information-technology
senso-concept-Mcs (techInfo)

McsHitp-creation:: {2019-12-28},

overview of techInfo

description::
· info-tech is human-technology that manages brain-info.

name::
* McsEngl.McsTchInf000002.last.html//dirTchInf//dirMcs!⇒techInfo,
* McsEngl.dirMcs/dirTchInf/McsTchInf000002.last.html!⇒techInfo,
* McsEngl.IT'(info-tech)!⇒techInfo,
* McsEngl.techInfo,
* McsEngl.info-tech!⇒techInfo,
* McsEngl.information-technology!⇒techInfo,
* McsEngl.infotech!⇒techInfo,
* McsEngl.tchInf!⇒techInfo,
* McsEngl.techInfo'(McsTchInf000002)!⇒techInfo,
* McsEngl.techInfo'(information-technology)!⇒techInfo,
====== langoSinago:
* McsSngo.teko-info!=techInfo,
====== langoGreek:
* McsElln.πληροφορίας-τεχνολογία!=techInfo,

01_evaluation of techInfo

description::
·

name::
* McsEngl.techInfo'01_evaluation,
* McsEngl.techInfo'att001-evaluation,
* McsEngl.techInfo'evaluation,

02_human of techInfo

description::
· any human related with techInfo.

name::
* McsEngl.techInfo'02_human,
* McsEngl.techInfo'att002-human,
* McsEngl.techInfo'human,

specific-tree-of-techInfo'human::
* user,
* worker,
* programer,
* hacker,

03_organization (link) of techInfo

04_law of techInfo

description::
· law related to techInfo.

name::
* McsEngl.law.techInfo,
* McsEngl.techInfo'04_law,
* McsEngl.techInfo'att003-law,
* McsEngl.techInfo'law,

05_investment of techInfo

description::
·

name::
* McsEngl.techInfo'05_investment,
* McsEngl.techInfo'investment,

info-resource of techInfo

name::
* McsEngl.techInfo'Infrsc,

addressWpg::
* http://reports.weforum.org/global-information-technology-report-2016/
* http://www.gartner.com/it-glossary/
* http://www.techterms.com/

DOING of techInfo

description::
* processing,
* communicating,
* storing,

name::
* McsEngl.techInfo'doing,

evoluting of techInfo

name::
* McsEngl.techInfo'evoluting,

addressWpg::
* Hellenic IT Museum: https://elmp.gr/,

{2019-12-28}::
=== McsHitp-creation:
· creation of current concept.

WHOLE-PART-TREE of techInfo

name::
* McsEngl.techInfo'whole-part-tree,

whole-chain::
* human-technology
* Solar-system,
* Milky-way-galaxy,
* Sympan,

part::
*

GENERIC-SPECIFIC-TREE of techInfo

name::
* McsEngl.techInfo'generic-specific-tree,

generic-tree::
* technology
...
* entity,

techInfo.SPECIFIC

name::
* McsEngl.techInfo.specific,

specific::
* hardware,
* software,
* system,
===
* char-techInfo,
* audio-techInfo,
* image-techInfo,
* video-techInfo,
===
* processing-techInfo,
* communicating-techInfo,
* storing-techInfo,
===
* hardware-techInfo,
* software-techInfo,
* hardsoft-techInfo,
===
* data-techInfo,
* dataNo-techInfo,
** artificial-intelligence-techInfo,
** machine-learning-techInfo,
** machine-translating-techInfo,
** natural-language-processing-techInfo,

techInfo.data-001

description::
· techData is techInfo that manages infoData.

name::
* McsEngl.techData,
* McsEngl.techInfo.001-data!⇒techData,
* McsEngl.techInfo.data!⇒techData,

techInfo.dataNo-002 (link)

lagConcept (link) of Cnptltech

techInfo.software-003

description::
· software is techInfo which is not hardware, ie representations of infoBrain that is-managed by the-techInfo.

name::
* McsEngl.software-of-techInfo!⇒techInfoSoft,
* McsEngl.techInfo.003-software!⇒techInfoSoft,
* McsEngl.techInfo.software!⇒techInfoSoft,
* McsEngl.techInfoSoft,

techInfo.hardware-004

description::
· the physical parts of techInfo, devices, cables, anything touchable.

