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2️ Cyber Attacks Against Energy (Oil & Gas) and Nuclear Sectors Critical infrastructure across all domains continues to remain a focal point for cyber-attacks, orchestrated by both cybercriminal elements and nation-state actors.
The energy and resources sector is undergoing a profound transformation driven by the global push toward sustainability, energy technological advancements, geopolitical risks, and increasing regulatory pressures in some areas of the world. Every digital fabric has horizontal and vertical digital threads. Digital twins are no different.
This is where harnessing artificialintelligence (AI) and data analytics can help. To assist utility companies, IBM has created the Clean Electrification Maturity Model (CEMM) in conjunction with the American Productivity & Quality Center (APQC). The latter can also help drive efficiency by lowering end-user energy use.
1 The ratio between man and machine All industries use machines, yet the energy and resources sector including utilities , oil and gas , chemicals , and metals & mining industries is the most capital intensive. trillion of annual capital investment is made in the energy industry today and by some estimates will grow to $9.2
Artificialintelligence simulates the human mind by simulating cognitive abilities like learning, reasoning, problems-solving, and decision-making. Sun burst = Corporate strategy & initiatives: The suns burst of energy represents a companys annual release of corporate strategies and initiatives.
Generative AI and digital twin use cases in asset-intensive industries Various use cases come into reality when you leverage generative AI for digital twin technologies in an asset-intensive industry such as energy and utilities. Consider some of the examples of use cases from our clients in the industry: Visual insights.
New developments in renewable energy are making headlines and inspiring hope in communities worldwide, from a remote Arctic village working to harness solar and wind power under challenging conditions to a U.S. Air Force base planning an advanced, utility-scale geothermal power system. Let’s take a look at both.
As more countries, companies and individuals seek energy sources beyond fossil fuels, interest in renewable energy continues to rise. In fact, world-wide capacity for energy from solar, wind and other renewable sources increased by 50% in 2023. What is renewable energy? trillion in 2023. trillion in 2023.
Our reliance on artificiallyintelligent software is deepening, signaling an era, just ahead, of great leaps forward for humankind. Energy at the edges. How microcontrollers distribute energy is a very big deal. This would lead to an optimum blending of private and public sources of energy.
Renewable energy , also known as clean energy, is produced from natural resources that are generated and replenished faster than they are consumed—such as the sun, water and wind. Most renewable energy sources produce zero carbon emissions and minimal air pollutants.
Last week industry leaders, experts, and innovators gathered at the Houston Aquarium for the OpenText Energy Summit in Houston , a pivotal event driving conversations on the intersection of artificialintelligence, information management, and energy sector dynamics.
Insight-driven decisions are required to operate digital energy grids - and keep my EV charged. Last summer, I had an experience that made me realize how, in the future, utility network operators will need to work based on data they get from assets they may or may not own. Decarbonization is challenging network operators.
The utility industry is facing a critical point where it must embrace the vast potential of artificialintelligence (AI) to transform energy production and distribution while addressing significant concerns related to regulations, data security, and ethical considerations.
New technologies are shaping the way we produce, distribute and consume energy. alone has installed nearly 10,000 electricity generation units, connected by more than 300,000 miles of transmission lines and capable of generating over a million megawatts of energy. Historically, the power grid has been a one-way street.
Humanizing utility assets: A new approach to using assets to drive automation. As utilities around the world navigate the path to digitalization, addressing growing customer expectations, the pressure to move to a low carbon economy, and changing operating and business models has become critical. Wed, 12/05/2018 - 00:35.
Urban planning Governments use GIS data and GIS-based solutions for urban planning: zoning and land use projects, natural disaster and health event response, roadway system and building design, utility distribution, energy production, and waste and resource management.
Businesses are increasingly embracing data-intensive workloads, including high-performance computing, artificialintelligence (AI) and machine learning (ML). Carbon footprint in practice Compute, storage and networking are the essential tech resources that consume energy in the process of building applications and services.
Your digital carbon footprint includes emissions from the software delivery process--planning, coding, building, testing, release--in addition to energy consumed from customer use. Decrease your individual energy output with automated tests executed on the cloud. Reduce the footprint of your system under test through virtualization.
We believe there are three core areas that every organization should focus on: sustainability strategy and reporting; energy transition and climate resilience; and intelligent asset, facility and infrastructure management. We also know that using AI requires vast amounts of energy and data.
Artificialintelligence and predictive analytics: The new competitive advantage Artificialintelligence (AI) has evolved from a buzzword to a critical strategic tool for retail and CPG companies. In 2025, AI-driven predictive analytics are no longer optional but essential for survival in a hyper-competitive marketplace.
For instance, when utility officials are aware that a heat wave is on its way, they can plan energy procurement to prevent power outages. 3 While the transition from fossil fuels to clean, renewable energy sources is already underway, accelerating this transition could help further limit emissions, even amid rising global energy needs.
Our top math geniuses point to iO as a cornerstone needed to unleash the full potential of artificiallyintelligent (AI) programs running across highly complex and dynamic cloud platforms, soon to be powered by quantum computers. The math community refers to this bottleneck as “indistinguishability obfuscation,” or iO.
