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Understanding Artificial Intelligence

10-Dec-2018 10:25:38

ai-article-heroStockfish and Deep Blue can beat world chess champions, Alexa can recognize your voice, your spam filter curbs annoying emails and your credit card provider can spot fraud. But real artificial intelligence goes much further… it’s about having a machine that learns, thinks and makes decisions in much the same way as a human.


Inside AI: the future Brain of the Smart Grid

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In the upcoming issue of our pathway magazine, we will be taking a deep dive into artificial intelligence and how it is set to transform the energy industry.

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AI at a Glance


Artificial Intelligence (AI)

AI is a broad term that refers to machines acting intelligently. It focuses on creating systems capable of using data to learn, decide, solve problems, plan, adapt and continually improve performance. AI has long caught people’s interest and imagination, including in its most famous sci-fi forms, HAL 9000, Terminator and Skynet.

Narrow Artificial Intelligence (NAI)

Narrow artificial intelligence, or ‘weak AI’, involves machines focused on performing single narrow tasks – usually binary questions that the computer program asks in sequence until it can provide a relevant answer. Used to automate repetitive service tasks, NAI examples include internet bots and Apple’s virtual assistant, Siri.

Artificial General Intelligence (AGI)

Also called ‘strong AI’, ‘full AI’ or ‘human-level AI’, AGI is machine intelligence that performs a task as well as or even better than a human, and with no requirement for programming in advance. Combining human-like flexible thinking and reasoning with super-fast data processing, AGI could soon be reality.

Machine Learning

 A field of AI, machine learning centers on algorithms that use often large volumes of data to continually increase efficiency and performance while completing tasks. It involves getting computers to learn, act and improve with experience without being explicitly programmed, and without need for human intervention.

 

What Can the Energy Industry Gain from AI?

 

lg-icon-46-blueSupply and Demand Optimization

Machine learning can be used to automate and improve demand management. AI, for example, can analyze usage data and predict peaks in supply and demand.

 

Customer experience and engagement

AI facilitates segmentation and micro-targeting makes it easier to forecast individual activities. The energy industry is able to provide new customer services.

 

Operations and outage managementlg-icon-12-blue

To keep a reliable grid, AI algorithms can automatically detect and address vulnerabilities in self-healing networks. The grid is able to reconnect with other parts automatically.

 

lg-icon-34Asset optimization and predictive maintenance

AI algorithms are able to monitor conditions of assets for predictive maintenance in real time. The energy industry is able to optimize its asset management.

 

lg-icon-09-blueRevenue protection and security

AI algorithms can help the energy industry to secure its grids by analyzing usage patterns, consumption profiles and other customer data to avoid energy theft and other external attacks.

 

Artificial Intelligence by the Numbers

 

$19.1 billion

Worldwide spending on cognitive and artificial intelligence systems by 2018 (Source: IDC)

$52.2 billion

Worldwide spending on cognitive and artificial intelligence systems by 2021 (Source: IDC)

1.8 million

Number of jobs will be replaced by AI in 2020 (Source: Gartner)

2.3 million

Number of jobs AI will create by 2020 (Source: Gartner)     

83%

of top European utilities executives consider artificial intelligence a high to medium priority for their business (Source: Roland Berger)

5%

have defined clear strategic targets, strategy and an implementation roadmap (Source: Roland Berger)                                        

 

Interested about the impact of AI on the energy industry? Click below to receive a notification when the next issue of our pathway magazine is released and download it for free.

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