It’s been three-and-a-half years since generative AI exploded onto the scene. In this past year, progress has continued its relentless pace: Vibe coding took off, companies embraced agentic workflows, ...

Large-scale systems rely on heuristics to tackle NP-hard problems such as traffic engineering, virtual machine placement, and packet scheduling. While these heuristics are efficient, they can exhibit ...

When it comes to decision making, heuristics—mental shortcuts that can simplify decision making—often attract derision as ineffective because they are subjective or non-data-driven. However, I believe ...

We use heuristics all the time across many systems including those that are critical to production services. Production systems use heuristics because they are faster or scale better than their ...

Abstract: This letter presents an efficient design technique for optimizing parameters on antenna designs by using a heuristic single-core sampling inertia-weight-enhanced particle swarm optimization ...

The percentage of teachers who are using artificial intelligence-driven tools in their classrooms nearly doubled between 2023 and 2025, according to data from the EdWeek Research Center. In 2023, a ...

We are currently in the Fifth Industrial Revolution, driven by the fast and widespread adoption of AI. Like industrial revolutions before, the way we work is drastically changing, and we can unlock ...

Abstract: This paper introduces a hybrid optimisation framework that integrates Genetic Algorithms (GAs) and Reinforcement Learning (RL) for the construction of high-order Runge–Kutta (RK) schemes.

Teachers’ and students’ use of artificial intelligence in K-12 classrooms is increasing at a rapid pace, prompting serious concerns about the potentially negative effects on students, a new report ...

We combine Mixed-Integer Programming (MIP) with Machine Learning to find near-optimal portfolios efficiently: maximize: μᵀw - λ·(wᵀΣw) - transaction_costs(w ...