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DoorDash researchers built an AI system that learns to adjust how its delivery dispatch algorithm weights speed against batching efficiency, using actual delayed signals from thousands of real deliveries. The system increased batching and cut courier time costs without slowing customer delivery times, by learning from historical marketplace data rather than requiring live experimentation.

Researchers built an AI system that identifies grasshopper and cricket species from their calls in the wild, even when trained on limited labeled data. The system outperformed existing tools by a wide margin—achieving three times better accuracy at identifying species than the previous best approach—and improved further when researchers actively selected which new audio samples to label.

A smaller, cheaper artificial intelligence model outperformed GPT-4o and GPT-5 at spotting false biomedical claims, achieving up to 12% better accuracy while costing a fraction as much. The researchers fine-tuned three small models on medical claim datasets and discovered that one popular dataset had a structural quirk that artificially inflated scores—and that removing this quirk made models much better at handling new types of medical claims they'd never seen before.

Researchers created the first large-scale benchmark for testing text-search systems in Slovak, a language with limited AI resources, and found that existing Slovak language models don't work well for this task. They then built two smaller, faster Slovak models that match the performance of expensive commercial systems but can run on local computers without internet access.

Large multinational corporations are using their back-office service units as testing grounds to balance environmental goals with digital efficiency. The research reveals that companies are shifting from simple automation toward smarter, more sustainable systems—and that mid-sized countries like Poland and Portugal are becoming unexpectedly valuable hubs for this transition, offering a practical middle path between global powers.

Engineers tested whether next-generation 6G mobile networks can operate in the same radio frequencies as existing satellites without causing dangerous interference. Using a detailed 3D model of Boston and computer simulations, they found that interference can be managed through careful network design—specifically by controlling which directions antennas transmit and where base stations are physically located, even when radio signals bounce off buildings and travel indirect paths.

Robots learning to manipulate objects from human demonstrations struggle with fine spatial details, even when given 3D point cloud data. Researchers found that converting 3D coordinates into Fourier space—a mathematical transformation that emphasizes precise geometric details—lets neural networks learn manipulation policies that are significantly more accurate without any architectural changes. The approach works consistently across different robot tasks and real robot experiments.

Physicists created a special quantum state in ultracold atoms that mimics a theoretical arrangement predicted to host particles with unusual braiding properties—a key building block for quantum computers. Using precise measurements, they confirmed the state had the expected pairing structure, marking the first direct observation of this arrangement in a controlled laboratory setting.

Ship financing requires piecing together financial data, technical specs, contracts, and regulations from messy, scattered documents — a task growing harder as environmental rules tighten. Researchers built ShipFinance.ai, an AI system using large language models to automatically extract information, analyze loan applications, and generate documents, showing that AI can shoulder much of this administrative burden and let finance professionals focus on judgment calls rather than paperwork.

Long conversations bog down AI chatbots because they have to re-read everything that came before. Researchers built a new system that stores compressed versions of conversation threads and updates them as the talk goes on, keeping the bot accurate and speedy for hundreds of turns—something existing approaches fail at. The method cuts processing costs while maintaining conversation quality.

Researchers found that 282 out of 444 examined iPhone apps expose the secret credentials needed to access paid AI services like ChatGPT and Claude — allowing attackers to impersonate users and rack up charges on developers' accounts. Three months after alerting developers to the problem, 72% of vulnerable apps remained unfixed, suggesting the issue stems from deeper gaps in how developers are taught to build secure apps rather than simple oversights.

Scientists often need to collect enormous amounts of data to reverse-engineer the equations that govern complex systems — but that data is expensive and time-consuming to gather. This work shows a smarter sampling strategy that identifies the right measurements to take, cutting the data requirement dramatically. By selectively measuring the most informative moments in a system's evolution rather than sampling randomly, the method reconstructs governing equations for both ordinary and partial differential equations with a fraction of the usual data cost.