Powering the Future: AI's Sustainable Path Forward
The buzz around artificial intelligence (AI) is louder than ever, with its integration and demand skyrocketing across different sectors.
From giants in the industry to budding enterprises born in the era of digital innovation, the race to infuse AI within their service offerings is fierce.
The topic, which was a focal point at the World Economic Forum in Davos, brings to attention a concerning projection: AI's energy consumption may soon rival that of entire countries. Thus, it begs the pressing question of sustainable AI utilisation on a global scale.
AI's hunger for energy: A global challenge
Upon revelations that AI's power needs might soon mirror those of countries as large as the Netherlands, experts like Maxime Vermeir, a Senior Director at ABBYY, are investigating ways businesses can engage with AI both effectively and sustainably.
Maxime highlights the shortcomings of generative AI and large language models (LLMs) due to their extensive data demands, which not only raise ethical, accuracy and privacy concerns but also significantly increase energy consumption.
“Many drawbacks of generative AI and LLMs stem from the massive stores of data that must be navigated to yield value,” he explained. “Not only does this raise risks in the way of ethics, accuracy and privacy, but it grossly exacerbates the amount of energy required to use the tools.
“Instead of highly general AI tools, enterprises have begun to pivot to narrower purpose-built AI, specialised for specific tasks and goals. For example, ABBYY has adopted this approach by training its machine learning (ML) and natural language processing (NLP) models to specifically read and understand documents that run through enterprise systems just like a human.
“With pre-trained AI skills to process highly specific document types with 95% accuracy, organisations can save trees by eliminating the use of paper while also reducing the amount of carbon emitted through cumbersome document processes.”
He notes a shift towards more focused AI solutions, designed for targeted tasks and outcomes, as a more energy-efficient strategy. ABBYY’s approach, for instance, trains AI to comprehend documents similarly to a human, achieving impressive accuracy and environmental benefits.
Moreover, Maxime champions the role of developers in advancing AI's sustainable future, as seen with OpenAI's introduction of developer-customisable ‘GPT’ platforms. This move towards customisation helps to limit the ecological toll of AI by doing away with superfluous features and data.
“Companies should also take a step back from the technology itself,” he continued, “and look inside their organisation for more ways to sustainably leverage AI.” An example he poses is Microsoft, which revealed that its AI-supporting hardware runs exclusively on clean energy, absolving them of creating and omitting ‘operational emissions’.
“Moreover, companies can use AI as a tool to explore other facets of their business in which sustainability could be prioritised.”
Maxime also urges companies to look beyond technology itself and find other sustainable AI applications, such as Microsoft's commitment to clean energy for its AI hardware. This approach not only addresses operational emissions but also demonstrates how AI can spotlight other areas within businesses where sustainability can be enhanced.
The research by Forrester further underscores AI's potential in sparking a green revolution, with its advanced capabilities of measurement, reporting and data visualisation.
Maxime concludes with a reminder that ecological impacts extend beyond emissions, referencing studies where robotics and AI have drastically cut herbicide usage.
“Although objectively important, emissions aren’t the only metric used to encompass ecological impacts — studies have shown that a combination of robotics and AI have reduced herbicide use in some contexts by 90%," he said. “As companies continue to grapple with the utility and consequences of AI, they must explore the full breadth of its capability to enhance and contribute to sustainability.”
As the dialogue around AI's utility and environmental impact continues, exploring its full spectrum of sustainability capabilities becomes imperative.
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