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Artificial Intelligence Technologies That Will Dominate
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Artificial Intelligence Technologies That Will Dominate

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New technology is each time with innovative and has different factors that are most life-changing. Why we are so conscious about that is because we love it. So what is coming now? Here we are sharing Artificial intelligence Technologies That Will Dominate that you want to know that, which will change your lifestyle. Artificial Intelligence meaning / Artificial Intelligence definition is to perform tasks/works as a human does. Here know the Artificial Intelligence article.  Artificial Intelligence examples are given below.

Artificial Intelligence Technologies 

New Artificial intelligence Technologies That Will Dominate in few years

1. Natural Language Generation

Natural language generation is an Artificial Intelligence that converts data into text. It enables computers to communicate ideas with perfect accuracy.

It is used to generate reports and market summaries for customer service. Some companies offered natural language generation which are Automated Insights, Cambridge Semantics, Digital Reasoning, Narrative Science, and SAS.

2. Speech recognition

Nowadays new technologies are developing and more and more systems are being created that can transcribe human language through voice-response interactive systems and mobile apps.

Many Companies and organizations are offering speech recognition services which include NICE, Nuance Communications, OpenText, and Verint Systems.

see also: Artificial Intelligence examples here on this page.

Artificial Intelligence is / AI Technology 

3. Virtual Agents

A virtual agent is like a computer agent or program capable of interacting with humans. The most common example of a virtual agent is chatbots.

Virtual agents are mostly used for customer service and support as smart home managers.

Some companies and organizations which provide virtual agents are Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, IPsoft, and Microsoft.

4. Machine Learning Platforms

Nowadays computers can easily learn and they can be incredibly intelligent. Machine learning is a branch of AI and it is a subdiscipline of computer science.

Aims of machine learning platforms are to develop techniques that allow computers to learn.

ML platforms are gaining more and more traction every day by giving algorithms, application programming interfaces,s and training tools.

ML is mostly used for prediction and classification. Some companies are selling machine learning platforms which are Amazon, Fractal Analytics, Google, SAS, and Microsoft.

5. AI-Optimized Hardware

Artificial Intelligence makes hardware friendlier and more popular through new graphics, central processing units, and processing devices that are specifically designed and structured.

You already saw AI-optimized silicon chips that can be inserted into your portable devices. You can get access to AI-Optimized Hardware through Alluviate, Cray, Google, IBM, Intel, and Nvidia.

6. Decision Management

Intelligent machines have the ability to introduce rules and logic to AI systems, so you can easily use them for initial setup, training, and ongoing maintenance.

It has a variety of corporate applications to assist and execute automated decisions and make the business as much as possible profitable.

7. Deep Learning Platforms

It uses a unique form of Machine Learning that has artificial neural circuits with various abstraction layers that can mimic the human brain.

Deep learning platforms process data and create patterns for decision-making. It is mostly used to recognize patterns and classify applications that are only compatible with large-scale data sets.

Some examples of Deep learning platform is Instinct, Ersatz Labs, Fluid AI, MathWorks, Peltarion, Saffron Technology, and Sentient Technologies.

Advantages of Artificial Intelligence Technologies

8. Biometrics

Biometrics is a technology that can easily identify, measure, and analyze human behavior and physical aspects of the body structure.

Due to biometrics natural interactions between humans and machines increase including interactions related to touch, image, speech, and body language recognition.

Biometric companies are Agnitio, FaceFirst, Affectiva, 3VR, Sensory, Synqera, and Tahzoo.

9. Robotic Processes Automation

Robotic process automation is useful when hiring humans for a specific job or task is too expensive or inefficient. It uses scripts that automate human tasks to support corporate processes.

One important example of Robotic Processes Automation is Adext AI which is a platform that automates digital advertising processes using AI.

It saves businesses from devoting hours to mechanical and repetitive tasks.

It is a solution that makes the most of human talent and moves employees into more strategic and creative positions. So their actions can really make an impact on companies’ growth.

Some example of robotic process automation companies is Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, and WorkFusion.

10. Text Analytics and Natural Language Processing

Text Analytics is a technology that uses text analytics to understand the structure of sentences and their meaning and intention through statistical methods and Machine Learning.

Text analytics are mostly used for security systems and fraud detection. They are also used by automated assistants and apps to extract unstructured data.

Some service providers and suppliers of Text Analytics are Expert Systems, Basis, Indico, Lexalytics, Technology, Coveo, Knime, Linguamatics, Mindbreeze, Sinequa, Stratifyd, and Synapsify.

11. Digital Twin

It is software that constructs the gap between physical systems and the digital world. It is not the only line of software code but also the most elaborate version which look like 3-D computer-aided designs.

One example of a digital twin is General Electric that building an AI workforce to monitor its aircraft engines, locomotives, and gas turbines and predict failures.

Companies that use digital twins are VEERUM, in the capital project delivery space, and Akselos which uses it to protect critical infrastructure and Supply Dynamic.

Artificial Intelligence Examples | Artificial Intelligence Future

12. Cyber Defense

It is a computer network defense mechanism that concentrates on providing timely responses to attacks or threats to infrastructure and information.

Artificial Intelligence and Machine Learning are mostly used to move cyber defense into a new evolutionary phase in response to an increasingly hostile environment.

Recurrent neural networks are capable of processing sequences of inputs that can be used in combination with ML techniques to create supervised learning technologies.

One best example of cyber defense is Dark trace company which pairs behavioral analytics with advanced mathematics to automatically detect abnormal behavior within organizations.

Another example of cyber defence is Cylance which applies AI algorithms to stop malware and mitigate damage from zero-day attacks. They both are working in the area of AI-powered cyber defense.

Another cyber defense company is Most Disruptive Startup which protects enterprise endpoints, servers, and mobile devices.

13. Compliance

It is the certification that a person or organization meets the requirements of accepted practices, legislation, rules, and regulations.

Nowadays the first wave of regulatory compliance solutions is mostly used, which use AI to deliver efficiency through automation.

Some examples of AI use in compliance are Natural Language Processing solutions that can scan regulatory text and match its patterns.

These are the 13 Artificial intelligence Technologies that will dominate and due to these technologies, we know why technology is good. You may also search on google risks of artificial intelligence and the advantages of artificial intelligence.

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