Researchers at the University of Cambridge have achieved a significant breakthrough by training a robotic chef to watch cooking videos and replicate the recipes. Equipped with a ‘cookbook’ containing eight simple salad recipes, the robot utilized video demonstrations to identify the recipe being prepared and recreate it. Remarkably, the robot even developed its own unique recipe after analyzing the videos. Published in IEEE Access, this study highlights the potential of video content as a valuable resource for automated food production, paving the way for more accessible and cost-effective deployment of robot chefs.
Related Posts
Insecticides threaten male fertility: Global study unveils concerning sperm concentration decline
A comprehensive review of 25 studies spanning nearly 50 years reveals a consistent association between insecticide exposure and diminished sperm concentration in adult men globally. The research, conducted by a team from Italy and the US, is considered the most thorough systematic analysis on the subject to date. Focusing on organophosphates and N-methyl carbamates, commonly […]
Your Immune Cells Hold the Key to Predicting Flu Outbreaks
Influenza A viruses (IAVs) are contagious pathogens responsible for severe respiratory infection in humans and animals worldwide. Upon detection of IAV infection, host immune system aims to defend against and clear the viral infection. Innate immune system is comprised of physical barriers (mucus and collectins), various phagocytic cells, group of cytokines, interferons (IFNs), and IFN-stimulated […]
Multi-Omics Approach for Short-Term COVID-19 Progression Prediction in ICU Patients
The study developed a multi-omics approach to predict short-term COVID-19 progression in ICU patients. Analyzing data from 32 SARS-CoV-2-infected patients, including 124 clinical parameters, 271 proteins, and 782 metabolites/lipids, it identified CCL7, CA14 proteins, and hexosylceramide 18:2 as key markers. A machine learning model accurately forecasted worsening conditions up to five days in advance (79% […]