Quantum Computing: The Next Big Thing for Oil Exploration?
Quantum computers exploit the peculiar behavior of objects at the atomic scale and use the qubit as the basic unit of quantum computing. A quantum computer with only 100 qubits would, theoretically, be more powerful than all the supercomputers on the planet combined.
Training a Single Artificial-Intelligence Model Can Emit as Much Carbon as Five Cars in Their Lifetimes
Researchers at the University of Massachusetts, Amherst, performed a life-cycle assessment for training several common large AI models. They found that the process can emit more than 626,000 lbm of carbon dioxide equivalent—nearly five times the lifetime emissions of the average American car.
Strengthening the Energy Sector’s Cyber Preparedness
The reality is that threats continue to outrun the sector’s security evolution, primarily because organizations are increasingly connecting operational technology, such as supervisory control and data acquisition systems and industrial control systems, to their information technology networks.
AI-Generating Algorithms: An Alternate Paradigm for Producing General Artificial Intelligence
This paper describes a path to general artificial intelligence (AI) (i.e., AI that is as smart or smarter than humans) based on the trend in machine learning that hand-designed solutions eventually are replaced by more-effective, learned solutions.
No Cloud Required: Why AI’s Future Is at the Edge
The algorithms for running AI applications have been so big that they’ve required powerful machines in the cloud and data centers, making many applications less useful on smartphones and other edge devices. Now, that concern is quickly melting away, thanks to a series of recent breakthroughs.
Integrated Internet of Things Platform Helps Close the Gap Between Data Science and Operations
Arundo Analytics has built an integrated industrial Internet of things platform that allows data scientists to productize data-science solutions and accelerate feedback/improvement iterations between end-users and data scientists effectively.
Microsoft Launches Drag-and-Drop Machine-Learning Tool
Microsoft announced three new services that aim to simplify the process of machine learning—an interface for a tool that automates the process of creating models; a new no-code visual interface for building, training, and deploying models; and hosted Jupyter-style notebooks for advanced users.
Researchers Want To Study AI the Same Way Social Scientists Study Humans
Maybe we don’t need to look inside the black box after all. Maybe we just need to watch how machines behave, instead.
Neural Networks Plus CFD Speed Up Simulation of Fluid Flow
High-fidelity 3D engineering simulations are valuable in making decisions, but they can be cost-prohibitive and require significant amounts of time to execute. The integration of deep-learning neural networks with computational fluid dynamics may help accelerate the simulation process.
DeepMind and Google: The Battle To Control Artificial Intelligence
AGI stands for artificial general intelligence, a hypothetical computer program that can perform intellectual tasks as well as, or better than, a human. AGI will make today’s most advanced AIs look like pocket calculators.
Harnessing Organizational Knowledge for Machine Learning
In collaboration with Stanford University and Brown University, Google explores how existing knowledge in an organization can be used as noisier, higher-level supervision—or, as it is often termed, weak supervision—to quickly label large training data sets.
Collaboration Redefines the Human/Robot Relationship
Robots have been a part of industrial production for decades, but the interface between humans and robots has changed as automation technologies increased in complexity, scope, and scale. Once a novelty, collaborative robots are projected to become a significant element of the automation landscape.
Foundations Built for a General Theory of Neural Networks
Neural networks can be as unpredictable as they are powerful. Now mathematicians are beginning to reveal how a neural network’s form will influence its function.
How AI Can Help Solve Some of Humanity’s Greatest Challenges—and Why We Might Fail
In 2015, the United Nations ratified the 2030 Sustainable Development Goals. Technology will be critical in the pursuit of these ambitious targets, but the pace and scale of change creates risks that humanity must take very seriously.
Analysis of 16,625 Papers Points to the Future of AI
A study of 25 years of artificial-intelligence research suggests the era of deep learning may come to an end.
Industrial Internet of Things Can Improve Profitability and Integrity Management
For too long, owner/operators have managed operational profitability using paper-based processes or monthly reporting cycles. In the new technological climate, this approach has been proven to be less effective. Enter the industrial Internet of things.
Houston Startup Creates the Alexa or Siri for Oil and Gas Companies
Nesh's digital assistant technology wants to make industry information more easily accessible for energy professionals.
Greedy Pursuit: Algorithms Show Promise in Measuring Multiphase Flow
“Greedy pursuit” in the realm of algorithms is a good thing. Saudi Aramco studied such algorithms to produce images simulating the flow inside a pipe’s cross section, possibly reducing the need for separator-based multiphase flowmeters.
How Algorithms Are Taking Over Big Oil
Artificial intelligence has come to the oil patch, accelerating a technical change that is transforming the conditions for the oil and gas industry’s 150,000 US workers.
Predictive Analytics Will Help Oil Companies Forecast the Future
The ability to predict the future to optimize operations has been the aim of oil and gas companies for some time. Could that time finally be here?
Radical New Neural Network Design Could Overcome Big Challenges in AI
Researchers borrowed equations from calculus to redesign the core machinery of deep learning so it can model continuous processes like changes in health.
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03 July 2019