Artificial intelligence is a term coined to demonstrate the intelligence of machine, particularly of computers. Artificial intelligence can be of two types – Weak AI and strong AI.
Weak AI is designed and trained for a particular task like personal assistance etc. Apple’s Siri is one of the examples of weak AI. Strong AI is a type of artificial intelligence which when is presented with unfamiliar tasks can find its solution by its intelligence.
All the recent studies are pointing to the future wide adoption and investment in artificial intelligence. It would be right to say that AI technology is flourishing in current time and the future of AI also looks bright.
Here is a list of the latest trends in artificial intelligence:
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Natural language processing - NLP is an area of artificial intelligence especially related to the way the computer interact with human language.
It is software that allows the machines to process the human language.
Today we have Siri, Google and Cortana to help us with simple questions of life but they are not able to understand the context of the word being used in the sentence.
NLP allows the computers to read and respond to the everyday human language.
Many companies have used NLP along with FaceBook and Skype.
Read the blog- 5 Crucial Artificial Intelligence (AI) Predictions For 2019 Everyone Must Know
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Natural language Generation (NLG) – NLG is also another discipline of AI which converts all the available data into human-readable text.
The software can generate the narratives and reports immediately in understandable language.
In simple language, you just put data on the computer only to get reports and summaries in human-readable text.
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Machine learning platforms – Machine learning is another sub-discipline of AI which allows computers to learn.
The significant goal of machine learning is to develop the intelligent machines that can teach and learn on their own without any sort of human interference and programming.
This is the area where most of the businesses are investing in to gain some business leverage.
Machine learning platforms involve algorithms, APIs (application programming interface), development and training tools, big data, applications and more.
Tech giants like Google, Amazon, and Microsoft have taken a step ahead and are using this technology for their benefit.
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Virtual agents – Virtual agents are the computer programs with which humans interact.
They can be either chatbots or other advanced systems.
Few of the well-known examples of virtual agents are Siri, Cortana, and Alexa.
These agents can make intelligent conversation and can answer to the simple questions.
They are widely used in home manager, customer service and support.
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Hardware merged with AI- Plethora of AI hardware solutions are going to be developed and are soon going to be available for us in the future.
The modern central processing units and processing devices are specially designed to handle AI oriented tasks.
AI-optimized silicon chips are the best example of the Hardware integrated with AI.
Some of the creators of this technology are IBM, Intel, Nvidia, Google, and Cray.
Read the Blog- How AI is Enhancing The Customer Experience And Customer Service
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Biometrics – This technology can identify and differentiate the physical aspects of different body structure and form.
Biometrics allows more natural interaction between human and computers.
Biometrics involves things like fingerprints, voice recognition, face structure and all other features that differ with individuals.
Some of the supporters of this technology are Affectiva, Agnitio, Sensory, Synqera, Tahzoo, and Facefirst.
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Deep learning platforms – Deep learning which is a subtype of machine learning simulates the way human brain functions, and it uses the artificial neural networks for data processing.
Deep learning platforms help in decision making and are used to recognize patterns and classifying apps that are compatible with large data.
A custom software development company has to work and research on it.
Some of them are Saffron technology, fluid AI, Peltarion, Deep Instinct, and Mathworks.
Understanding how deep learning platforms work is essential for its future use and development.
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Generative adversarial networks- It is also a type of deep learning system which is implemented as two competing neural networks.
One network creates fake data which looks like real data and second network ingest real and simulated data.
With passing the time both the networks improve, making the pair to learn the full distribution of the given set of data.
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Probabilistic programming – Probabilistic programming language is a high-level Artificial intelligence programming language through which a developer can define the probability models and solve them automatically.
Probabilistic programming can accommodate the incomplete information in the business domain.
It allows reusing the model libraries, support interactive modeling, and formal verification in order to provide the necessary abstraction layer to foster generic, efficient inference in universal model classes.
