AI is the hottest trend when it comes to technology and innovation that transforms the daily lives of people across the world. On one hand, there is an emergence of AI innovation trends and on the other hand, it has created a plethora of job opportunities for humans. AI innovation trends are expected to drive massive breakthroughs in multiple industries such as healthcare, automotive, manufacturing finance and so on in these recent years. It has become an essential component to boost productivity and assist employees through machine learning algorithms, RPA, cybersecurity and many more. The rapid growth of advanced technologies with the implementation of AI can transform the foreseeable future of the tech-driven world.
Top 10 AI innovation trends for you to experience in 2021
Conversational AI
Conversational AI chatbots are essential for the better understanding of customer behaviour leading to enhance customer engagement for organisations. These AI models utilise machine learning algorithms and NLP to comprehend human commands efficiently.
Hybrid Workforce in the Healthcare Sector
The healthcare sector is one of the prominent sectors to adapt to cutting-edge AI innovations to boost the productivity of doctors and nurses. The hybrid workforce involves the interaction between humans and hi-tech machines for detecting diseases, tumours and other medical conditions at a very early stage. The applications help the doctors with highly accurate reports of patients and generate alert for emergencies. AI and machine learning algorithms leverage real-time data of patients and predict the outcomes efficiently to save lives daily. Surgical robots with VR and AR functionalities are guiding medical students to have virtual operations on virtual patients.
AI Chips
AI chips are invented to enhance server optimisation and better security management with high bandwidth memory. AI hardware is built for machine learning algorithms to work faster at an affordable price in hi-tech companies. Some popular AI chip startups are developing some hi-tech AI chips with around 40GB on-chip memory or can perform one quadrillion operations per second for faster computation.
AI for Quantum Computing
The integration of AI and machine learning algorithms into the existing computer systems has invented quantum computing. These advanced computer systems can solve complex problems within a short span of time by utilising quantum bits. Quantum computing also interprets multiple sets of real-time data to predict some meaningful business insights for the upcoming years. AI is transforming those traditional computers into smart reliable computers.
AI for Reinforcement Learning
Reinforcement learning uses deep learning and machine learning algorithms to enhance the customer experience in the nearby future. Several robots interact with its environment, observe some behavioural patterns and respond them accordingly to maximise the reward in the long term. It requires several sets of data with the implementation of machine learning algorithms and RPA.
NLP
Natural Language Processing (NLP) has been gaining popularity due to the virtual home assistants from popular tech companies in recent years. Humans can verbally communicate in their natural languages and accents with machines and robots with the help of NLP. It employs machine learning algorithms for machine translation, process description, chatbots and many more functionalities to enhance user experience.
AI for Cybersecurity
AI is transforming the world into a data-driven culture with cutting-edge technologies. But there is a prominent presence of malicious hackers who seek vulnerable machines to hack and achieve phishing attacks with ransomware. There is a huge risk compromising confidential data with minimal cybersecurity. AI technologies protect the machines against malicious scams and frauds with hi-tech cybersecurity. The AI-enabled framework automatically detects any unusual activity or irregularities in the machines to thwart data breaches.
Facial Recognition
The integration of AI and machine learning algorithms has invented facial recognition on smart devices. It covers the protection of smartphones as well as the biometric system for organisations. There is a huge demand for facial recognition application worldwide due to the digital transformation of business operations. It is also used for performing online transactions to ensure high-end security against malicious hackers. AI and machine learning algorithms compare the real-time data from images or videos with the existing information in the database to detect the appropriate movement or person.
Explainable AI
Explainable AI is one of the upcoming AI innovation trends in the global market that should be followed by all organisations. It allows all organisations to make stakeholders understand the framework of the machine learning algorithms that are used to generate solutions from complex data. It is crucial for organisations to have a clear concept of the functionalities of machine learning models and neural networks. Explainable AI is essential to promote end-users trust with proper explainability and accountability.
AI in RPA
Robotic Process Automation (RPA) enhances the workflow of organisations by automating repetitive tasks on the behalf of employees. The collaboration of RPA and AI has the potential to take automation and completing tasks to a whole new level. These two ground-breaking technologies can perform high-volume tedious processes without any human intervention and mistake. RPA has the potential to help employees complete other crucial high-valued work to increase the productivity of organisations.
Source: analyticsinsight.net
