Federal regulators opened an investigation into Tesla's Full Self-Driving feature after 58 incidents involving traffic violations, crashes, injuries, and fires. The National Highway Traffic Safety Administration is reviewing nearly three million Tesla vehicles with the Full Self-Driving system, which requires drivers to remain alert. Tesla faces additional probes into crash reporting and other driver-assistance features. A Miami jury found Tesla partly responsible for a fatal 2019 crash involving its Autopilot system and awarded damages. Industry experts recommend supplementing Tesla's camera-based system with additional sensors. Tesla's sales have declined amid increased competition and consumer backlash, leading the company to introduce more affordable vehicle models.

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A survey of 7,000 European teenagers categorizes their understanding of artificial intelligence into four levels and finds most use technology daily for communication, entertainment, and learning. Respondents identify AI as a tool for personal and professional growth while expressing concerns about privacy, misinformation, and ethical use. Many seek more accessible digital skills education, highlighting opportunities for startups and educators. The findings indicate a digitally native generation attentive to technology's ethical implications and signal the need for businesses to invest in education and transparent practices.

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Researchers from Seoul National University of Science and Technology and U.S. partners developed an AI system that uses text embedding inversion and machine learning to analyze patent maps, identify vacant areas, and generate human-readable descriptions of potential technology opportunities. The system was validated using over 17,000 LiDAR technology patents and is being expanded to generate research proposals and patent documents, enabling startups, developing countries, and other stakeholders to identify and act on technology trends more efficiently.

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Researchers at Seoul National University of Science and Technology, led by Professor Hakyeon Lee, developed an AI-based patent abstract generator that identifies and describes technology opportunities by analyzing gaps in patent maps. The system uses text embedding inversion to convert patent data into human-readable descriptions of potential innovations. A case study on LiDAR technology demonstrated the tool’s ability to find and detail untapped opportunities in over seventeen thousand patents. The technology aims to provide startups, researchers, and policymakers with accessible innovation forecasting and is being expanded to generate research proposals and patent documents automatically.

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The electrification boom of the 1920s led to rapid industrial growth, concentrated market power, speculative investment, and ultimately a market crash followed by regulatory reforms. Artificial intelligence is experiencing similar patterns, with accelerated adoption, significant investment, market concentration among a few firms, and varied regulatory approaches. Business leaders are advised to recognize these historical parallels and prepare for both opportunities and risks as AI becomes increasingly integrated into the economy.

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The Bank of England and International Monetary Fund warn of a potential AI investment bubble as tech stocks, particularly those focused on artificial intelligence, reach high valuations and comprise a significant portion of the S&P 500. Economists note uncertainty about AI's long-term economic impact, while major companies like OpenAI, Nvidia, and AMD continue to make large deals despite profitability concerns. Industry leaders acknowledge risks of overinvestment and market correction, and analysts predict a shift from AI hype to practical evaluation of returns as the market matures.

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Formula E has developed pit boost technology that delivers a 600-kilowatt charge, providing 10 percent battery capacity in 30 seconds for electric race cars. Julia Palle, Formula E’s vice-president for sustainability, states this technology could be available for public electric vehicles in major cities within five years. The system aims to address the lack of fast charging infrastructure, making electric vehicles more practical for urban use and business fleets. Formula E has evolved to allow teams like Nissan and Jaguar to develop custom components, accelerating battery and charging innovation. The organization has set targets to reduce carbon emissions by 50 percent by 2030, with verification from the Science Based Targets initiative and the British Standards Institution.

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OpenAI and AMD announced an agreement for AMD to supply its Instinct MI450 chips to OpenAI, providing up to 6 gigawatts of computing power for AI infrastructure, with the first batch scheduled for deployment in 2026. OpenAI has the option to acquire up to a 10 percent stake in AMD through a warrant for 160 million shares, contingent on computing milestones and share price targets. AMD shares rose 25 percent following the news, while Nvidia shares declined slightly. OpenAI recently announced a separate $100 billion partnership with Nvidia to expand data center computing power, and analysts indicate the AMD deal reflects the rising demand for AI compute resources.

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FarX, a Malvern-based startup, develops an AI-powered system that combines voice and facial recognition to improve digital security, with adoption by the banking sector. The technology continuously learns from users to better identify genuine individuals and detect imposters, including those using deepfakes. FarX holds patents in the UK and US for its unified algorithm. The company is advancing its system to recognize users' emotional states through analysis of voice and facial cues, aiming to enhance automated customer service and user authentication.

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A West Monroe survey of over 300 U.S. executives finds that 86 percent of companies increased IT spending in the past year and 85 percent expect further increases, with 63 percent of leaders believing they spend more than competitors. Sixty-three percent report spending at least seven percent of company revenue on IT, and 23 percent allocate at least ten percent of their IT budget to artificial intelligence initiatives. Scaling AI and data capabilities is the top investment priority for 42 percent of companies, while 91 percent expect AI investments to drive tech spending higher. Only one percent anticipate significant headcount reductions from AI, while 25 percent expect hiring to increase.

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