Magneto-optical driveA magneto-optical drive is a kind of optical disc drive capable of writing and rewriting data upon a magneto-optical disc. Both 130 mm (5.25 in) and 90 mm (3.5 in) form factors exist. In 1983, just a year after the introduction of the compact disc, Kees Schouhamer Immink and Joseph Braat presented the first experiments with erasable magneto-optical compact discs during the 73rd AES Convention in Eindhoven. The technology was introduced commercially in 1985.
Optical storageOptical storage refers to a class of data storage systems that use light to read or write data to an underlying optical media. Although a number of optical formats have been used over time, the most common examples are optical disks like the compact disc (CD) and DVD. Reading and writing methods have also varied over time, but most modern systems use lasers as the light source and use it both for reading and writing to the discs. Britannica notes that it "uses low-power laser beams to record and retrieve digital (binary) data.
Optical discAn optical disc is a flat, usually disc-shaped object that stores information in the form of physical variations on its surface that can be read with the aid of a beam of light. Optical discs can be reflective, where the light source and detector are on the same side of the disc, or transmissive, where light shines through the disc to the be detected on the other side. Optical discs can store analog information (e.g. Laserdisc), digital information (e.g. DVD), or store both on the same disc (e.g. CD Video).
Optical jukeboxAn optical jukebox is a robotic data storage device that can automatically load and unload optical discs, such as Compact Disc, DVD, Ultra Density Optical or Blu-ray and can provide terabytes (TB) or petabytes (PB) of tertiary storage. The devices are often called optical disk libraries, "optical storage archives", robotic drives, or autochangers. Jukebox devices may have up to 2,000 slots for disks, and usually have a picking device that traverses the slots and drives. Zerras Inc.
Strategic managementIn the field of management, strategic management involves the formulation and implementation of the major goals and initiatives taken by an organization's managers on behalf of stakeholders, based on consideration of resources and an assessment of the internal and external environments in which the organization operates. Strategic management provides overall direction to an enterprise and involves specifying the organization's objectives, developing policies and plans to achieve those objectives, and then allocating resources to implement the plans.
Marketing strategyMarketing strategy is an organization's promotional efforts to allocate its resources across a wide range of platforms, channels to increase its sales and achieve sustainable competitive advantage within its corresponding market. Strategic marketing emerged in the 1970s and 80s as a distinct field of study, branching out of strategic management. Marketing strategy highlights the role of marketing as a link between the organization and its customers, leveraging the combination of resources and capabilities within an organization to achieve a competitive advantage (Cacciolatti & Lee, 2016).
Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
Automated machine learningAutomated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment. AutoML was proposed as an artificial intelligence-based solution to the growing challenge of applying machine learning. The high degree of automation in AutoML aims to allow non-experts to make use of machine learning models and techniques without requiring them to become experts in machine learning.
Rule-based machine learningRule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that collectively represent the knowledge captured by the system. This is in contrast to other machine learners that commonly identify a singular model that can be universally applied to any instance in order to make a prediction.
ConnectionismConnectionism (coined by Edward Thorndike in the 1930s) is a name of an approach to the study of human mental processes and cognition that utilizes mathematical models known as connectionist networks or artificial neural networks. Connectionism has had many 'waves' along the time since its beginnings. The first wave appeared in the 1950s with Warren Sturgis McCulloch and Walter Pitts both focusing on comprehending neural circuitry through a formal and mathematical approach, and Frank Rosenblatt who published the 1958 book “The Perceptron: A Probabilistic Model For Information Storage and Organization in the Brain” in Psychological Review, while working at the Cornell Aeronautical Laboratory.
