3 challenges of AI that Vietnam IT Companies have to face
AI is a technology that can revolutionize manufacturing industries, healthcare, space exploration, and more. As a result, artificial intelligence is growing and gaining popularity at an excellent rate. This growing popularity of AI has urged several businesses to invest in developing and researching different AI applications like robots and automated cars.
However, it is important to note that AI is still facing some challenges. Here are some of the common challenges that most Vietnam IT companies face when implementing Artificial Intelligence.
As most of you are probably aware, AI systems are driven and developed by leveraging quality data. Therefore, the difficulty of accurate data collecting and quality control and the expense of labeling data are the most challenging aspects for every AI business wherever in the globe. Vinfast, for example, is a major artificial intelligence application company in Vietnam. Vinfast is Vietnam’s sole autonomous vehicle research and development center. Vinfast has invested a lot of time and money into putting together a fleet of cars that can go around the streets and snap photographs in a range of time and weather situations.
According to Nguyen Minh Tan – Vice Managing Director of Rikkei AI
“An AI product is a synthesis of many different materials, and data is one of the essential components. According to statistics, up to 80% of AI product development time is spent on data-related processing.”
In addition, training AI is similar to educating a child. AI can learn successfully if the correct data is used to train it. In contrast, if we teach AI with incorrect data, it will learn incorrectly. Furthermore, when heterogeneous data is used at an inaccurate moment, the AI becomes confused. Therefore, the privacy and security of data collecting and training for AI should be paid attention to; the more data appropriately utilized for training, the smarter the AI becomes and the more precisely it can recognize.
Here is one of the most critical challenges in AI, one that has kept researchers on edge for AI services in companies and start-ups. These companies might be boasting of above 90% accuracy, but humans can do better in all of these scenarios. For example, let our model predict whether the image is of a dog or a cat. The human can predict the correct output nearly every time, mopping up a stunning accuracy of above 99%.
For a deep learning model to perform a similar performance would require unprecedented finetuning, hyperparameter optimization, a large dataset, and a well-defined and accurate algorithm, along with robust computing power, uninterrupted training on train data, and testing on test data. That sounds like a lot of work, and it’s actually a hundred times more difficult than it sounds.
AI companies can avoid doing all the hard work by using a service provider to train specific deep learning models using pre-trained models. They are trained on millions of images and are fine-tuned for maximum accuracy, but the real problem is that they continue to show errors and would really struggle to reach human-level performance.
The amount of power these power-hungry algorithms use is a factor keeping most developers away. Machine Learning and Deep Learning are the stepping stones of this Artificial Intelligence, and they demand an ever-increasing number of cores and GPUs to work efficiently. There are various domains where we have ideas and knowledge to implement deep learning frameworks such as asteroid tracking, healthcare deployment, tracing of cosmic bodies, and much more.
They require a supercomputer’s computing power, and yes, supercomputers aren’t cheap. Although developers work on AI systems more effectively due to the availability of Cloud Computing and parallel processing systems, they come at a price. Not everyone can afford that with an increase in the inflow of unprecedented amounts of data and rapidly increasing complex algorithms.
Businesses will have to familiarize themselves with AI, which will help them understand how AI works. There is no denying that implementing AI in businesses can have several challenges, and you will start noticing these challenges when creating an AI strategy for your business. However, adopting a step-by-step and strategic approach will simplify the process of AI implementation to a certain level. Or you can use the service of Rikkeisoft. We are a reputable information technology company in Vietnam. With ten years of experience, Rikkeisoft are confident to solve all three main challenges of AI implementation in Vietnam. Rikkeisoft is also recognized by many international review sites, such as Top IT Outsourcing Companies by DesignRush.
If you’re interested in updating more about technical knowledge, please stay tuned for the new Rikkeisoft blog!
More From Blog
January 18, 2023
Top 10 Trustworthy IT Outsourcing Companies In Thailand
Nowadays, Thailand’s IT industry is rapidly growing and attracts numerous investors from foreign countries. To optimize the whole operation process, many software companies in Thailand have been searching for reliable companions to collaborate with in the long run, which in this case, are the outsourcing vendors. To improve your experience while outsourcing to Thailand, we […]
January 11, 2023
10 Common Risks in Software Development | How to Minimize?
The term “no one is immune to risks” is no longer true in today’s world. Every industry sector and market niche has its own pitfalls and bottlenecks that must be taken into account and IT is no exception. According to Statista, around $5473 million were spent worldwide for handling integrated risk management in the IT […]
January 9, 2023
10 Best Programming Languages for Finance & FinTech
Programming is a process of writing a language to make a computer perform certain instructions. This process is familiar to following the cooking recipe with an order list of requirements and actions. The “recipe” to build financial mobile apps nowadays is similar and more approachable as there are many programming languages available for coders. Finance […]
January 9, 2023
Outsourcing in Vietnam: Data-backed Opportunities & Challenges [Infographics]
Outsourcing is a rising sector in Vietnam, with the IT outsourcing industry alone projected to grow 13.47% by 2027. Affordability and a large pool of tech talents are among prominent reasons the country attracts global leaders looking for ways to cut costs effectively & manage their teams flexibly. Promising as it seems, there are plenty […]
January 6, 2023
What is MVP in Software Development? [Detailed Explaining]
We’re sure you’ve heard of the term MVP. But here, we are not talking about the most valuable players, we are talking about computers and programs. In software development, we’re talking about an MVP, sometimes known as a “minimum viable product,” a step where you validate the problem and test the solution. What is MVP […]
December 30, 2022
Fintech App Development 101
Technologies integrated finance are a crucial part of our hustle and bustle life. With up-to-date and advanced features, fintech apps help us save more time and enjoy diversified functionalities. Imagine without digital fintech app services, Covid-19 pandemic could seriously impacted our daily lives and individuals can not handle their financial needs. Therefore, this article will […]