This week’s roundup of top data news covers highlights from February 7, 2026, to February 13, 2026, includes a new computer chip that helps self‑driving cars react faster and chocolate makers using AI to speed up their product development.
Researchers at the Chinese Academy of Sciences have built an artificial insect-scale eye that gives small drones a 180-degree field of view and the ability to detect hazardous gases. Using laser printing, they created over 1,000 tiny lenses and added an inkjet-printed chemical sensor that changes color when exposed to certain fumes. Tested on a small drone, the system tracked motion and avoided obstacles. It could aid search-and-rescue or environmental monitoring.
Researchers at the Georgia Institute of Technology have used the Frontier supercomputer at Oak Ridge National Laboratory to run a 3D turbulence simulation, modeling airflow at 35 trillion grid points. The high detail allowed them to test long-standing theories and better understand extreme air fluctuations that affect storms, pollution spread, and aircraft stability. The findings can help refine how scientists predict turbulent air flows.
3. Controlling Pigeons’ Flight
Russian neuro-tech startup Neiry has created a system that uses small brain implants to steer pigeons in flight. Tiny electrodes stimulate motor-control regions associated with turning or flying forward, triggering movements that mirror the bird’s natural neural signals. A lightweight wireless backpack sends commands to the implant and carries a small camera, allowing the pigeon to navigate and transmit live video for surveillance and reconnaissance purposes.
4. Improving Autonomous Car Safety
Scientists at Beihang University China have built a machine-vision system that processes images in microseconds by combining an ultrafast camera with a neuromorphic computer chip. Instead of processing entire images in sequence like a traditional chip, this brain-inspired chip responds only to changes in light and motion, much like nerve cells in the human eye. The system detects sudden movement and tracks fast objects in real time for improved safety in self-driving cars.
5. Saving Time on Lesson Preparations
Colorado‑based ed‑tech company MagicSchool AI has expanded its platform across Hillsborough County Public Schools in Florida. The platform uses an AI system to generate lesson plans, quizzes, and assignments based on teacher prompts. Educators enter a topic or goal, and the system produces ready-to-use materials that teachers can edit and customize. District leaders say the tool speeds up lesson preparation.
6. Solving Complex Equations with Light
Researchers at Queen’s University Canada have built a computer that uses chips powered by laser light moving through tiny photonic circuits to solve math problems. Because light produces almost no heat, the computer can perform certain optimization and matrix calculations faster and with far less energy than computers that rely on traditional electronic chips. The prototype isn’t meant to replace general‑purpose computers, but it shows how light‑based hardware could make future scientific computing more efficient.
The botanical garden at Cambridge University has launched an exhibition that lets visitors chat with 20 plants through an AI system called Talking Plants. Scanning a QR code by the plant opens a phone‑based chat window for two‑way voice or text conversations, with each plant speaking in a distinct personality. The system is trained on curated scientific data and supports multiple languages, trivia, and plant‑led meditation sessions.
Swiss‑Belgian chocolate manufacturer Barry Callebaut has opened an AI‑driven Chocolate Innovation Center in Singapore that uses machine‑learning and data analytics to accelerate product development. Its platform analyzes consumer trends, ingredient behavior, and regional taste preferences to predict successful chocolate formulas, reducing trial‑and‑error testing. The system guides flavor design, nutritional adjustments, and rapid prototyping for Asian markets.
9. Solving Ancient Board Games
Researchers at Leiden University Netherlands have used an AI model to analyze a 1,600‑year‑old limestone game board from a Roman fort in the Netherlands. By analyzing wear patterns and board markings, the system helped infer how the game was likely played. Archaeologists worked alongside the model to interpret results. The approach speeds analysis compared to traditional methods and could help researchers reconstruct other ancient games.
Researchers at Harvard University have built a robot knee‑like joint using an AI‑guided design method that mimics how natural joints distribute force. Their machine‑learning system evaluated thousands of structural variations to generate a hinge balancing strength, flexibility, and smooth motion. The resulting joint bends, rotates, and absorbs impact more efficiently than conventional robotic hinges, improving stability for walking robots and potential prosthetics.
