Wallace, Scott A. (Washington State University Vancouver) | Patel, Bhadresh (Washington State University Vancouver) | Kryger, Landon (Washington State University Vancouver) | Seley, Susan (Data Data Inc.)
We describe a collaborative project between our research group and a small west-coast business to apply machine learning techniques to a document processing task. This experience suggests two key points: (1) even as machine learning and artificial intelligence matures, there are many business applications that have not yet exploited these techniques; and (2) academically well-established machine learning techniques have much to offer both in terms of flexibility and economic benefit.
The next evolution in cloud computing is a smarter application not in the cloud. As the cloud has continued to evolve, the applications that utilize it have had more and more capabilities of the cloud. This presentation will show how to push logic and machine learning from the cloud to an edge application. Afterward, creating edge applications which utilize the intelligence of the cloud should become effortless.
The CBR field has grown rapidly over the last few years, as seen by its increased share of papers at major conferences, available commercial tools, and successful applications in daily use. This forum is intended to gather AI researchers and practitioners with an interest in CBR to present and discuss developments in CBR theory and application.
Artificial Intelligence became one of the most dominant topics in 2019 but, together with machine learning and data analytics, these technologies are continuously delivering practical applications and dramatic changes in many industries and are impacting our our daily life. We're living in the age of automation, and thus, with the increasing spread of AI in almost all industries, the challenges are growing in addition to the areas of application. Therefore, it's time to make our policies right in order to maximize the advantages without wasting any time. Here below we've tries to demonstrate the application of AI shaping different industries in 2020:
The power behind self-driving cars, real-time facial recognition, and intelligent robots is called machine learning,a subfield of artificial intelligence (AI).The first formal definition of AI came from Arthur Samuel in 1959: "A field of study that gives computers the ability to learn without being explicitly programmed."They've Currently, machine learning not only enablescomputers to park our cars and win at Jeopardy, it also allows them to beat humans at chess and Go, and to learn for itself how to play new games without any instruction.Although these are all very flashy applications of this technology, the business applicability has so far been limited. Nevertheless, understanding how machine learning algorithms work can be very useful in a business context. This can also lead to potential applications in sales, marketing, finance, and HR that can drive better decisions and give you a competitive edge.