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) …
We are able to turn on the lights in our homes from a desk in an office miles away. The built-in cameras and sensors embedded in our refrigerator let us easily keep tabs on what is present on the shelves, and when an item is close to expiration. When we get home, the thermostat has already adjusted the temperature so that it's lukewarm or brisk, depending on our preference. These are not examples from a futuristic science fiction story. These are only a few of the millions of frameworks part of the Internet of Things (IoT) being deployed today.
Learn how AI is driving the future of video surveillance technology. See how it can play an important role in mitigating risks and creating a safer environment for organizations. This webinar will highlight the benefits of Artificial Intelligence which includes reducing the occurrence of false alarms during active monitoring, increasing efficiency during forensic review, and reducing storage and bandwidth requirements - all while turning your surveillance into actionable business intelligence. Aaron M Saks, MSIT Sr. Product and Technical Training Manager Mr. Saks is the Sr. His primary responsibilities include managing the development of training and certification programs for various user groups.
Digital health products played a prominent role in addressing the COVID-19 pandemic and in helping caregivers and patients navigate their care in the past year. Going into 2022, remote monitoring, wearables, sensors, and other mobile health (mHealth) products are taking center stage in defining the future of medicine. "One of the clearest areas of excitement now and into the future is the sector of healthcare products referred to as wearables. These are devices like fitness trackers, heart monitors, and other devices that record in real time and communicate biometric data either directly to the user or to a connected platform for a variety of purposes, including coaching, intervention, analysis and even within clinical trials administration," notes a recent report from contract manufacturer Jabil, St. Petersburg, FL. The report, "Digital Health Technology Trends," finds that "the top three solution categories providers are developing or plan to develop are in patient monitoring, diagnostic equipment, and on-body or wearable devices (see Figure 1). As digital and mHealth capabilities have become an integral part of many medical devices and diagnostics, they have enabled a more agile and flexible healthcare system to emerge in the face of COVID-19. These products will continue to improve access to patient care. Digital transformation of healthcare is not just about adopting new digital technology, notes a recent position paper from medtech giant Philips. It's about reimagining healthcare for the digital age -- using the power of data, artificial intelligence (AI), cloud-based platforms, and new business models to improve health outcomes, lower the cost of care, and improve the human care experience for patients and staff alike."
AIOps and MLOps are both essential components of an AI-powered business. Many companies have used these terms interchangeably in recent years, but there is a difference between them. Understanding that difference can help you understand what role AI will play in your organization and how it will change your business practices. Artificial intelligence for IT operations, also known as AIOps, is a category of tools and strategies that allows organizations to take advantage of big data and machine learning. AIOps uses artificial intelligence to automate and optimize tasks in enterprise IT infrastructure.
Italy suffers from a serious problem of water wastage, linked both to factors of education in the use of resources by citizens and to leaks in the pipelines due to obsolescence and wear and tear of the pipes, as well as the malfunctioning of the meters. The problems of the distribution network also determine inefficiencies (in particular interruptions in the water supply), which in the south of the country occur three times more frequently than in northern regions. Revelis, the company where I work, developed an IoT platform able to monitor a water delivery network in a district of Catanzaro (a small italian town that you'd probably didn't know before). The project is still under development but few milestones has been achieved. This component is responsible for the monitoring of several tracked objects.
In factories and manufacturing organizations, robots are no longer new. For decades, robots have improved productivity and offloaded workers so they can focus on other high-level tasks. Now, RPA is increasing the same level of productivity for employees of companies that do high-volume work, IT support, and workflow processes. Using RPA tools as part of a larger business process automation strategy, you can easily configure software "robots" to trigger responses, reconcile data, and communicate with other digital systems. Applications range from, for example, the simple task of generating an autoreply message to an email deploying thousands of pre-programmed bots each to automate ERP tasks.
The railroad industry is one of the most complex industries in terms of digitization. From a technical perspective, it has many barriers that make it rather difficult to integrate existing systems into modern digital architectures. This can explain its low level of digitization. IoT Edge Computing can be the answer to many of the challenges for railroads. In a study in the Harvard Business Review, the transport industry is identified at the tail of digital maturity, and the rail sector, in particular, contributes significantly to this low level of digitization.
If you read news, follow research articles, and discuss the future, then you would have already read about how the healthcare industry is in dire need of AI. If I were to pick the prominent industries which can drive sustainable growth healthcare would be on the top. Perhaps it is the reason that majority of new research now includes terms "renewable, sustainable, and eco friendly". Humans have realized that growth at the risk of environmental deterioration, and deteriorating human health is no growth at all. There is another parallel industry that is being explored by the inventors and it is "artificial intelligence".
Every day, millions of articles and papers are published. While there is a lot of knowledge hidden in those articles, it is virtually impossible to read all of them. Even if you only focus on a specific domain, it is still hard to find all relevant articles and read them to get valuable insights. However, there are tools that could help you avoid manual labor and extract those insights automatically. I am, of course, talking about various NLP tools and services. In this blog post, I will present a solution of how you can combine the power of NLP with knowledge graphs to extract valuable insights from relevant articles automatically.
Humming in the background of everyday life, artificially intelligent systems are operating complex tasks--but there are limits. They can't adapt to ever-changing environments without human help. They can't yet teach and maintain themselves. And their full potential has yet to be realized. One of his research projects aims to develop a rigorous, scalable learning framework that will enable AI systems to self-assess their performance and continually expand upon their prior knowledge.