Generative AI is the new kid on the block, powering chatbots and image generators and revolutionizing the tech industry. But with great power comes great responsibility, and the question on everyone’s mind is: what is the environmental cost of this powerful new technology?
The Power Problem
Generative AI refers to the ability of an AI algorithm to produce complex data, such as sentences, paragraphs, images, and short videos. As the models become increasingly more powerful, their energy consumption rises. For instance, creating GPT-3, a generative AI model with 175 billion parameters, consumed 1,287 megawatt hours of electricity and generated 552 tons of carbon dioxide. These numbers are equivalent to one person driving 123 gasoline-powered passenger vehicles for one year.
Naturally, people are concerned about the environmental impact of these models and their growing popularity. The energy cost of a single AI model includes manufacturing the computing equipment, creating the model, and using it in production. Furthermore, larger models use more energy during their deployment and receive more generative AI queries, which, according to industry estimates, result in four to five times higher carbon emissions than search engine queries.
However, there is hope for reducing the carbon footprint of generative AI. Models can be made to be more energy-efficient by optimizing the model architecture, processor, and data center. For the same size, using a more efficient model can reduce the carbon footprint by 100 to 1000 times. Furthermore, by using renewable energy sources, the carbon footprint of AI can be significantly reduced. By bringing the computation to locations where green energy is abundant or scheduling computation for times of day when renewable energy is more available, emissions can be reduced by 30 to 40 times.
Chatbots as Popular as Search Engines
Chatbots powered by generative AI are becoming increasingly popular, with models like ChatGPT and Microsoft’s Bing chatbot gaining a considerable following. While chatbots have many uses, including writing documents, solving math problems, and creating marketing campaigns, they do pose an energy consumption problem if each company develops their own models for millions of users. However, AI assistants can offer a better and more direct way to get information than search engines, which could potentially balance out the increased energy use compared to search engines.
As generative AI models become larger and more sophisticated, it is easy to imagine a future where people turn to AI for more tasks, including receiving legal advice, medical expertise, and other expert knowledge.
Saving the Planet
The good news is that more research can be done to develop more energy-efficient AI models. Companies and research labs can publish the carbon footprints of their AI models, facilitating consumers to choose greener chatbots. It’s essential for us to put societal pressure to have more environmentally responsible services globally. By addressing these issues, we can balance the power of generative AI with environmental responsibility, and since AI can work with renewable energy, there is hope yet to minimize it’s carbon footprint.
Editor’s Opinion
The benefits of using advanced AI models in various industries cannot be denied. However, it’s becoming clearer that the growing carbon footprint of AI is becoming a significant concern. It is essential to balance the promise of AI with environmental responsibility to avoid making a bad situation worse. But while we wait for hardware and software breakthroughs that will reduce the environmental impact of AI, we must focus on reducing our energy footprint in other ways- and we must also hope that giant companies throw their weight behind these initiatives. As AI continues to become increasingly integral to everyday life, the need for more energy-efficient models and practices will only grow more pressing.
#Keyword: Generative AI
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