Blockchain development in Vietnam

Vietnam Blockchain country is a big project for turning Vietnam into the next blockchain ecosystem on the world map.

The target is to connect with leaders, policy makers, businesses, profit and non-profit organizations in the blockchain ecosystem in Vietnam.

Infinity Blockchain Labs (IBL) says that if the campaign is successful, Vietnam’s image will be known as a pioneering country of a new technology by international investors. The project is expected to attract an abundant foreign investment in local technological start-ups.

One of the pilot projects is “Fruit chain” which is a solution to retrieve the origin of farm products on the first blockchain platform in Vietnam. Fruitchain is developed by IBL aiming to retrieve transparent information in value chain of the products. 

This project was tested on Cat Chu mango in Dong Thap Province. This is the first step before applications of blockchain technology are applied largely in agricultural area.

In addition, another significant organization of this campaign is Vietnam Blockchain Club. This is a non-profit organization of IBL, which is for connecting other people, sharing knowledge, testing new ideas and building blockchain applications.   

Especially, Vietnam Blockchain Club and IBL are official members of Vietnam Blockchain Branch founded by Vietnam E-Commerce Association (VECOM). The branch focuses on sharing knowledge of blockchain or training blockchain skills for people and business community.

In front of a bright blockchain future of a global digital economy, VECOM suggested Vietnam promote blockchain researchs and applications. Specifically, on April 23^rd 2018, VECOM established Vietnam Blockchain Branch. The branch opened officially on June 8^th 2018 at the Vietnam Blockchain Summit (VBS) with the topic “From Technology to Policy”.

Furthermore, the branch will associate with authorities and develop policies to improve legal framework as well as instructions, legislation to create an auspicious environment for blockchain applying in Vietnam. Besides, the branch organizes training courses to nurture resources and support start-ups activities of young talents.

IBL’s mission is to push social advancement by developing blockchain's potential and strength to make breakthrough solutions. Moreover, IBL’s vision is to become a leading center in research and developing blockchain technology and apply practical applications in business activities. Finally, further target of IBL is to boost Vietnam’s position as a blockchain country as well as the top choice for international projects.

About us:
TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/   

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Artificial Intelligence (AI) has just discovered a new super antibiotic that can kill the most dangerous antibiotic-resistant bacteria

Researchers have used artificial intelligence to make a major breakthrough in countering the world's most dangerous antibiotic-resistant bacteria. In just a few hours, the algorithm was able to find a new super antibiotic, which could destroy the most dangerous antibiotic-resistant bacteria.

Tests have shown that the new antibiotic can kill antibiotic-resistant bacteria, including Acinetobacter and Enterobacteriaceae. These are two of the three levels of the alert level, which the World Health Organization (WHO) classifies as new antibiotic-resistant bacteria.

This is the first antibiotic found in history. Researcher Regina Barzilay at MIT said: "I think this is the strongest antibiotic that has been made to date. It can kill some dangerous antibiotic resistant bacteria”.

In order to find a new antibiotic, first of all, researchers have to teach a Google’s deep learning algorithm to determine which types of molecules can kill bacteria. To do this, they must provide information on the atomic and molecular features of nearly 2,500 drugs and natural compounds for AI to study.

After entering enough data, AI researchers started working to find new antibiotics. However, instead of focusing on finding an effective antibiotic, the algorithm will focus on finding an unprecedented one. That is the key to destroy the current antibiotic-resistant bacteria.

To expand and search for more new powerful antibiotics, researchers turned to a huge database of about 1.5 billion compounds. They put the algorithm to work with about 107 million of them. After 3 days, AI released a list of 23 new potential antibiotics.

The head of the research project, Dr. Jonathan Stokes, said it was impossible to screen all 107 million compounds manually. Artificial intelligence has helped accomplish this utopia, and shortened the time to just a few days.

Antibiotic-resistance is a concern, because without new antibiotics, 10 million people around the world could be at risk of infection each year. But with artificial intelligence, this worry would be solved soon.

Source: https://cafebiz.vn/tri-tue-nhan-tao-vua-tim-ra-mot-loai-sieu-khang-sinh-moi-co-the-tieu-diet-vi-khuan-khang-khang-sinh-nguy-hiem-nhat-20200224105144313.chn

About us:

TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/   

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AI and Machine Learning: Why should be Python?

Over the past few years, Python has been celebrated as a relentless climb to distinction and is actually rivaling the situation of one of the planet's most well-known programming dialects.

