Have you ever heard of self-driven cars? Have you used Alexa or Siri or any other similar intelligent personal assistant service? Most likely, the answer is yes.
All of us have either used, heard, seen or experienced the impact of devices that are developed by utilization of Artificial Intelligence technology. This applied science is flourishing beyond the hype and is infiltrating our day-to-day life.
Due to a plethora of applications and futuristic scope, enterprises are investing rapidly to acquire and exploit this field of applied science. Chief technical officers of organizations and their teams of AI developers are continuously looking for ways to develop and implement this advanced technology to drive maximum value from it. The developers are trying to build AI models that would befittingly replace direct human labor. This is expected to resolve the issues related to the inadequacies of human efforts like ineffectiveness, inaccuracy, etcetera.
IDC estimated that the AI market will grow from $8 billion in 2016 to more than $35.8 billion in 2019.
Via this expertise companies are emphasizing on manufacturing devices and machines that can perform tasks and react to the environment like humans. Some of the generic and most trending activities that you can expect from the ai technology tools include speech recognition, learning capabilities, planning actions and problem-solving.
Latest trends of Artificial Intelligence technologies in 2019:
Digital Twin/AI Modeling
Digital twins are also known as full-scale mock-ups. These are virtual models of things, objects, tools, buildings or devices that organizations can use to run simulations before actual products are constructed and deployed. Generally, data scientists and applied mathematicians with in-depth knowledge of the product in hand and machine learning are employed to create a digital twin using ai modeling.
Designing new components in the automotive and aviation industry is a tedious, slow and expensive process. However, with the help of AI engineers can create and generate millions of new and innovative designs and configurations in comparatively much lesser time and cost. Companies are using this machinery to save money, maintenance cost, reduce product defects and production time to reach the market. Multi-national companies like General Motors and Airbus are known for utilizing AI technology to design new components.
Previously fingerprints/ palm prints were the only way to identify each unique individual and were used for providing reliable security. Now facial recognition has become a massively adopted mechanism used for security purposes.
The science of face recognition is getting popular due to numerous applications in real-world scenarios. This artificial intelligence technology procures an image and immediately compares the distinct geometric physiognomies of a person’s facial features with the whole database by using a one-to-many search. The device uses data like nose structure, the distance between eyes and shape of the lips.
AI-Enabled Chips DevOps through AIOps
AI enabled applications are too fast to be handled by either regular or advanced CPUs. This year scientists and engineers are expecting new developments in the field of AI-enabled chips based on (FPGA) field programmable gate arrays. Qualcomm’s A12 chip is one of the examples of the latest impact of ai driven technology.
Chip manufacturing enterprises are going to work towards developing specialized chips for different capabilities of artificial intelligence technologies like natural language processing and speech recognition. Big technological brands like Amazon, Google, and Facebook, are expected to invest more resources in the field of customized AI-enabled chips. These chips are expected to handle high-performance computing, predictive analytics and speeding up query processing with next-generation databases.
Biometrics is an application of Artificial Intelligence, which is used for security purposes. This can be categorized into two sections: physical and behavioral. Distinctive and measurable characteristics of human body parts like the shape of a nose, size of ears, iris, fingerprints, and DNA are measured and analyzed in physical biometrics. This data is transformed into a code that is used by the AI system for further processing.
Behavioral characteristics like walking pace, typing rhythm, way of interacting with devices, etcetera is stored in databases and, then used during authentication. Face, voice and iris recognition are a few applications of physical biometrics. Behavioral biometrics is used chiefly for market research, prediction, and analysis.
Speech recognition is a technology that recognizes voices and allows devices to convert spoken words into text. This functionality has found its utility in many tools that are used by us in our daily lives like Amazon Echo and Alexa, Siri and Google Homes. These top tech companies are going to utilize this AI application more effectively in the future by improving their capabilities to handle accents and background noises.
Research firm Research and Markets reported that the speech recognition market will be worth $21.5 billion by 2024.
Soon speech recognition will find its way in our homes through refrigerators, cars and other daily use equipment.
Virtual Agents are computer generated, animated programs that are used as chatbots by enterprises. These talkative programs operate via using two branches of AI, natural language processing and natural language generation. These intelligent agents are used as online customer care representatives. These assistants are responsible for having a smart conversation with the clients. They respond to their questions, provides the solution. They are expected to have an adequate discussion with the customers just like humans.
They appear everywhere from social media feeds to customer service pages for several reasons, which can be providing conversation, advice or companionship. These chatbots are transforming the way we interact with organizations. They are being used in numerous business sectors like food delivery services, utility companies, banks, and government institutes.
Responsibilities of virtual assistants are not limited to customer care services. The agents can help you in minimizing regular mundane errands from your daily schedule. Simple tasks like managing your messages, ordering grocery, setting reminders and meeting deadlines can be accomplished with the help of these virtual agents.
Machine Learning Platforms
Until now, AI developers and other programmers believed in writing algorithms for machines to perform multiple tasks. Machine learning is a practice in which computers learn itself to perform by using data without being explicitly programmed.
It is an application of AI technology, which enables systems to learn and develop automatically by experience. All they require is access to data to improve itself. Soon, AI developers are going to work on automated machine learning algorithms. This will eliminate the need to overwrite the algorithms in a timely manner.
Currently, machine learning platforms are being used for classification and prediction analysis. Companies like Amazon, Google, and Netflix, are using it for various business purposes. Oil & Gas companies are using it for the prediction of maintenance of specialized equipment.
One of the ways you have experienced this technology is while using Netflix, a feature of precise recommendation or suggestions during online shopping. This is just a fraction of the power of Machine Learning. In the coming days, it is expected to help governments and healthcare industries in predicting and preventing epidemics as well.
Robotic Processes Automation
Robotic Processes Automation (RPA) and Artificial Intelligence Technology are considered a match made in heaven. RPA is the application of AI that enables employees in an organization to configure a “robot” or computer software to capture and interpret current applications for manipulating data, activating responses, handling a transaction and interacting with other digital systems.
Companies that use human labor on a large scale for regular data processing, transactional procedures, and other simple high-volume business processes can use RPA. RPA provides vast improvements in precision and cycle time. This will result in saving money and time.
Text Analytics & NLP (Natural Language Processing)
Organizations have terabytes of unstructured data that can be helpful if collected and interpreted aptly. Natural language processing (NLP) is an AI application that can support companies in handling unstructured data and explain it in a way that the information can be used successfully to improve business operations, efficiency and revenue.
To conclude, with the help of Artificial Intelligence, many of our daily personal and business activities can be carried out efficiently by programmed machines. As per the latest Artificial Intelligence trends, the levels of Artificial Intelligence technology differ from one geographical region to another. However, with multiple applications, utilities, and benefits, it is clear that the popularity of Artificial Intelligence technology is rising exponentially. The prospects for AI future use are enormous. This is already indicated in the current use of AI in the medical, banking, gaming, transport, manufacturing, and defense sectors.
We at TechAhead have been working on Artificial Intelligence projects for these upcoming technologies and helping our clients for better data processing and adding new updated features in their mobile apps which is helpful for their end users.