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In US cities and suburbs, felled trees often end up being chipped instead of being made into lumber. This frustrated Ben Christensen, who grew up in New Mexico with a family deeply rooted in the lumber industry – his father was a carpenter – instilling in him a deep respect for trees. Image Note: Image generated by AI, image licensing service Midjourney Christensen points out that the main reason for wood waste is...

In the United States, despite the apparent benefits of recycling, the recycling rate has stagnated in recent years. To address this challenge, AMP Robotics has launched an AI system called AMP ONE to help waste processing plants sort garbage more efficiently. Recently, the company completed a $91 million Series D funding round to further advance the adoption of this technology. Image source note: Image generated by AI, image licensed from MidjourneyAMP Robotics.

With the rapid development of generative AI technology, the amount of e-waste generated is expected to increase significantly in the coming years. A global research analysis predicts that by 2030, AI-related e-waste will skyrocket from 2,600 tons in 2023 to 2.5 million tons. This figure is equivalent to nearly two discarded iPhones for each of the 8.5 billion people worldwide, raising serious concerns about environmental impacts. Image source note: Image generated by AI, provided by the image licensing service Midjourney.

The Director of the China RISC-V Industry Alliance and the founder of VeriWaves Microelectronics, Dr. Weimin Dai, pointed out during the World Artificial Intelligence Conference that the current phenomenon of a hundred models in the AI field is more of a waste of resources.Image Source Note: The image is generated by AI, provided by image authorization service MidjourneyDr. Dai indicated that since the ChatGPT-induced surge in generative AI, many companies have invested in the research and devel

KLM Royal Dutch Airlines employs artificial intelligence technology TRAYS to reduce in-flight meal waste by predicting the actual number of boarding passengers and accurately calculating the required number of meals, resulting in a 63% reduction in food waste, saving tens of thousands of meals, and improving flight operational efficiency and sustainability.

KLM Royal Dutch Airlines utilizes AI large models to reduce the number of in-flight meals, which has decreased food waste by 63%. The AI model TRAYS can accurately predict the actual number of boarding passengers, leading to a 63% reduction in food waste after using the predictive model.

In a South Korean agricultural sorting facility, a technician was mistakenly identified by a robot as a box of vegetables and crushed to death. The incident occurred prior to the equipment's trial operation, raising calls for improved safety measures. With the widespread application of robots, ensuring comprehensive safety measures is crucial.

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