If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
This is, what we aim to at our own factories. Read my introduction to a series of blogposts how we do this. Harnessing the power of artificial intelligence (AI), engineers at our manufacturing plant in Amberg can predict when a key component is likely to fail – up to 36 hours before the failure actually happens. This allows them to react in plenty of time to avoid a costly breakdown of the machine. In our electronics manufacturing facility in Amberg, we have several PCB cutting machines that are deployed for a number of our SIMATIC products – including the S7-300 and ET 200.
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The proven impact of machine learning models has pushed more investment toward their development. Still there are plenty more gains to be realized. From the first harnessing of economies of scale to the introduction of the assembly line, the search for new efficiencies has always been at the heart of manufacturing. Today, the greatest new gains come from the innovative combination of hardware and software. In particular, robotics has revolutionized manufacturing, allowing for greater output from fewer workers.
Using the CB Insights platform, we track where AI is heating up, from health to entertainment. Since 2013, over 3.6K AI startups have raised equity funding globally. The majority of these companies -- like unicorns UiPath, Automation Anywhere, and Face -- sell AI software-as-a-service. Others use AI to develop their core products, including Indigo Agriculture, which leverages machine learning to develop microbial seed treatments. Some other startups -- such as Graphcore, Habana, and Cerebras -- focus on hardware to support AI workloads.
Advances in AI are reshaping the future for airlines. Application areas include crew management, flight maintenance, ticketing, and passenger identification, and they all center on one objective: improving the customer experience. Business and technology grow hand in hand. Companies that don't leverage technology for the good of their customers or employees don't often last. A lot of businesses have failed because they didn't innovate and embrace the new technology and practices their competitors embraced.
Imagine a network of mine sites operated remotely--drilling, analysing core samples, collecting and interpreting data wirelessly from machine to machine, and transmitting real-time information into the cloud, absolutely without physical, human touch. In fact, it is fast becoming the reality in an industry that's increasingly powered by artificial intelligence a.k.a When we think of AI, we think of robots and machines capable of independent thought or autonomous movement. These are possibilities, and even realities, in today's world where practically anything can be automated. AI, however, goes beyond hardware, and its applications are farther-reaching than we can perhaps imagine.
The American Bureau of Shipping recently collaborated with Google Cloud and software engineers SoftServe to use artificial intelligence (AI) models to detect levels of corrosion and marine coatings breakdowns on brown- and bluewater vessels. The pilot project is aimed at developing image recognition software tools that can examine early signs of degradation in hull structures, to avoid unsafe working conditions, unscheduled maintenance and resulting operational downtime. The effort demonstrated how AI can support early detection of structural anomalies that are usually found through traditional, visual inspections. The project was focused on corrosion and coatings failures, but ABS engineers believe the new tools could also be used to detect stress fractures and larger hull deformations. These AI techniques -- in tandem with advanced data algorithms -- could be used to analyze images over time to understand the trends in corrosion and asset fatigue that would support a transition to more efficient class and maintenance regimes for everything from workboats to offshore structures.
Robotic process automation (RPA) can be a great fit for tedious and repetitive processes, but it won't fix a process you don't fully understand or that is otherwise fundamentally broken. That's a basic – and frequent – misstep that commonly leads to an RPA project not achieving its intended goals. Read also: How to explain Robotic Process Automation (RPA) in plain English. "People are trying to apply RPA before they really know how their processes work," says Antony Edwards, COO at Eggplant. "That tends to fail as they are constantly discovering new exceptions and variants."
We have an almost mystical faith in the ability of artificial intelligence (AI) to understand and solve problems. It's being applied across many areas of our daily lives and, as a result, the hardware to enable this is starting to populate our data centers. Data centers in themselves present an array of complex problems, including optimization and prediction. So, how about using this miracle technology to improve our facilities? Machine learning, and especially deep learning, can examine a large set of data, and find patterns within it that do not depend on the model that humans would use to understand and predict that data.
Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups in Industry 4.0. As there is a large number of startups working on a wide variety of solutions, we decided to share our insights with you. This time, we are taking a look at 5 promising artificial intelligence (AI) solutions. For our 5 picks of artificial intelligence startups, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 5 interesting examples out of 214 relevant solutions.