💼 Chinese AI Invests Heavily in Research Scientists. US mHealth Usage. Organisations Differ With GenAI Output Reviews.

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Today's Topics

💼 Workforce. Chinese companies invest heavily to attract AI research scientists
⚕️ Health Skills. US mHealth usage centered around sleep, weight and diet tracking
🤖 Artificial Intelligence. Organisations differ with GenAI output reviews

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💼 Chinese Companies Invest Heavily To Attract AI Research Scientists

Chinese companies invest nearly ¥3M ($420K) on average to attract top AI research scientists in 2025, with industry leaders offering high compensation packages including equity. Beyond salary, firms provide distinctive benefits such as 20-40% dedicated research time, international collaboration opportunities, and dual-track career advancement, while offering up to ¥100M in project funding for top talent. China aims to dominate global AI by 2030, holding 47% of top researchers, 50%+ of patents, and targeting a $1.4T market. Government backing includes ¥258B R&D investment, $15B Big Fund III, talent visa fast-tracks, and housing subsidies, positioning China for AI leadership through application-driven innovation.

⚕️US mHealth Usage Centered Around Sleep, Weight and Diet Tracking

At least 40% of US mHealth app users tracked sleep (48%), weight (46%), and diet (41%) in 2023, with 320M+ Americans using health apps as usage grew along with growing health consciousness. Simultaneously, the wearables market expanded to $84.2B in 2024, projected to hit $352B by 2033 at 18.5% CAGR, driven by smartwatches and innovative wearables being developed by many companies, along with AI integration. However, critical limitations persist over data privacy concerns, accuracy and over-reliance on mHealth app data

🤖 Organisations Differ With GenAI Output Reviews

Organisations showed polarised GenAI output review in 2024, with 30% reviewing all outputs versus 27% reviewing none. Critical gaps persist due to a lack of organisational policies on AI and a lack of proper review frameworks. Universal frameworks emerged, such as NIST AI Risk Management Framework, EU AI Act, emphasising output validation, monitoring, and transparency. Organisations struggle with GenAI's "black box" nature in critical sectors, requiring cross-functional governance balancing innovation with accountability through risk-based frameworks.

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