Artificial Intelligence (AI) Technologies

Artificial Intelligence (AI) Technologies

artificial intelligence technology

artificial intelligence technology The Artificial Intelligence market (AI) technology thrives. Apart from Hype and heightened media attention, numerous startups and internet giants Racing acquire them; there is a significant increase in investment and acceptance by businesses. Research of narrative Science found last year that 38% of enterprises already use AI, growing to 62% for 2018. Forrester study anticipated more than 300% increase in artificial intelligence investment in 2017 compared to 2016. It is estimated that the AI market will grow from $8 to 000 000 000 2016 to over $47 000 000 000 in 2020.

artificial intelligence technology

Invented in 1955 to describe the new computer science sub-discipline, the “artificial intelligence ” Today includes various technologies and tools, some time-tested, others relatively new. To help figure out what is hot and what is not, Forrester has just published a TechRadar report on artificial intelligence (for specialists in application development), a detailed analysis of 13 enterprise technologies should consider acceptance support Human decision making.

Based on Forrester’s analysis, here is my list of 10 hottest AI technologies:

Speech Recognition

Transcribe and change the public address in the same computer format for all applications. Currently used in voice interactive real response and mobile applications. Sample vendors: Excel, Nuance Communications, OpenText, Verint true.artificial intelligence technology

Natural Language Generation

Production of text from computer data. Customer service, report creation and summarize business intelligence insights are currently used. Sample vendors: Attivio, automated reviews, Cambridge Semantics, digital reasoning, Lucidworks, Narrative Science, SAS, Yseop. artificial intelligence technology

Machine Learning Platforms

Provides API algorithms, development and Training data toolkit, as well as processing power in the train design and deployment forms as application processes and other machines. Currently, it is used in a wide variety of applications of most organizations related to forecasting or classification. Vendor Example: Amazon, fractal Analysis, Google,, Microsoft, SAS, Skytree. artificial intelligence technology

Decision Management

Engines are inserted rules and considerations to the AI system and are used in pre-planning/training and tuning and production. A mature technology, used in a variety of enterprise applications, helps with or performs automated control. Sample vendors: Advanced Considerations for System, Informatica, Maana, Pegasystems, UiPath.

AI-optimized Hardware

The Graphics Processing unit (GPU) and the machinery are specially designed and architected to run AI-oriented computational work with efficiency. Currently, a distinction is made between primarily deep learning applications. Sample vendors: Paket, Krambay, Google, IBM, Intel, Nvidia.

Deep Learning Platforms

Different types of devices are learning whether artificial neural networks have multiple abstraction layers. Currently, the release is initially used by the classification of applications that are large. Sample vendors: Deep Instinct, Ersatz Labs, Fluid OFFSET, MathWorks, Peltarion, Saffron Technologies, Sentient Technologies.

Robotic Process Automation

Automate human operations using scripts and other methods to support efficient business processes. It is currently used for people who are too expensive or inefficient to perform tasks or processes. Example vendors: Advanced system concepts, automation everywhere, blue prism, UiPath, work fusion.

Text Analytics and NLP

Natural language processing (NLP) supports text analysis by facilitating the understanding of the structure of the sentence and meaning, sentiment and intention through statistical and machine learning methods. Now in detecting fraud and security, a wide range of automated assistants and applications for non-structured mineral data are used. Typical sellers: basic technology, COVEO, connoisseur System, Indico, Knime, Lex Fibres, Linguamatics, Mindbreeze, Sinequa, stratigraphy, Synapsify.


Provide more physical interactions between people and machines, including but not limited to image and touch recognition, speech and body language. Currently used mainly in market research. Sample sellers: 3VR, Affectiva, Agnitio, FaceFirst, Sensory, Synqera, Tahzoo.

Artificial Intelligence (AI) Technologies


Once companies win these obstacles, Forrester concludes, they stand up with a rapid change of driving in the application of anti-customers and developing an linked web mind of business.

  1. Digital Twin/AI Modeling:

    Digital Twin is a software structure that bridges the gap between physical systems and the digital world.

    For example, General Electric (GE) builds an AI workforce that monitors its aircraft engines, locomotives and gas turbines, and predicts failures with GE’S machines ‘ cloud-based software models. Their digital twins are basically, lines of software code, but the most advanced versions look like 3-D computer-aided design drawings filled with interactive diagrams, graphs, and Data points.

    Enterprises using digital twins and ARTIFICIAL INTELLIGENCE modeling technologies include the ROLLING stock in the supply of the capital project; Akselos, which uses it to protect critical infrastructure and Supply dynamics, which have developed a SaaS solution to manage to sour of raw materials in complex, highly dispersed production environments.

  2. Cyber Defense:

    Cyber defence is a computer network protection mechanism focusing on infrastructure and information-oriented attacks on prevention, detection and response.

    ARTIFICIAL INTELLIGENCE and ML are now being used to take cyber defence in a new evolutionary phase in response to an increasingly hostile environment: the violation level index was discovered by more than 2 000 000 000 injured items in 2017. 76 percent of the study records were accidentally lost, and 69 percent had some form of identity theft. Recurrent neural networks capable of handling feeding kits can be used in conjunction with ML Technologies to create supervised learning techniques that reveal suspicious user activity and detect up to 85% of all Cyberattacks.

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