Construction Technology’s Next Frontier

Artificial Intelligence
Artificial intelligence has the potential to transform manufacturing tasks like visual inspection, predictive maintenance, and even assembly. Cognitive computing is really a term that has been popularized by mainly IBM to describe the current wave of artificial intelligence and, specifically also machine learning, with a twist of purpose, adaptiveness, self-learning, contextuality and human interaction.

These include IBM’s Watson clinical decision support tool, which is trained by oncologists at Memorial Sloan Kettering Cancer Center, and the use of Google DeepMind systems by the UK’s National Health Service , where it will help spot eye abnormalities and streamline the process of screening patients for head and neck cancers.

XAI is one of a handful of current DARPA programs expected to enable third-wave AI systems”, where machines understand the context and environment in which they operate, and over time build underlying explanatory models that allow them to characterize real world phenomena.

But if you modify the training data to have only human-obvious features, any algorithm trained on it won’t recognize—and be fooled by—additional, perhaps subtler, features. Weaving together advances in AI from disciplines such as computer vision and human language technologies to create end-to-end systems that learn from data and experience.

Facebook AI Research

Artificial Intelligence
Dramatic success in machine learning has led to a torrent of Artificial Intelligence (AI) applications. When most people hear the term artificial intelligence, the first thing they usually think of is robots. Today, nearly everyone talks about AI. Like any new major technology trend, the new wave of making AI and intelligent systems a reality is creating curiosity and enthusiasm.

There are a vast number of emerging applications for narrow AI: interpreting video feeds from drones carrying out visual inspections of infrastructure such as oil pipelines, organizing personal and business calendars, responding to simple customer-service queries, co-ordinating with other intelligent systems to carry out tasks like booking a hotel at a suitable time and location, helping radiologists to spot potential tumors in X-rays, flagging inappropriate content online, detecting wear and tear in elevators from data gathered by IoT devices, the list goes on and on.

Instead of talking about artificial intelligence (AI) many describe the current wave of AI innovation and acceleration with – admittedly somewhat differently positioned – terms and concepts such as cognitive computing or focus on several real-life applications of artificial intelligence that often start with words such as smart” (omni-present in anything related to the IoT as well), intelligent”, predictive” and, indeed, cognitive”, depending on the exact application – and vendor.

Artificial Intelligence Is A Must, Not A Need

Technology plays a pivotal role in bringing transitional changes in the lifestyle of humans all over the world. However, even if general human-level intelligent behavior is artificially unachievable, no blanket indictment of AI threatens clearly from this at all. In 2016, there were more than thirty companies testing self-driving cars using artificial intelligence. You will also have a good overview of the main AI techniques and an in-depth understanding of how to apply these techniques in at least one of theareas within Agent Theory, Human and Machine Reasoning, or Cognitive Modelling.

Whether such an outcome would spell defeat for the strong AI thesis that human-level artificial intelligence is possible would depend on whether whatever else it might take for general human-level intelligence – besides computation – is artificially replicable.

These cloud platforms are even simplifying the creation of custom machine-learning models, with Google recently revealing a service that automates the creation of AI models, called Cloud AutoML This drag-and-drop service builds custom image-recognition models and requires the user to have no machine-learning expertise.

Association For The Advancement Of Artificial Intelligence

The University of Georgia has always viewed Cognitive Science and Artificial Intelligence as interdisciplinary fields where computer science meets philosophy , psychology , linguistics , engineering and other disciplines. However, it continues to be a challenge for the current machine learning and neural network models since the continual acquisition of new information from non-stationary data sources generally lead to catastrophic forgetting of previously learned knowledge or abrupt decrease in the precision.

At a very high level artificial intelligence can be split into two broad types: narrow AI and general AI. We cover the latest advances in machine learning, neural networks, and robots. China’s largest funder of basic science is piloting an artificial intelligence tool that selects researchers to review grant applications, in an attempt to make the process more efficient, faster and fairer.

NI Expert Appointed To Top Artificial Intelligence Role

Artificial Intelligence
The European Commission puts forward a European approach to artificial intelligence and robotics. Artificial general intelligence is very different, and is the type of adaptable intellect found in humans, a flexible form of intelligence capable of learning how to carry out vastly different tasks, anything from haircutting to building spreadsheets, or to reason about a wide variety of topics based on its accumulated experience.

In other words, our problems come from the systems being really good at achieving the goal they learned to pursue; it’s just that the goal they learned in their training environment isn’t the outcome we actually wanted. Artificial intelligence refers to the simulation of human intelligence in machines.
The field was founded on the claim that a central property of human beings, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine.