There are two basic ways to understand the world of AI: artificial general intelligence (general AI, or AGI) and narrow artificial intelligence (narrow AI). Narrow AI is the use of machines to intelligently solve specific problems, while general AI is a machine or group of machines that have the complete cognitive capabilities of a human. Contrary to what the science fiction movies might suggest, general AI is still a long way off. The main challenge to general AI is that, well, we don't fully understand what consciousness is.
Cognitive security, or artificial intelligence, can "understand" natural language, and is a logical and necessary next step to take advantage of this increasingly massive corpus of intelligence that exists. Pairing humans and cognitive security solutions will help make sense of all this data with speed and precision, accomplishing response in a fraction of the time. Deep Blue as it is Kasparov consulting with Deep Blue before deciding on his next move against an unknown opponent. Defense works best when people and machine work together.
In this special guest feature, Mike Brooks, Senior Business Consultant at AspenTech, discusses how companies can no longer rely solely on traditional equipment maintenance practices but must also incorporate operational behaviors in deploying data-driven solutions using machine learning. For example, a North American energy company was losing up to a million dollars in repairs and lost revenue from repeat breakdowns of electric submersible pumps. In another case, a leading railway freight firm operating across 23 states in the US used Machine Learning to address perennial locomotive engine failures costing millions in repairs, fines, and lost revenue. Companies can no longer rely solely on traditional maintenance practices but must also incorporate operational behaviors in deploying data-driven solutions.
Artificial intelligence (AI) is already proving its value to oil and gas companies, and yet widespread adoption of AI technologies within the industry still faces lots of hurdles. "The barriers for oil companies to adopting new AI technologies are many, ranging from resistance to change, a belief that what they already have is sufficient, and skepticism about whether new technologies will deliver," said Ray Hall, energy sector director at Tessella, a provider of engineering and consulting services that has helped global energy companies identify ways to improve drilling and operational efficiency with data. It's important, from a competitive standpoint, that oil and gas companies overcome the challenges in adopting AI and other emerging technologies, because the industry is facing challenges on many levels. For example, it worked with one oil customer to help the company improve its understanding of durability and levels of corrosion of existing wells, as part of the company's plan to get greater returns from wells.
Cheat Sheet Posted on Monday, July 31st, 2017 at 12:16 pm. Vertica 8.1.1 provides SQL functions that support the complete machine learning workflow--from cleaning your data to training a model to evaluating model performance. Vertica machine learning is fast and scalable along the sizes of data samples, features, and computing cluster. If you're new to Vertica machine learning or you want a quick reference of the functions in the 8.1.1 offering, check out this cheat sheet.
Sunway TaihuLight, the world's fastest computer, has modelled the birth and early expansion of the universe using 10 trillion digital particles, a new report claims. Sunway TaihuLight (pictured), the world's fastest computer, has modelled the birth and early expansion of the universe using 10 trillion digital particles, a new report claims In astronomy, researchers simulate the universe by breaking down its mass into particles. The supercomputer may be used to conduct earth system modelling, ocean surface wave modelling, atomistic simulation, and phase-field simulation. The supercomputer may be used to conduct earth system modelling, ocean surface wave modelling, atomistic simulation, and phase-field simulation.
OpenText has launched an artificial intelligence platform built on top of OpenText Analytics and Apache Spark. "It is an open platform built on open standards like HTML5, Java, SQL, and Hadoop," Barrenechea wrote. Because it is built on open standards, Magellan is embeddable, offering our customers access to a wealth of well-studied and well-written algorithms." Although not mentioned in the announcement, OpenText has positioned Magellan as a challenger to IBM's Watson cognitive computing platform.
AI is already helping engineering companies model new jet engine designs, oil companies predict where to drill for oil, drug companies indentify promising new areas for research. Data analytics allowed companies to identify interesting patterns in data which could help them better target customers and understand operations – transforming online sales and marketing, and well understood production processes. Next is the AI infrastructure layer, which allows developers to build AI tools such as machine learning and neural nets using existing frameworks. Companies which identify a problem that needs solving; understand the context, find the right data, apply the right intelligence and build the right solutions with the right tools will be the ones who bring about the next big disruption.
Example: GoodYear Tire Confidential and Private 14 • ServiTIZE the Product • Service-led Competitive Strategy • Participate in a Larger Value Chain/Stream • Value-based Pricing in an Otherwise Commodity, Cost- Plus Environment • Must Understand the Customer's Business Process and Determine the Right Business Model Extended Value Chain Opportunities Advanced Services Intermediate Services Integrated Products/Systems Augmented Product Use information to Move Beyond the Product Use Information to Sell The Product as a Service Use Information to Improve The Product in Use Use Information to Improve The Product Product Monitoring Services Supporting Customers Services Supporting Products Categories of Value Creation from IoT Source: Goodyear Global Innovation Dept. IIoT Predictive Maintenance Model Should Include • Technology Solution that has easy "bolt on" connectivity outside SCADA or IIoT • Automated Alerting and Dashboard Reporting • People and Process to Interject with Alerting • People and Process with Domain Experience to Diagnose and offer Prescriptive Solution • People and Process to Schedule Maintenance • People and Process to Repair Equipment Confidential and Private 41 40.
The report found that digital transformation is not just about adopting the technologies of the past: 62% of research participants expect to have technology such as virtual advisors in their organisations within the next two years. "Organisations have grown their use of analytics to understand how these technologies impact their business performance: 64% use analytics to improve their customer services, and 58% use analytics to benchmark their workplace technologies." However, the number one barrier to successful adoption of new work styles was IT issues, and research participants cited organisational issues as another. Enterprises are also turning to new workplace technologies to drive increased customer service, with 45% of respondents saying they've improved customer satisfaction as a result of their use of digital workplace technology.