However, in the past few decades, advances in artificialintelligence, sensing, simulation and more have driven enormous impacts within the biotech industry. To that end, we convened five working groups covering healthcare/life sciences, materials science, high-energy physics, optimization and sustainability.
The Rise of ArtificialIntelligence and Machine Learning in Information Governance Trend Overview Artificialintelligence (AI) and machine learning (ML) are transforming information governance by automating complex tasks. Environmental Impact Consideration: Addressing the energy consumption of data centers.
Utilities Digital Journey Insights (Part 3): Data, the new “digital capital” - Going beyond the hype of advanced analytics and AI. This series of blog posts builds on the 2018 CGI Client Global Insights, providing insights into how utilities are making progress toward digital transformation. So where do utilities stand?
Today, utilities and many other industries use drones extensively to conduct surveys, map assets and monitor business operations. Capgemini’s Energy & Utilities Industry Platform is the global industry hub and Centre of Excellence (CoE) for Energy and Utilities. billion in 2022 to USD 47.38
These spanned from being a video editor, interning at startups, assisting in artificialintelligence research, and numerous other stints in between. Support technicians can utilize their technology background to find creative solutions as new issues arise. For example, the green energy giant ENN Group Co.
Artificialintelligence (AI) is revolutionizing industries by enabling advanced analytics, automation and personalized experiences. Frameworks like TensorFlow, PyTorch and Apache Spark MLlib support distributed computing paradigms, enabling efficient utilization of resources and faster time-to-insight.
Currently, other transformational technologies like artificialintelligence (AI), the Internet of Things (IoT ) and machine learning (ML) require much faster speeds to function than 3G and 4G networks offer. As mobile technology has expanded over the years, the amount of data users generate every day has increased exponentially.
Big energy companies expect action whenever there is a move to end drilling leases for federal lands, in exchange for the tens of millions they contribute to congressional reelection campaigns. We should expect these techniques to get better and their utilization to grow, just as we’ve seen in so many other domains.
Enterprise organizations in industries that need to meet strict regulatory compliance standards or comply with data sovereignty laws (manufacturing, energy, oil and gas) frequently choose private cloud environments when they need to meet strict regulatory standards. All the major public cloud providers (e.g.,
Some 5G networks’ download speeds can reach as high as 10 gigabits per second (Gbps) making them ideal for new technologies like artificialintelligence (AI) , machine learning (ML) and Internet of Things (IoT). Examples of mMTC include smart transportation networks, smart factories and smart energy grids.
It integrates advanced technologies—like the Internet of Things (IoT), artificialintelligence (AI) and cloud computing —into an organization’s existing manufacturing processes. Industry 4.0 IDG infographic to understand how you can unlock Industry 4.0 with an asset lifecycle management cloud 2.
The largest models are expensive, energy-intensive to train and run, and complex to deploy. Obsidian models utilize a new modular architecture developed by IBM Research, providing high inference efficiency and levels of performance across a variety of tasks.
Many managers in asset-intensive industries like energy, utilities or process manufacturing, perform a delicate high-wire act when managing inventory. While artificialintelligence (AI) already factors into many inventory managers’ plans, it’s worth keeping an eye on the latest iteration of the technology.
Ongoing CPU trends Several tangential issues will continue to influence CPU development and the use cases for which they are utilized in coming years: Increased use of GPUs: Graphics processing units (GPUs) are an electronic circuit first developed for use in smartphone and video game consoles. AI ASICs: USD 1.5 billion SoC FPGAs: USD 5.2
In the era of digital transformation, digital twins are emerging as a potent solution to energy production challenges. And the increasing adoption of technologies like artificialintelligence (AI), machine learning and IoT will only further enhance the capabilities of digital twins.
Wikipedia tells us “In artificialintelligence, an expert system is a computer system emulating the decision-making ability of a human expert.” I’m not sure why the “in artificialintelligence” is in that statement. Pick your favorite definition of artificialintelligence (AI).
EAMs optimize the quality and utilization of physical assets throughout their lifecycle, increase productive uptime and reduce operational costs. Condition monitoring: Utilize condition-monitoring techniques to collect real-time data on asset performance. Compliance adherence minimizes legal risks and ensures asset integrity.
Automated device compliance through compliance assessments and remediation workflows Automated onboarding of new devices, including bring-your-own-device (BYOD) endpoints and guest users eyeSegment Features Simulate updated policies to determine how they will impact operations prior to activation Enable Zero Trust initiatives with zones, groups, and (..)
Our partnership benefits from IBM’s expertise in cloud computing , artificialintelligence (AI) and analytics, and TCS’s experience in digital transformation, consulting and cloud-engineering services. Furthermore, they met or exceeded all existing latency performance and high-availability requirements for their users.
The need to build on this research has been given impetus by the recent UK government’s Industrial Strategy White Paper 4) Department for Business, Energy & Industrial Strategy, 2017. ↑ Department for Business, Energy & Industrial Strategy, 2017. Industrial Strategy: building a Britain fit for the future.
The oil and gas industry remains an integral part of the energy landscape, but it faces a number of modern challenges, including volatile market conditions, expanding environmental regulations and the growing need for operational efficiency. But the future of EAM in the oil and gas industry is not just about adopting new technologies.
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