name::
* McsEngl.hardware-techInfo!⇒techInfoHard,
* McsEngl.techInfo.004-hardware!⇒techInfoHard,
* McsEngl.techInfo.hardware!⇒techInfoHard,
* McsEngl.techInfoHard,

techInfo.system-005

description::
· machines or system of machines with hardware and software with specific doings.

name::
* McsEngl.ITS!⇒techInfoSys,
* McsEngl.information-technology-system!⇒techInfoSys,
* McsEngl.techInfo.005-system!⇒techInfoSys,
* McsEngl.techInfo.machine!⇒techInfoSys,
* McsEngl.techInfo.system!⇒techInfoSys,
* McsEngl.techInfoSys,

specific-tree-of-techInfoSys::
* computer,
* computer-network,

techInfo.natural-language-processing-006

description::
"Natural Language Processing (NLP) comprises a set of techniques to work with documents written in a natural language to achieve many different objectives. They range from simple ones that any developer can implement, to extremely complex ones that require a lot of expertise."
[{2020-09-20} https://tomassetti.me/guide-natural-language-processing/]

name::
* McsEngl.natural-language-processing-tech!⇒techNlpg,
* McsEngl.techInfo.006-natural-language-processing!⇒techNlpg,
* McsEngl.techInfo.natural-language-processing!⇒techNlpg,
* McsEngl.techNlpg,

specific-tree-of-techNlpg::
* Grouping similar words,
* Finding words with the same meaning,
* Generating realistic names,
* Understanding how much time it takes to read a text,
* Understanding how difficult to read is a text,
* Identifying the language of a text,
* Generating a summary of a text,
* Finding similar documents,
* Identifying entities,
* Understanding the attitude expressed in a text,
* Translating a text,

techNlpg.language-recognition

description::
·

name::
* McsEngl.identifying-language-of-text,
* McsEngl.techNlpg.001-language-recognition,

addressWpg::
* https://en.wikipedia.org/wiki/Wikipedia:Language_recognition_chart,

techNlpg.machine-translation

description::
"Machine translation, sometimes referred to by the abbreviation MT[1] (not to be confused with computer-aided translation, machine-aided human translation or interactive translation), is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another."
[{2021-02-06} https://en.wikipedia.org/wiki/Machine_translation]

name::
* McsEngl.machine-translation-tech!⇒techMntn,
* McsEngl.techMntn,
* McsEngl.techMntn'(machine-translation)!⇒techMntn,
* McsEngl.techNlpg.002-machine-translation!⇒techMntn,
* McsEngl.techNlpg.machine-translation!⇒techMntn,

techInfo.artificial-intelligence-007

description::
· techAi is techInfo with intelligence (= doing of organism's managing-sys).

name::
* McsEngl.AI'(artificial-intelligence)!⇒techAi,
* McsEngl.artificial-intelligence!⇒techAi,
* McsEngl.techAi,
* McsEngl.techInfo.007-artificial-intelligence!⇒techAi,
* McsEngl.techInfo.artificial-intelligence!⇒techAi,

info-resource of techAi

description::
* https://www.stateof.ai/,
* https://welcome.ai/about,
* https://knowledge4policy.ec.europa.eu/ai-watch_en,
* https://joinup.ec.europa.eu/collection/elise-european-location-interoperability-solutions-e-government/artificial-intelligence-public-sector,
* {2021-01-15} https://www.weforum.org/agenda/2021/01/ai-agriculture-water-irrigation-farming,
* {2020} Blagoj DELIPETREV, Chrisa TSINARAKIi, Uroš KOSTIĆ. “Historical Evolution of Artificial Intelligence”, EUR 30221EN, Publications Office of the European Union, Luxembourg, 2020, ISBN 978-92-76-18940-4, doi:10.2760/801580, JRC120469: https://publications.jrc.ec.europa.eu/repository/handle/JRC120469,
* {1995-12-26} http://sandcastle.cosc.brocku.ca/~bross/3P71/misc/outsider_ai.txt,

name::
* McsEngl.techAi'Infrsc,

evoluting of techAi

{1950}-techAi-::
""
[{2020} Historical-Evolution-of-AI, p7, ifrcElnc000001]
* McsEngl.{1950}-techAi-,

