Nadia Partners’ Post

Artificial Intelligence: Transforming Modern Industries Artificial Intelligence (AI) has become a key driver of innovation across multiple sectors. By simulating human intelligence, AI allows machines to perform complex tasks that require reasoning, learning, and decision-making. This capability has led to advancements in healthcare, where AI systems assist in diagnosing diseases, and in finance, where AI helps detect fraud and manage investments. Examples: For instance, in healthcare, IBM’s Watson Health uses AI to analyze patient data, helping doctors make informed treatment decisions. In finance, companies like JP Morgan use AI to detect unusual transactions, enhancing security. The Role of AI in Sustainable Development AI also contributes to Sustainable Development Goals (SDGs) by supporting environmental and resource management efforts. AI technology can improve energy efficiency, predict climate patterns, and manage urban resources. Examples: Smart cities, such as Singapore, use AI for traffic management, while AI-driven tools help optimize renewable energy usage. Conclusion AI is not only advancing industries but also supporting sustainability. Its potential to improve efficiency and solve complex problems positions it as a key technology for the future.

Is AI a one man show in digitalization and digitization future for Energy Sector? It is the fact that Artificial Intelligence (AI) is going to re-shape the energy sector. AI is fundamentally changing the way the energy industry operates, moving it towards a more efficient, sustainable, and secure future. AI is Enhancing grid resilience: It has the ability to rapidly process massive amounts of data and detect subtle patterns can assist grid operators in diagnosing and responding to (or avoiding) disruptions in electricity delivery. Machine learning can analyze large amounts of data from various sources, such as usage status, weather data, and historical maintenance records, to predict potential breakdowns or anomalies before they occur. HOWEVER;  AI cannot successfully perform this role without: setting an accurate threshold fully comply with 24/7operation status & conditions, network dip or surges, etc. by experienced operators. Also, AI needs advanced tools to provide him with the maximum possible effective data could be gathered from the assets. This definitely includes the most critical aspects; I like to say Continuous Assets Scanning. AI needs a comprehensive maintenance record includes the applied services, the performance record, the specifications, and manufacturer recommendations. 

Artificial intelligence (AI) technology offers multiple opportunities to enhance the planning, engineering, operation, and maintenance of electrical power transmission systems, thereby boosting their efficiency and reliability. One of the primary applications of AI electrical power transmission systems is load forecasting. By utilizing machine learning techniques, historical data on electricity consumption, weather conditions, and economic events can be analyzed to predict future energy demand. Consequently, companies and institutions can better plan future investments in infrastructure and ensure efficient meeting increasing demand. Furthermore, AI can be used to optimize load dispatching. Through analyzing data related to power flow and equipment status, load dispatching can be improved, and currents can be directed to avoid congestions and enhance transmission efficiency. This aids in improving the system's response to sudden changes in demand or production, ultimately increasing the network's reliability. Additionally, AI can improve maintenance and repairs. By analyzing big data concerning equipment performance, equipment failures can be predicted before they occur, enabling precise and effective preventive maintenance and repairs. This reduces operational downtime and unplanned costs. In conclusion, AI significantly contributes to enhancing the efficiency and reliability of electrical power transmission systems. Through accurate forecasting, improved network load dispatching and predictive maintenance, the system's performance can be substantially enhanced, offering economic, environmental, and social benefits to society as a whole.

ARTIFICIAL INTELLIGENCE IN MAINTENANCE With the rising demand for efficiency and quality in production & manufacturing operations across industries, manufacturers are turning to digitalization for transforming their operations. The advancements in digital technology have brought massive volumes of data at the disposal of maintenance professionals, and they are in search for tools and techniques that can help them parse through this data, to extract meaningful and actionable insights. Artificial Intelligence is the most advanced tool that has the potential to comb through vast amounts of complex machine data and provide the much-needed information to improve maintenance activities. It uses machine learning algorithms to analyze different kinds of data from the machines, to provide real-time insights on machine health. When implemented appropriately, it can detect even small changes in the machine performance, and perform root cause analysis to prevent equipment failures and avoid unplanned downtime. The genuine value of AI is its ability to analyze enormous volumes and different kinds of data, in conjunction with the complex machine operations and real-world applications to provide better understanding of the overall health & performance of industrial assets.

