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t. e. In science, computing, and engineering, a black box is a system which can be viewed in terms of its inputs and outputs (or transfer characteristics), without any knowledge of its internal workings. [1][2] Its implementation is "opaque" (black). The term can be used to refer to many inner workings, such as those of a transistor, an engine ...
t. e. Black-box testing, sometimes referred to as specification-based testing, [1] is a method of software testing that examines the functionality of an application without peering into its internal structures or workings. This method of test can be applied virtually to every level of software testing: unit, integration, system and acceptance.
Discovery system (AI research) A discovery system is an artificial intelligence system that attempts to discover new scientific concepts or laws. The aim of discovery systems is to automate scientific data analysis and the scientific discovery process. Ideally, an artificial intelligence system should be able to search systematically through ...
Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), either refers to an artificial intelligence (AI) system over which it is possible for humans to retain intellectual oversight, or refers to the methods to achieve this. [1][2] The main focus is usually on the reasoning behind the decisions or ...
Black Box Corporation. Black Box Corporation is an IT company headquartered in Texas, United States. [1] The company provides technology assistance and consulting services to businesses in a variety of sectors including retail, transportation, government, education, and public safety. Black Box operates in 75 locations across 35 countries.
Fuzzing. In programming and software development, fuzzing or fuzz testing is an automated software testing technique that involves providing invalid, unexpected, or random data as inputs to a computer program. The program is then monitored for exceptions such as crashes, failing built-in code assertions, or potential memory leaks.
Examples include attacks in spam filtering, where spam messages are obfuscated through the misspelling of "bad" words or the insertion of "good" words; [19] [20] attacks in computer security, such as obfuscating malware code within network packets or modifying the characteristics of a network flow to mislead intrusion detection; [21] [22] attacks in biometric recognition where fake biometric ...
The AI code of practice will not be legally binding when it takes effect late next year, but it will provide firms with a checklist they can use to demonstrate their compliance.
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