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Chilean food-tech start-up NotCo uses artificial intelligence (AI) to identify the optimum combinations of plant proteins when creating vegan alternatives to animal-based food products. The company, set up in 2015, has attracted investment from Amazon founder Jeff Bezos and Future Positive, a US investment fund founded by Biz Stone, the co-founder of Twitter. NotCo's machine learning algorithm compares the molecular structure of dairy or meat products to plant sources, searching for proteins with similar molecular components. NotCo has a database containing over 400,000 different plants, including macronutrient breakdown and chemical composition. These factors are used to predict novel food combinations with the target flavour, texture, and functionality.
What if I told a story here, how would that story start?" Thus, the summarization prompt: "My second grader asked me what this passage means: …" When a given prompt isn't working and GPT-3 keeps pivoting into other modes of completion, that may mean that one hasn't constrained it enough by imitating a correct output, and one needs to go further; writing the first few words or sentence of the target output may be necessary.
The global artificial intelligence (AI) market in food and beverage (F&B) industry market is poised to grow by USD 275.34 million during 2017-2021, progressing at a CAGR of more than 42% during the forecast period. This press release features multimedia. The introduction of regulations to improve food safety and emergence of IIoT is anticipated to boost the growth of the market. Manufacturers in the F&B industry are increasingly adopting automation to meet regulations and guidelines set by industry associations for the maintenance of quality products. F&B manufacturers are required to have a safety system in place for analysis of hazards and risk-based preventive controls.
It is crucial for the wine industry to have methods like electronic nose systems (E-Noses) for real-time monitoring thresholds of acetic acid in wines, preventing its spoilage or determining its quality. In this paper, we prove that the portable and compact self-developed E-Nose, based on thin film semiconductor (SnO2) sensors and trained with an approach that uses deep Multilayer Perceptron (MLP) neural network, can perform early detection of wine spoilage thresholds in routine tasks of wine quality control. To obtain rapid and online detection, we propose a method of rising-window focused on raw data processing to find an early portion of the sensor signals with the best recognition performance. Our approach was compared with the conventional approach employed in E-Noses for gas recognition that involves feature extraction and selection techniques for preprocessing data, succeeded by a Support Vector Machine (SVM) classifier. The results evidence that is possible to classify three wine spoilage levels in 2.7 seconds after the gas injection point, implying in a methodology 63 times faster than the results obtained with the conventional approach in our experimental setup.
RIO DE JANEIRO, BRAZIL – iFood is planning to invest US$20 million in opening an AI learning center to strengthen ties with the tech industry. With an expected staff of 100 people by the end of the year, everything from machine learning, deep learning, behavioral science, and logistics will be covered. All of this is part of iFood's US$500 million funding round that began last year. São Paulo-based iFood is one of Latin America's biggest and most successful startup food delivery company. Seeing how the international food delivery ecosystem is worth around US$94 billion, it's easy to understand why iFood takes digital innovations so seriously.