forbes.com
AI Offers Potential Solution to Europe's Crumbling Refinery Sector
Europe's refining sector faces a crisis with one refinery closing monthly in 2025 due to high energy costs and carbon neutrality regulations; however, AI-driven optimization offers potential solutions.
- What are the underlying causes of the decline in Europe's refining sector, and what are the potential long-term consequences?
- Europe's refining sector faces a 35% output reduction projection over 15 years, coupled with a 60% demand increase. This discrepancy is exacerbated by factors such as increased competition from Asia and the Middle East. Applied Computing's AI solution, Orbital, aims to mitigate this by optimizing energy usage and improving efficiency across existing infrastructure.
- What is the immediate impact of refinery closures in Europe, and how might AI solutions like Applied Computing's Orbital mitigate this?
- On average, one European refinery per month shut down in 2025 due to high energy costs, competition, and carbon neutrality regulations. This trend threatens Europe's industrial output and energy independence. AI-driven optimization, as offered by Applied Computing's Orbital, could significantly reduce energy consumption and costs, potentially reversing this decline.
- How might the success or failure of AI solutions like Orbital influence future trends in the European energy sector and broader industrial policy?
- Applied Computing's Orbital, using multi-foundation AI, could reduce refinery energy consumption by 10%, saving billions. Successful scaling of this technology across European refineries within the next year is crucial to prevent further decline in the sector and maintain energy security. The company's significant seed funding and expansion suggest a strong push towards market penetration and potential broader impact.
Cognitive Concepts
Framing Bias
The article frames the narrative to highlight the potential benefits of AI, using strong positive language and focusing on the success of the startup. The headline and introduction emphasize the dire situation in the European refining sector to create a sense of urgency and highlight the AI solution as a savior. This framing might overshadow potential risks or limitations of relying solely on AI.
Language Bias
The article uses strong, positive language to describe the AI solution, such as "stem the tide," "reverse it," and "savior." Terms like "dire" and "bleak" are used to describe the situation, creating a sense of urgency and potentially inflating the perceived impact of the AI solution. Neutral alternatives include describing the situation as "challenging" or "complex" and emphasizing that AI is "one" potential solution, rather than "the" solution.
Bias by Omission
The article focuses heavily on the potential of AI to solve the European refining crisis, but omits discussion of alternative solutions or policy changes that could address the issues of high energy costs, increased competition, and carbon neutrality regulations. While acknowledging the limitations of space, a broader perspective on potential solutions would enhance the article's completeness and avoid presenting a potentially skewed view.
False Dichotomy
The article presents a false dichotomy by framing the situation as a choice between accepting industrial decline or adopting AI solutions. It overlooks other potential mitigation strategies, such as government subsidies, technological innovation in other areas, or adjustments to carbon neutrality policies. This simplification overstates the impact and necessity of AI.
Gender Bias
The article focuses primarily on the male CEO of the AI startup. While this is understandable given the focus on the company, mentioning other key individuals, or providing more balanced representation of gender within the broader refining industry would provide a more complete picture.
Sustainable Development Goals
The article highlights the use of AI to improve efficiency in the energy sector, specifically in refineries and petrochemical plants. This innovation can contribute to sustainable industrial development and boost economic growth by reducing energy consumption and costs. The development and implementation of AI-driven solutions like Orbital directly support industrial innovation and infrastructure improvement.