            And as it rightly says, "If you're famous, there's more to learn than just the stuff themselves!"
            Backed up for applications ranging from cloud advancement to scripting and process mechanization, Python is increasingly becoming the top decision for human-made intelligence or (AI), ML, and deep learning projects among engineers.

Computer-based intelligence or Artificial Intelligence has made application engineers a universe of opportunity. Computer-based information allows Spotify to prescribe to customers’ artisans and melodies, or Netflix to understand what shows you need to see immediately. It is also commonly used by client assistance organizations to drive self-administration and enhance work processes as well as worker productivity.

Simulated or Machine-driven intelligence undertakings contrast with conventional programming undertakings. The distinctions lie in the innovation stack, the skills needed for an AI-based experiment, and the need for in-depth research. To execute your AI wishes, you should use a programming language that is steady, adaptable and has tools that are accessible. Python is offering all of this, which is why we see the Python AI bunches extending today.

Python assists engineers to be competitive and confident about the product they are creating, from development to arrangement and upkeep.

Advantages that make Python the best fit for AI and AI-based undertakings include effortless and reliable access to extraordinary libraries and frameworks for AI and AI (ML) are adaptability, stage freedom, and an extensive network, contributing to the language's general popularity.

Why can everyone easily count on Python's efficiency to make things happen?

-                    An incredible library environment:

            One of the main reasons why Python is the most common programming language used for AI is an exceptional variety of libraries. A library is a module or a set of modules distributed by different sources such as PyPi that integrates a pre-composed bit of code that enables clients to get to some usefulness or perform different activities. Python libraries give things at the base level, so programmers do not necessarily need to code them from the earliest starting point.

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           Primary and inevitable:

           Python offers a short and decipherable code. While complex calculations and flexible work processes remain behind AI and AI, the effortlessness of Python allows engineers to build robust frameworks. Designers find a workable pace in their efforts to address the ML issue, rather than focusing on the specialized subtleties of the language.

             In fact, Python attracts a variety of programmers because it's anything but difficult to learn. Python code is realistic for humans, makes it easier to create AI models.

             Numerous software engineers argue that Python is more intuitive than other programming dialects. Others put together multiple systems, libraries, and upgrades that boost the execution of different functionalities. It is commonly acknowledged that Python is appropriate for shared performance when numerous engineers are involved. Because Python is a commonly used language, it can do a lot of complex AI tasks and enable you to create models quickly that allow you to test your item for AI purposes.

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          The limitation below:

           Working in the ML and AI fields means managing a lot of information that you need to process most advantageously and convincingly. The low section hindrance helps more knowledge researchers to quickly get Python and start using it for AI advancement without squandering an over-exercise in language learning.

             After the regular English language, Python programming language takes place, making the road to learning simpler. Its straightforward punctuation allows you to work with complex frameworks quickly, ensuring clear relationships between the components of the Framework.

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            Wide library and system options:

             It can be doubtful to upgrade AI and ML calculations, and also requires a lot of time. Having a well-organized and well-tried environment is critical to encouraging designers to think about the best coding arrangements.

               Software engineers go to various Python frameworks and libraries to reduce the time needed for development. A software library is a pre-composed code which is used by programmers to recognize common programming errors. With its rich software stack, Python has a broad array of computerized logic and AI libraries.

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              In summary:

              Computer-based intelligence or artificial intelligence profoundly affects the world we live in, with new applications steadily increasing. Brilliant designers choose Python as their favorite programming language for the numerous benefits that make it particularly suitable for AI and deep learning projects.

                 Python's wide selection of AI specific libraries and systems disassemble the process of development and cut time for advancement. The basic grammar and comprehensibility of Python is advancing fast testing of complex calculations and rendering the language available to non-developers.

It also reduces the psychological overhead on engineers, opening up their mental assets with the goal of focusing on critical thinking and achieving venture goals. Ultimately, the simple punctuation makes it easier for designers to work together, or switch transitions between them.

Furthermore, Python flaunts a large, diverse network of designers who are prepared to offer help and support, which can be critical when handling these complex projects.

While other programming dialects can also be used in AI projects, there's no escape from the way Python is at the forefront and critical thinking should be provided. That's why you should consider Python for your AI plan.

About us:
TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/   

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Applying 5G in Healthcare: Promises and challenges

5G brings huge opportunity to renovate the healthcare industry.

Source: Telit

The fifth generation of telecommunication holds promise to transform many world’s industries. Among them, healthcare is reported to experience the biggest changes. 5G development can change this industry at large, from improving existing devices to carrying out new services.

