Software Development Insights | Daffodil Software

7 AI Technologies that will be in Forefront in 2018

Written by Kunwar Jolly | Nov 22, 2017 12:19:09 PM

The ever growing interest of businesses and the market hype for Artificial Intelligence (AI) is making it one of the predominant element of tech-industry. AI, essentially is a broad term that defines the ability of machines to exhibit human intelligence. While real-AI is a near future, the current AI technologies are still offering a level playing field to almost every industry today, including healthcare, manufacturing, transportation, and many others.

With its amazing future perspectives, AI is projected to be the major driving force in reinventing business models and ecosystems, enhancing customer experience, refine decision making, and a lot more. According to a survey conducted by Gartner, 59% of organizations are still gathering information to build their AI strategies, while the remainder have already made progress in piloting or adopting AI solutions.

At present, we have narrow AI with us, at its best and we can make the most of it. For businesses to revolutionize their respective industry with AI, it is important to be informed about the potential AI technologies. Therefore, here, we enlist top 7 artificial intelligence technologies that can lead your way to industrial disruption in 2018.

1. Machine Learning

If there is one AI technology that almost every industry, at every level is putting into service, then it would certainly be Machine Learning (ML). We use machine learning everyday, but probably don’t realize it. From intelligent apps to software applications, ML has been replicating the power of cognitive learning through trained ML models.

ALSO READ: How Machine Learning will Enhance User Experience in Mobile Apps

2. Virtual Agents

Considering that customer experience is the key to every business’s success, virtual agents for interaction with humans are being put to use. One of the most common and widely utilized example of this technology is chatbots, virtual assistants (like Siri, Google Assistant), smart speakers (Google Home, Alexa). Virtual agents use machine learning algorithms in the background for training.

3. Speech Recognition

Speech recognition is the ability of machine or a program to transcribe and convert the spoken words or phrases into language that a machine understands. Presently, speech recognition have found its applications in voice response interactive systems (like Alexa), mobile apps (Google Translate), speech-to-text processing etc.

4. Intelligent Things

AI will make the existent things intelligent, by interacting with people and surroundings. For example: a camera turning into smart camera. Image content analysis, object identification, video recognization, has been made possible, without explicit programming, making things intelligent than ever. You can thank various Machine Learning frameworks that keeps on introducing APIs to simplify these tasks.

5. Deep Learning

Deep Learning is a subfield of Machine Learning, where the algorithms are designed mimicking structure and function of brain (called Artificial Neural Networks). At present, Deep Learning is essentially used for pattern recognization and classify applications that are compatible with huge data sets. This is the reasons, why Deep Learning has found its major use cases in healthcare industry projects.

6. Text Analytics and NLP

Text analytics is a technology that deals with understanding sentence structures, their meaning and intension. This is done through statistical methodologies and cognitive learning (ML). Text Analytics and Natural Language Processing (NLP) are currently have potential use cases in fraud detection and security systems. Therefore, this AI technology can find some great use cases in fintech, healthcare, manufacturing solutions.

7. Natural Language Generation

Natural Language Generation is a subfield of AI that deals with data conversion into text. This discipline of AI find its application in communicating idea with perfection. Currently, Natural Language Generation has its use cases in customer services for generating reports and market summaries.

ALSO READ: 7 Artificial Intelligence Trends that will Rule 2018

Which AI Technology do you think is the most Promising?

Over the next few years every app, application and service will incorporate AI at some level, predicts Gartner. From the discussion above, it is evident that all of these AI technologies are interdependent up on each other to offer precise and advanced results. Which AI technology according to you will disrupt the tech solutions in the coming year. Share with us in the comments below.