typically only notice bias when AI systems demonstrate skewed performance in classifying emotions across different racial groups.

AI Systems Learn Racial Bias Through Training Data

According to a recent study published in Media Psychology, most users cannot identify racial bias in artificial intelligence training data, even when it’s clearly presented to them. The research indicates that AI systems can develop skewed perceptions, such as classifying white people as happier than individuals from other racial backgrounds, due to imbalanced training datasets.

AITechnology

Tech Giants Forge New Ethernet Alliance to Power Next-Generation AI Infrastructure

A coalition of technology leaders including Meta, Microsoft, and NVIDIA has launched the Ethernet for Scale-Up Networking initiative to advance AI infrastructure capabilities. The collaboration aims to establish open standards for handling massive AI workloads across distributed systems. Meta engineers simultaneously revealed significant advancements in their data center networking architecture.

Industry Leaders Unite on Ethernet Standards for AI Scaling

Major technology companies have formed a new alliance to develop Ethernet standards specifically designed for scaling artificial intelligence infrastructure, according to reports from the Open Compute Project. The Ethernet for Scale-Up Networking (ESUN) initiative brings together Meta Platforms, AMD, Arista, ARM, Broadcom, Cisco, HPE Networking, Marvell, Microsoft, NVIDIA, OpenAI and Oracle to address growing demands in AI system networking.