If you find yourself intrigued by the concept of Artificial Intelligence (AI) but are unsure of what it truly entails or how it could be applied to real-life scenarios, you're not alone. Generative AI can seem complex and daunting, leaving many wondering how it works and how it could be harnessed for practical purposes. Winnow’s technology utilises AI to help commercial kitchens track their food waste. To understand more about how this works, we talked with our Product Director Shonak Nathwani. Read on for the Q&A as he decodes how AI works, and how Winnow’s technology works to drive down food costs and environmental impacts.
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Q1: What is Winnow Vision?
Shonak: “Winnow Vision is our flagship product that leverages AI to revolutionise food waste management in commercial kitchens. It uses cutting-edge AI technology to automate the process of tracking and analysing food waste, providing real-time insights and actionable data to kitchen staff. Reducing your food waste helps save on operational costs, it also saves your staff time so they can focus on what really counts - preparing food and delighting your customers.”
Q2: You mentioned Winnow uses it, but what actually is AI?
Shonak: “AI stands for Artificial Intelligence, a technology that enables computer systems to perform tasks that typically require human intelligence. It involves the use of advanced algorithms and machine learning techniques to analyse vast amounts of data, recognise patterns, and make informed decisions. AI is increasingly prevalent in various industries and applications, such as self-driving cars, virtual assistants like Siri and Alexa, personalised recommendation systems in streaming services, and fraud detection in financial transactions. In the context of waste management, AI can be harnessed to automate processes, provide real-time insights, and optimise operations for more sustainable outcomes.”
Q3: How does Winnow use AI?
Shonak: “Our AI-driven cameras and scales are equipped to automatically identify and categorise discarded food items. The process begins with building extensive datasets containing various images of different food items. These datasets serve as training data, allowing our AI models to learn and recognise patterns associated with specific foods.
As kitchen staff dispose of food waste, the AI cameras capture images of the discarded items, which are then processed through our trained models. The AI algorithms analyse these images, comparing them to the patterns learned from the datasets. Through this comparison, the AI models can accurately categorise the type and quantity of food waste generated. The real-time data analysis provides kitchen staff with valuable insights, including the types of food wasted, the quantities, and potential areas for improvement.”
Q4: Why should I choose Winnow’s AI?
Shonak: “There are several reasons why Winnow's AI sets us apart from competitors. Firstly, we were the first to scale this kind of AI back in 2019 - enabling us to expand into 2000 locations worldwide. This backs up our technology with a vast and diverse dataset, helping our AI models to learn and adapt continually - improving accuracy and efficiency. Secondly, we invest significantly in our AI expertise. Our data science team work tirelessly to continuously refine and optimise our AI models, ensuring that we stay at the forefront of the industry. Thirdly, our system is designed to blend into any kitchen’s operation. Disposing of food waste remains a familiar process - just throwing it in the bin as normal with our AI working quietly in the background. Also, our edge computing approach ensures that our system remains versatile, operating in various environments where network connectivity can be unreliable. This multifaceted approach, combining data insights and continuous learning, delivers a higher level of granularity and automation, making Winnow's AI the most effective food waste management solution.
Q5: What do you mean by edge computing?
Shonak: “Edge computing is a critical aspect of Winnow's AI technology. It refers to our system's ability to run our AI technology inside the kitchen itself, at the point at which the user interacts with the system, rather than relying solely on cloud-based computing (this is when data gets sent to remote servers to be analysed which takes a bit longer). This approach ensures real-time analysis and feedback, even in environments with limited or no network connectivity. With edge computing, our AI can offer immediate insights and collaboration with kitchen staff, enhancing data accuracy and decision-making.”
Q7: How has Winnow’s technology evolved over the years?
Shonak: “Winnow's technology has progressively become more powerful and versatile. We have continually expanded our data collection capabilities, increasing the granularity of our waste categorization and prediction models. When we first started, we could only identify the top 8 items. In the past 12 months, we’ve developed to automatically select the top item, enabling the first zero-touch transactions to be logged. This is a huge step, and is done with a level of precision that none of our competitors can achieve.
Q8: What would you say to a commercial kitchen considering implementing AI technology for waste management?
Shonak: “Embracing AI technology for waste management can be a game-changer for commercial kitchens. Winnow Vision can help you track and analyse food waste more effectively, identifying opportunities to optimise production and reduce waste. With real-time insights and actionable data at your fingertips, you can make smarter decisions that drive down your food costs. Our proven track record, and ongoing investment in AI ensure that you'll be partnering with a market-leading solution for your food waste management needs.”
In this Q&A with Winnow's Product Director, Shonak Nathwani, we explore the world of AI and its application in Winnow's technology for food waste management in commercial kitchens. With a vast dataset, ongoing AI expertise investment, and edge computing capabilities, Winnow is a leading solution for efficient and sustainable food waste management. Hopefully you understand a bit more about how generative AI works and real life applications. If you want to learn more about AI’s impact, take a look at our guide.
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