{1969}-techAi-Shakey-the-Robot::
"1969 Shakey the Robot was the first general-purpose mobile robot capable of reasoning its actions. This project integrated research in robotics with computer vision and natural language processing, thus being the first project that combined logical reasoning and physical action (Bertram 1972)."
[{2020} Historical-Evolution-of-AI, p7, ifrcElnc000001]
* McsEngl.{1969}-techAi-Shakey-the-Robot,

{1956}-techAi-Dartmouth-conference::
"The first “AI period” began with the Dartmouth conference in 1956, where AI got its name and mission.
McCarthy coined the term "artificial intelligence," which became the name of the scientific field.
The primary conference assertion was, "Every aspect of any other feature of learning or intelligence should be accurately described so that the machine can simulate it” (Russell and Norvig 2016).
Among the conference attendees were Ray Solomonoff, Oliver Selfridge, Trenchard More, Arthur Samuel, Herbert A. Simon, and Allen Newell, all of whom became key figures in the Ai field"
[{2020} Historical-Evolution-of-AI, p7, ifrcElnc000001]
* McsEngl.{1956}-techAi-Dartmouth-conference,

{1955}-techAi-Logic-Theorist::
"1955 The Logic Theorist had proven 38 theorems from Principia Mathematica and introduced critical concepts in artificial intelligence, like heuristics, list processing, ‘reasoning as search,' etc. (Newell et al. 1962)."
[{2020} Historical-Evolution-of-AI, p7, ifrcElnc000001]
* McsEngl.{1955}-techAi-Logic-Theorist,

{1950}-techAi-Turing-test::
"In 1950, Alan Turing published the milestone paper "Computing machinery and intelligence" (Turing 1950), considering the fundamental question "Can machines think?”
Turing proposed an imitation game, known as the Turing test afterwards, where if a machine could carry on a conversation indistinguishable from a conversation with a human being, then it is reasonable to say that the machine is intelligent.
The Turing test was the first experiment proposed to measure machine intelligence"
[{2020} Historical-Evolution-of-AI, p7, ifrcElnc000001]
* McsEngl.{1950}-techAi-Turing-test,

name::
* McsEngl.techAi'evoluting,

GENERIC of techAi

description::
* tool,
===
"Human beings across time have shared one important characteristic: they use tools to improve what they can achieve.
AI can be one such tool, and it can work well, provided we remember it is a tool. As a tool it must be put in the hands of a human, who can use appropriately and intentionally, for achieving the goals they have."
[{2020-10-08} https://clearbox.ai/blog/2020-06-16-making-ai-less-magic-and-more-human/]

name::
* McsEngl.techAi'generic,

techAi.SPECIFIC

description::
* machine-learning,
* neural-network,
* semantic-AI,
* statistical-AI,

name::
* McsEngl.techAi.specific,

techAi.narrow

description::
"Artificial Narrow Intelligence (ANI), often referred to as “Weak” AI is the type of AI that mostly exists today. ANI systems can perform one or a few specific tasks and operate within a predefined environment, e.g., those exploited by personal assistants Siri, Alexa, language translations, recommendation systems, image recognition systems, face identification, etc.
ANI can process data at lightning speed and boost the overall productivity and efficiency in many practical applications, e.g., translate between 100+ languages simultaneously, identify faces and objects in billions of images with high accuracy, assist users in many data-driven decisions in a quicker way. ANI can perform routine, repetitive, and mundane tasks that humans would prefer to avoid."
[{2020} Historical-Evolution-of-AI, ifrcElnc000001]

name::
* McsEngl.ANI'(Artificial-Narrow-Inteligence),
* McsEngl.Artificial-Narrow-Inteligence,
* McsEngl.techAi.narrow,
* McsEngl.weak-AI,

techAi.general

description::
"Artificial General Intelligence (AGI) or “Strong” AI refers to machines that exhibit human intelligence. In other words, AGI aims to perform any intellectual task that a human being can. AGI is often illustrated in science fiction movies with situations where humans interact with machines that are conscious, sentient, and driven by emotion and self-awareness. At this moment, there is nothing like an AGI."
[{2020} Historical-Evolution-of-AI, ifrcElnc000001]

