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) …
IBM and Verizon have announced a joint venture in which the companies will work together on 5G and edge computing technology to help enable the future of industry 4.0. The partnership will combine the high speed and low latency of Verizon's 5G and Multi-access Edge Compute capabilities, IoT devices and sensors with IBM's expertise in artificial intelligence, hybrid multiload, edge computing, asset management and connected operations. In a press release, the companies said the partnership will help industrial enterprises find ways to use edge computing to accelerate access to near real-time, actionable insights into operations to improve efficiencies. The first solutions planned from the collaboration are to mobile asset tracking and management solutions to hep enterprises improve operations, optimize production quality and enhance worker safety. For those first solutions, the companies plan to leverage Verizon's 5G Ultra Wideband network, Multi-access Edge Computing (MEC), ThingSpace IoT Platform and Critical Asset Sensor solution, which will be jointly offered with IBM's Maximo Monitor with IBM Watson and advanced analytics.
Imagine an automated meeting room, whether it be a conference room, lecture hall, or council chambers. The displays turn on automatically, the lights dim or brighten to the right level, previously configured for the type of meeting you are having. Cameras focus on whoever is speaking, switching seamlessly from presenter to audience member, when required. Inconspicuous microphones pick up high-quality sound. Recording or conferencing begins automatically, on schedule, or by voice command.
Artificial intelligence vision silicon company Ambarella is partnering with Amazon Web Services to allow AWS customers to use the tech giant's services to train machine learning models and run them on devices equipped with Ambarella's CVflow AI vision chip. According to Ambarella, developers previously had to manually optimize machine learning models for devices based on the company's AI vision system on chip (SOC), a step that could add delays and errors to the app development process. In an announcement, the companies said they collaborated to simplify the process by integrating the Ambarella toolchain with the Amazon SageMaker Neo cloud service. Now, developers can bring trained models to Amazon SageMaker Neo and automatically optimize the model for Ambarella's CVflow-powered SoCs, the companies said. Using MXNet, TensorFlow, PyTorch or XGBoost, customers can train the model using Amazon SageMaker in the cloud or their local machine.
Smart technology, artificial intelligence and machine learning are grabbing headlines every day, and those familiar buzzwords are now inescapable. Algorithms are being enhanced and scientists are coming up with new ways to train and teach these models. According to VentureBeat, machine learning is also shaping business and society. The publication spoke to five leading artificial intelligence experts for their input on what we'd see happen in machine learning in the new year. PyTorch creator Soumith Chintala, University of California professor Celeste Kidd, Google AI chief Jeff Dean, Nvidia director of machine learning research Anima Anandkumar, and IBM Research director Dario Gil said great strides were made in several fields in 2019, like natural language-based models and reinforcement learning, but the five AI experts were essentially unanimous in predicting an even more exciting 2020.
With the help of computational pathology firm Paige, healthcare technology giant Royal Phillips is bringing clinical artificial intelligence to pathology laboratories to help improve a pathologist's workflow and treatment planning for patients. According to a joint news release Thursday, this strategic collaboration will first start with Paige Prostate to help pathologists quantify and characterize cancer in tissue samples and make precise and efficient diagnoses. The release noted the need for more advanced cancer diagnosis technology as the number of cancer cases rises. Glass slide-based laboratory workflows are being converted to digital using solutions like ones offered by Phillips. Once digital images are created, the CE-marked Paige Prostate software is applied automatically to detect and localize prostate cancer, providing pathologists with valuable information they can use to evaluate prostate biopsies.
Technology, artificial intelligence and automation are supposed to solve our biggest problems, not create new ones or exacerbate existing issues. Unbeknownst to many, big tech is actually putting a huge burden on the environment. In a study assessing the energy consumption required to train several common large AI models, Researchers at the University of Massachusetts Amherst said artificial intelligence emissions can be over 626,000 pounds of carbon dioxide, which is about 5 times as much the lifetime emissions of an average car. According to research firm IDC, spending on AI systems is exploding, with the figure expected to hit nearly $98 billion in 2023, more than 3.5 times the $37.5 billion being spent this year. The U.S. is expected to deliver more than half of that spending through the forecast, which will be led by the retail and banking industries, according to IDC.
Artificial intelligence technology is an incredible advancement and is paving the way for the future of big tech and the way humans live. Just this morning, my iPhone told me how long it would take to get to work without me even moving a finger. Thanks to my spam filter, I don't even see the very legit emails offering me a fast $15,000 personal loan or a $100 Visa gift card. Those artificial intelligence technology applications are small potatoes in the greater AI world, but tech companies are pushing the technology's limits and the field is rapidly advancing -- sometimes at the expense of society. Please do develop applications and technology that make our lives easier, but we should be smart about it and not release technology that has to constantly be updated before it actually works the way it was intended.
Machine learning and artificial intelligence are by no means perfect, and it takes human intervention to constantly tweak algorithms. Those applications are essentially based on math problems and may never bee 100% accurate, so companies and software developers should think carefully before going down that road. At a recent conference, TWIMLcon: AI Platforms, panelists spoke about the ethics of artificial intelligence and the need for its human developers to take painstaking actions to ensure these applications work for everybody. Any one group or central team should not be the only to write code and fix fairness or the whole company. To do this, companies must have a diverse group of people working on these applications.
The question that seems to get asked more often than not is to talk about how many industrial applications we can name for machine learning. Industrial machine learning is not a device you can plug into a production line and make the production line operate better than it did before. Machine learning is a process that needs inputs from many devices to feed data to it so that data can be collected, evaluated, and used to develop knowledge about how a production line produces the products and parts it does. That knowledge can then be used to determine how production line can have a higher throughput of parts, operate at a lower cost, and run more reliably. In that way, industrial machine learning transforms an industrial operation into a system of systems that can get products to market faster at a lower cost so the company that owns it can remain competitive in its market and keep their customers happy by delivering the products they want.
In recent years machine learning is gaining more and more popularity, but what exactly is it? The name "machine learning" initially originated from famous gaming researcher Arthur Lee Samuel. Samuel is the first person to bring self-learning programs into society. This remarkable discovery shortly laid the foundation for machine learning algorithms. In later years, rising popularity in artificial intelligence give birth to many innovations in the field of Computers and Automation.