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🗑️ AI’s Pioneering Role in Tackling Global Waste

AI is reshaping the future of waste management

Hello AI Enthusiasts,

The countdown is on! Only a few seats remain in the upcoming Master in Prompt Engineering! Starting on July 24th, this program is designed to help you effectively leverage ChatGPT and incorporate Generative AI into your product and business.

The course boasts:

  • Three live sessions, with recordings available for your convenience plus on-demand video and text lessons.

  • An opportunity to build your AI prototype and add an impressive case study to your portfolio.

  • An insightful curriculum taught by Harvard Professor and AI expert Gianluca Mauro.

No prior technical expertise is necessary!

Take advantage of our installment plan, enabling you to spread your payment over three manageable, monthly installments.

Still not sure? check out a FREE lesson from the program.

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📔 Case study: Greyparrot's AI for Waste Sorting

Mountains of solid waste are a global issue, with 2.24 billion tonnes produced in 2020 and an expected rise to 3.88 billion tonnes by 2050. In direct response to this exigency, Greyparrot, a UK start-up, has innovatively used AI to analyze and help in waste processing and recycling.

Implementing cameras above conveyor belts at over 50 waste and recycling sites in Europe, Greyparrot's AI real-time software analyses what passes through. Despite initial struggles to train the AI system to recognize waste due to varying conditions, the system now tracks 32 billion waste objects annually, creating a comprehensive digital map of waste.

This detailed knowledge not only allows waste managers to be more operationally efficient but also provides valuable data to help shape regulations and influence packaging design.

🧱 Foundational concepts: Resource Utilization

Just like how Greyparrot's AI system interprets different waste materials, AI, in general, needs an effective method to process and analyze various inputs. This Resource Utilization process is where AI's understanding of different variables and inputs is developed and honed.

Different aspects of resources are taken into account, allowing the AI model to analyze and draw valuable insights for better decision-making. This is pivotal in areas like waste management, where technology needs to effectively differentiate between various materials and determine their suitability for recycling or repurposing.

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