– Dr Minh Dinh
What are the most anticipated artificial intelligence (AI) trends and their implications on the Vietnam job market? RMIT Vietnam’s senior lecturer in AI and software engineering Dr Dinh Ngoc Minh shared his insights.
Powerful languages models
The rapid growth in portable device usage such as smartphones, tablets, and laptops has provided businesses with new interfaces to connect to their customers via websites and social media platforms.
According to Dr Esteban Ortiz-Ospina of Our World in Data, there are 2.4 billion Facebook users, while other social media platforms including YouTube and WhatsApp also have more than one billion users each. These services create a surge in consumer-generated data and highlight the needs for natural language processing capacities.
Natural language processing (NLP) is a branch of computer science that focuses on creating, analysing, and interpreting human language to accomplish tasks such as sentiment classification, machine translation, handwritten character recognition, speech recognition, just to name a few. We have seen significant breakthroughs in NLP in the last few years with the most powerful language models such as GPT-3, which can produce creative fiction, develop computer code, and summarising a large corpus of research literature. Yet, the full potential of NLP is still being explored.
In the coming years, we will continue to see further advancement in the field of NLP, especially in coping with data in multi-lingual context. The impacts will be riveting in domains such as finance, services, and entertainment, in which the targeted audience is no longer limited to specific regions or languages. NLP will continue to develop to satisfy the need for mining consumers’ opinions, understanding customers’ demand, and personalising work and play options.
 100vw, 800px” data-recalc-dims=”1″></p> <p id=)
Dr. Dinh Ngoc MinhAdvanced computer vision technology
AI is quickly maturing in the field of imaging and computer vision with the recent advent of deep learning techniques, unsupervised learning, and active learning.
Since the days when we could classify objects such as letters, animals, and household items, computer vision has come a long way and delivers significant impacts in our everyday lives. For example, AI solutions can handle some of the greatest challenges in the healthcare segment, especially in medical imaging. Typically, the analysis of medical images requires much time and effort from experienced radiographers and doctors. Today doctors don’t have to scan through thousands of CXR and CT majors while they rather could use an automated AI system to help them identify the most important ones so that they could expedite their decision-making.
We will continue to see breakthrough in AI-based computer vision solutions and the impacts will be beyond the medical imaging domain. Computer vision will showcase successes in autonomous driving, smart manufacturing, and smart home and cities, through a new discipline called ‘computer vision on the edge’. Real-time photos and images will be processed, classified, and characterised much closer to where they are generated to support the real-time decision-making process.
Reinforcement Learning
This is another key domain of AI and machine learning where AI scientists focus on decision-making using reward-based training, instead of loss function optimisation.
In a nutshell, reinforcement learning models a realistic environment in which agents explore and adjust their behaviours to maximise rewards (and/or minimise punishments). This learning model works because it mimics how we learn in real life, where we don’t always make the correct decision or perform a completely safe action. While we don’t necessarily perform random acts and rely completely on trial-and-error process, it’s important we factor the randomness of the real world in training our intelligence artificial agents. As a result, reinforcement learning techniques play a key role in developing autonomous robots including autonomous vehicle, constructing trading strategies, and in validating complex decision-making process.
Comparing to supervised learning, in which deep learning has delivered significant breakthroughs, reinforcement learning has yet to shine. However, because we expect artificial agents to make complex decisions while holding long-term goals, reinforcement learning will continue to be one of AI’s most exciting trends.
Generative AI
The emerging trend of generative AI involves machine learning methods, including NLP, that aims to generate realistic, and potentially original, artefacts by learning features and content from domain-specific data.
Generative AI algorithms, for instance, can compose music pieces, generate fictional literature, or create paintings when given specific topics, and therefore has a significant impact on education, creativity, and media.
Gartner considers Generative AI as a strategic AI technology trend for 2022 and will boom in the coming years. Amongst potential technologies, generative language models, which target the generation of natural-sounding content, have impactful applications in marketing, customer services, and personalised education. Generative adversarial networks (GANs) can be used for fraud detection, synthetic data generation and risk factor modelling, especially in banking and investment services. Last but not least, generative AI solutions can solve generic problems while adapting to different situations and context, thus, promises a roadmap to artificial general intelligence (AGI).
A surge in demand for AI experts in Vietnam
The Vietnamese Government has issued a national strategy on research, development, and application of AI until 2030, aiming to turn Vietnam into an innovation and AI hub in ASEAN. To realise that goal, the Ministry of Science and Technology (MoST) has recently launched the Vietnam-Australia Artificial Intelligence Cooperation Network (Vietnam-Australia AI Network). According to Vietnam-Australia AI Network, about one million more ICT personnel will be needed in the country by 2030, and the demand for AI talents is expected to increase continuously.
The Vietnam job market has shown a significant demand for top AI talents to respond to the national strategy above. A Vietnam IT Market Report by TopDev indicates that AI and Machine Learning engineers can receive the highest average monthly salary among IT engineers, reaching US$3,054, as of the 2nd quarter 2021.
With the current trend in the Vietnam job market, the highest paying positions in IT require special skills such as data analysis, DevOps, Machine Learning or AI. This trend in the job market indicates the importance for IT professionals to upskill towards AI and Data Science majors to remain competitive.
RMIT University in Vietnam recently launched the Master of Artificial Intelligence program for those who wish to further their career in AI through exploring practical components of developing AI applications and platforms and understand the role that ethics and social responsibility play in the future of technology.
RMIT is ranked among the world’s best in AI and Image Processing research by Excellence in Research for Australia (ERA) – Australia’s national research evaluation framework and rated ‘above world standard’ by the Australian Research Council. Students in Vietnam will join one of the most specialised AI programs found in Australia and will learn from international experts.
About the author
With a Ph.D. in Computer Science from Monash University, Australia, Dr Dinh Ngoc Minh’s research expertise is in computational science, high-performance computing, and AI. His expertise is developed through his previous positions at Monash University, the University of Queensland, and the Queensland Cyber Infrastructure Foundation.
Dr Dinh’s recent research projects developed a Deep Neural Network debugger, an optical character recognition (OCR) pipeline for recognising and transcribing Vietnamese doctor handwriting, and a scalable machine-learning pipeline for enhancing computational modelling techniques.
Related
Source: Vietnam Insider