Two important things happened on January 20, 2025. In Washington, D.C., Donald Trump was inaugurated as President of the United States. In Hangzhou, China, a little-known Chinese firm called DeepSeek released R1, an AI model that industry watchers called a "Sputnik moment" for the country's AI industry. "Whether we like it or not, we're suddenly engaged in a fast-paced competition to build and define this groundbreaking technology that will determine so much about the future of civilization," said Trump later that year, as he announced his administration's AI action plan, which was titled "Winning the Race." There are many interpretations of what AI companies and their governments are racing towards, says AI policy researcher Lennart Heim: to deploy AI systems in the economy, to build robots, to create human-like artificial general intelligence.

Display Ads and the generalized assignment problem are two well-studied online packing problems with important applications in ad allocation and other areas.

We study a challenging form of Smoothed Online Convex Optimization, a.k.a.

In the music industry, artists have changed the length and structure of songs in response to Spotify's algorithm and payment structure [ Hodgson, 2021 ].

Artificial Intelligence (AI) and Large Language Models (LLMs) are revolutionizing today's business practices; however, their adoption within small and medium-sized enterprises (SMEs) raises serious trust, ethical, and technical issues. In this perspective paper, we introduce a structured, multi-phased framework, "SME-TEAM" for the secure and responsible use of these technologies in SMEs. Based on a conceptual structure of four key pillars, i.e., Data, Algorithms, Human Oversight, and Model Architecture, SME-TEAM bridges theoretical ethical principles with operational practice, enhancing AI capabilities across a wide range of applications in SMEs. Ultimately, this paper provides a structured roadmap for the adoption of these emerging technologies, positioning trust and ethics as a driving force for resilience, competitiveness, and sustainable innovation within the area of business analytics and SMEs.

Display Ads and the generalized assignment problem are two well-studied online packing problems with important applications in ad allocation and other areas.

Just as AI begins to upend American society, Congress is considering a move that would sideline states from enforcing commonsense safeguards. Tucked into the recently passed House reconciliation package is Section 43201, a provision that would pre-empt nearly all state and local laws governing "artificial intelligence models," "artificial intelligence systems," and "automated decision systems" for the next 10 years. Last night, the Senate released its own version of the moratorium that would restrict states from receiving federal funding for broadband infrastructure if they don't fall in line. Supporters argue that a moratorium is needed to avoid a patchwork of state rules that could jeopardize U.S. AI competitiveness. AI'S DEVELOPMENT IS CRITICALLY IMPORTANT FOR AMERICA – AND IT ALL HINGES ON THESE FREEDOMS But this sweeping approach threatens to override legitimate state efforts to curb Big Tech's worst abuses--with no federal safeguards to replace them. It also risks undermining the constitutional role of state legislatures to protect the interests and rights of American children and working families amid AI's far-reaching social and economic disruptions.