The US is exploring ways to improve location-tracking capabilities in AI chips as part of efforts to curb semiconductor exports to China, according to a senior official. The move aims to counter China's growing influence in the global chip industry and limit its access to advanced technology.
The American Arbitration Association (AAA) is hosting a transformative event that brings together global legal and AI experts to discuss the implications of Artificial Intelligence (AI) for dispute resolution. The conference, scheduled for October 9-10, 2025, will explore data ethics, regulatory trends, and real-world applications of AI in Alternative Dispute Resolution (ADR). The event is part of the AAA's Future Dispute Resolution program, which aims to foster innovation and collaboration among ADR professionals, developers, and technologists. Following the conference, a Hackathon on October 10 will be held at the AAA-ICDR's Midtown Manhattan office, where interdisciplinary teams will create solutions to improve dispute resolution processes in collaboration with Wolters Kluwer and its Kluwer Arbitration team.
The Productivity Commission has found that a combination of artificial intelligence (AI) and better use of personal data could deliver a $200 billion boost to Australia's economy over the next decade, with potential productivity growth rate increases of 4.3% and an additional $10 billion in annual benefits through higher productivity. However, the commission warns that there may be job losses due to AI, particularly painful transitions for those whose jobs are made redundant, and advises against binding regulations on AI, citing concerns it could limit growth opportunities.
The development of large-scale AI data centers faces challenges due to legacy decisions on location selection, which often prioritize existing infrastructure over clean energy sources or heat reuse networks. In response, there's a growing trend towards modular, energy-efficient builds that can reduce environmental impact and support flexible deployment. However, retrofitting older sites with high capacity requirements remains difficult, and collaboration between government, energy providers, and infrastructure is still fragmented, hindering the progress of critical AI workloads.
A researcher's work on machine vision and intelligent control systems is enhancing road design with AI-driven models that can adapt to their environment, reducing human error and evolving as needed, benefiting from his academic focus on these areas.
The Royal College of GPs has warned family doctors about the risks of using AI tools to write medical notes, citing potential misinterpretation of conversations and "hallucination" - where the system generates inaccurate information. The Medicines and Healthcare products Regulatory Agency (MHRA) is urging GPs to report any issues with AI scribes through its Yellow Card Scheme, including suspected inaccuracies. A UK GP who recently moved to Canada reported using an AI tool that misinterpreted his conversations with patients, recording notes suggesting they had moved to Canada instead of the UK.
AMD's China Concerns Overshadow Upbeat Sales Forecast for AI. The company has expressed concerns about the impact of China on its sales, despite a forecast that suggests strong demand for artificial intelligence (AI) solutions. AMD is a leading provider of AI chips and software, but it faces challenges in the Chinese market due to trade restrictions and competition from local players.
Doctors in Australia are increasingly using AI digital scribes to help with administrative tasks, raising concerns about sensitive patient data. The use of these AI-powered tools is becoming more widespread among general practitioners (GPs), but experts warn that this could compromise patient confidentiality. For instance, a recent study found that AI scribes can make mistakes when documenting patient information, which could lead to incorrect diagnoses or inappropriate treatment plans. As the healthcare industry continues to adopt AI technology, there is a growing need for stricter regulations and guidelines to ensure the secure storage and handling of sensitive patient data.
Avilom is a blockchain infrastructure integrating AI across its core layers, enabling real-time adaptation, privacy-enhancing protocols, and predictive automation. The platform aims to support next-gen decentralized applications, cross-chain systems, and privacy-aware AI computation. Avilom Labs plans to launch a beta testnet and ecosystem onboarding in Q4 2025, followed by cross-chain neural bridge testing and documentation expansion in Q1 2026. A DAO governance framework and privacy toolkit are slated for Q3 2026, with the mainnet launch expected in Q1 2027.