"AI needs large amounts of energy": This keeps coming up, the idea that AI need lots of energy, and as a consequence, it is necessary to increase power generation to provide the tech. This is only partially true. AI in itself does not need energy, it is simply information, and processing of information. AI does not store or use energy. The demand for energy is a result of current computer technology being inefficient and thus waste a lot of energy from thermal losses in semiconductors. It can not be ruled out that improvements in technology will improve efficiency quite considerably, and thus there will not be any need for this power, for AI.

In an era where artificial intelligence (AI) is revolutionizing many industries, the quality of our data is more important than ever. This is especially true when it comes to underground infrastructure: 1) Precision gives better planning AI models can only be as accurate as the data they are trained on. Detailed data about pipes, cables, and other underground installations are essential for precise predictions and planning. 2) Safety and reduction of damages By having comprehensive data, AI can help anticipate and prevent risks associated with excavation or other underground activities, and create machine control data for excavators. 3) Efficiency and shorter time-cycles With accurate AI models based on quality data, we can optimize preventive maintenance, reduce downtime, and save resources. 4) Innovation and new developments The more data we have, the better AI can assist us in developing new, intelligent solutions for managing and monitoring underground infrastructure. This is why DATA is gold. (Picture from this excellent 2020 piece on AI and subsurface https://lnkd.in/dHFu9cvY)

Artificial intelligence (AI) technologies offer multiple opportunities to enhance the planning, engineering, operation, and maintenance of electrical power transmission systems, thereby boosting their efficiency and reliability. One of the primary applications of AI electrical power transmission systems is load forecasting. By utilizing machine learning techniques, historical data on electricity consumption, weather conditions, and economic events can be analyzed to predict future energy demand. Consequently, companies and institutions can better plan future investments in infrastructure and ensure efficient meeting increasing demand. Furthermore, AI can be used to optimize load dispatching. Through analyzing data related to power flow and equipment status, load dispatching can be improved, and currents can be directed to avoid congestions and enhance transmission efficiency. This aids in improving the system's response to sudden changes in demand or production, ultimately increasing the network's reliability. Additionally, AI can improve maintenance and repairs. By analyzing big data concerning equipment performance, equipment failures can be predicted before they occur, enabling precise and effective preventive maintenance and repairs. This reduces operational downtime and unplanned costs, the system's performance can be substantially enhanced, offering economic, environmental, and social benefits to society as a whole.

Here is a great article in the WSJ about how data centers are trying to reduce their needs. With so much growth needed to support the AI demand Power & Cooling will continue to be the biggest hurdles to overcome. https://lnkd.in/g5vJhmAE The authors of this article are: evan.halper@washpost.com caroline.odonovan@washpost.com Remove media AI is exhausting the power grid. Tech firms are seeking a miracle https://lnkd.in/ebN8NjMq

Artificial intelligence (AI) is revolutionizing the tech industry by enabling more sustainable system designs for complex applications. Through generative design, AI can explore a multitude of design alternatives to find the most efficient and environmentally friendly options. This not only enhances the performance of systems but also ensures they are built with sustainability in mind from the outset. AI’s impact on sustainability extends to reducing energy consumption, particularly in data centers. By optimizing operations such as cooling systems, AI has demonstrated the potential to significantly lower energy usage and carbon emissions. This optimization is crucial as the tech industry seeks to mitigate its environmental footprint. However, the development of AI models themselves can be resource-intensive. To address this, the industry is moving towards more targeted, domain-specific AI models that require less data and energy to train. This shift is essential for creating AI solutions that are not only powerful but also sustainable, paving the way for a future where technology advances hand in hand with environmental responsibility.