name::
* McsEngl.AGI'(Artificial-General-Intelligence),
* McsEngl.Artificial-General-Intelligence,
* McsEngl.techAi.general,

techAi.supper

description::
"Artificial Superintelligence (ASI) is defined as “any intellect that greatly exceeds the cognitive performance of humans in virtually all domains of interest” (Bostrom 2016). ASI is supposed to surpass human intelligence in all aspects — such as creativity, general wisdom, and problem-solving. ASI is supposed to be capable of exhibiting intelligence that we have not seen in the brightest thinkers amongst us. Many thinkers are worried about ASI. At this moment, ASI belongs to science fiction.
If we ever succeed in creating an AI that is capable of generalizing, understanding causality, making a model of the world, it is highly likely that it will be closer to ASI than AGI. AI excels in numerical calculations, and there is no logical explanation as to why AI would downgrade its abilities to simulate humans. AI’s quest ultimately leads to ASI."
[{2020} Historical-Evolution-of-AI, ifrcElnc000001]

name::
* McsEngl.ASI'(Artificial-Superintelligence),
* McsEngl.Artificial-Superintelligence,
* McsEngl.techAi.supper,

techAi.semantic

description::
"Semantic AI is used everywhere where the complexity of the underlying data is high and the details must not be ignored.
This distinguishes semantic AI from AI based on statistical methods (e.g. neural networks): statistical AI generalizes but details and traceability are lost. This is not bad for the classification of images - but not acceptable for the representation of processes or contracts."
[{2021-02-04} https://www.semafora-systems.com/]

name::
* McsEngl.semantic-AI,
* McsEngl.techAi.semantic,

techInfo.machine-learning-008

description::
"A system is said to learn if it is capable of acquiring new knowledge from its environment.
Learning may also enable the ability to perform new tasks without having to be redesigned or reprogrammed, especially when accompanied by generalization.
Learning is most readily accomplished in a system that supports symbolic abstraction, though such a property is not exclusive (reinforcement strategies, for example, do not necessarily require symbolic representation).
This type of learning is separated from the acquisition of knowledge through direct programming by the designer, which is referred to throughout this document as the Ability to Add New Knowledge." [{1998-02-16} http://krusty.eecs.umich.edu/cogarch4/toc_defs/defs_capa/defs_lear.html]

name::
* McsEngl.ML'(Machine-Learning)!⇒techMachine-learning,
* McsEngl.Machine-Learning!⇒techMachine-learning,
* McsEngl.techMachine-learning,

descriptionLong::
"Machine learning (ML) is the study of computer algorithms that improve automatically through experience.[1][2] It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so.[3] Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop conventional algorithms to perform the needed tasks.
Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a related field of study, focusing on exploratory data analysis through unsupervised learning.[5][6] In its application across business problems, machine learning is also referred to as predictive analytics."
[{2020-09-22} https://en.wikipedia.org/wiki/Machine_learning]

info-resource of techMachine-learning

description::
* https://machinelearningmastery.com/,

name::
* McsEngl.techMachine-learning'Infrsc,

meta-info

this webpage was-visited times since {2019-12-28}

page-wholepath: synagonism.net / worldviewSngo / dirTchInf / techInfo

SEARCH::
· this page uses 'locator-names', names that when you find them, you find the-LOCATION of the-concept they denote.
GLOBAL-SEARCH:
· clicking on the-green-BAR of a-page you have access to the-global--locator-names of my-site.
· use the-prefix 'techInfo' for sensorial-concepts related to current concept 'information-technology'.
LOCAL-SEARCH:
· TYPE CTRL+F "McsLang.words-of-concept's-name", to go to the-LOCATION of the-concept.
· a-preview of the-description of a-global-name makes reading fast.

footer::
• author: Kaseluris.Nikos.1959
• email:
 
• edit on github: https://github.com/synagonism/McsWorld/blob/master/dirTchInf/McsTchInf000002.last.html,
• comments on Disqus,
• twitter: @synagonism,

webpage-versions::
• version.last.dynamic: McsTchInf000002.last.html,
• version.1-0-0.2021-04-08: (0-17) ../../dirMiwMcs/dirTchInf/filMcsTchInf.1-0-0.2021-04-08.html,
• version.0-1-0.2019-12-28 draft creation,

support (link)