Business Strategy

In the paper Deep Reinforcement Learning for Urban Air Quality Management: Multi-Objective Optimization of Pollution Mitigation Booth Placement in Metropolitan Environments, Kirtan Rajesh and Suvidha Rupesh Kumar tackle an intricate urban challenge using AI: where to place air pollution mitigation booths across a city to optimize overall air quality under multiple, conflicting objectives1. The proposed solution uses Proximal Policy Optimization (PPO), a modern deep reinforcement learning algorithm, and a multi-dimensional reward function to model this real-world spatial optimization. But beneath the urban context lies a mathematical and algorithmic structure that holds powerful potential for business decision-making—especially where trade-offs between objectives are crucial. ...

The AI world has always been unusual, but starting in early 2025, it became increasingly so. LLM developers began releasing and updating models at unprecedented paces, while more giants and startups joined the AI rush—from foundational generative models (text, image, audio, video) to specific applications. It’s a new kind of gold rush, but fueled by GPUs and transformer architectures. On February 1st, DeepSeek released its open-source model DeepSeek R1, quickly recognized for rivaling—or even exceeding—the reasoning power of ChatGPT-o1. The impact was immediate. Just days later, a screenshot from Reddit showed Sam Altman, CEO of OpenAI, admitting: ...