In detail, 5G betters imaging tools such as X-rays and MRIs, helping these devices operate wirelessly. Also, it can be a great helping hand in complex medical scenarios training by enabling augmented and virtual reality tools. However, the application of 5G in healthcare given the most attention right now is remote surgery.

Actually, remote surgery is not a completely new definition. The term has long been introduced, nonetheless, is considered to be impossible as even a small error in data transmission or little lagging in connection can cause risks related to lives. Now, with the development of 5G, which provides connection 10 to 100 times faster than a typical 4G connection, remote surgery has potential to be applied into reality.

With remote surgery, patients from rural and resource-limited areas are given chances to access to modern and high-quality healthcare services. 5G helps eliminate the distance, hence minimize the travel fee and provide emergent services at any times. Also, it would become an effective assistance to the government in tackling urbanization, as people from remoted areas can receive high-quality treatment despite living far away from the hospitals. In other words, thanks to 5G, geographical barriers will be removed, giving people equal opportunities to be treated by experts wherever they reside.

5G holds bright future for healthcare, but challenges as well as questions remain. In order to put remote surgery into reality, it demands 5G coverage to be available in both places where the surgeon and the patient is. The challenges include all hospitals being armed with 5G technology and upgraded devices to make sure that every information in remote surgery could be transmitted in real-time. The above mentioned questions, of course, cannot be solved in just 1 or 2 days. They demand both time and effort from not only the government, but also healthcare experts and 5G engineers in their relative fields.

In short, the arrival of 5G is expected to renovate the whole healthcare industry by improving speed while reducing latency. It brings remote surgery, considered unthinkable before, closer to the reality. Even though many issues remain to be solved, 5G shows promise for a modern, innovative healthcare industry in the future.

About us: 

TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/

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Fast development of Artificial Intelligence in Vietnam

In Vietnam, Artificial Intelligence is growing speedily and continuously confirming that it is a turning point of technology in the 4.0 Generation. High-tech development has established AI tactics to use AI for pushing economic growth. 

In recent years, more and more organizations have applied AI in different areas such as education, healthcare, telecommunications… AI has been not only the lead in the market but also made massive revenue.

Presently, AI has been received the most attention in the world. Several nations have invested billions of US dollars in AI expansion plans with the desire to be the winner on AI racing track.

With AI trend, Vietnam is not the exception. Over the last few years, Vietnam’s AI industry has many incredible developments with AI in a wide range of works.  

Big local technology companies really enjoy spending money on AI, developing AI as well as deploying AI strategies. Furthermore, Inland corporations in addition to inventive star-ups implement AI in lots of products in latest commerce plans.

Otherwise, as other nations, Vietnam also faces the lack of big databases, resources, infrastructure…

External technology enterprises and top AI corporations in the world have launched offices in Vietnam to exploit well-qualified workforce to server for their markets.  

Foreign countries’ invitations have drawn significant attentions of Vietnamese young labor force in AI industry. While the preparation for these people in the AI field is still inadequate as well as not having enough well-trained instructors. Hence, Vietnam need to have appropriate plans in developing AI workforce.

Especially, Vietnam has many people who are doing AI research overseas together with outstanding AI specialists in technologically advanced nations. As a result, it is essential to associate with them and boost their awareness to devote to Vietnam.

At the recent onshore and offshore AI meetings, Vietnam has been said to have a weaker beginning compared to other nations. If Vietnam sticks to AI development strategies as technologically advanced nations, it will be hard to catch up with them.

AI enterprises has selected to pay attention on dealing with minor and particular problems in daily life. However, they have not still had mutual agreements in shaping a shared platform and data sources on technologies for the AI environment.

Hence, it is important for Vietnam to follow its path for the AI development strategies. Vietnam should have special rules to develop engineers in the high-tech field. In addition, Vietnam needs to associate with AI communities, which have shaped freely, to increase the delivery of data, research, and applications to making a stronger AI platform.

About us:

TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/   

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Adopt AI to tackle IoT security risks

As industry 4.0 trends continue, people are in the middle of an Internet of Things gold rush, with IoT devices are seen everywhere now, from tech giants’ offices to our daily used cars, homes, etc. According to Gartner, the number of IoT devices is expected to grow to 41.6 billion by 2025, along with over 1 trillion USD spent on their development.

The potential is huge, however, there raises an issue of security. The cost of cyber-criminal activity, reported by Fox News, will reach 6 trillion USD by 2021, which poses a big threat to IoT devices.

IoT devices face security threats. Source: IoT Business News

In Internet of Things, every device is connected, hence forming a network with large data sets. Once IoT device is targeted then attacked by hackers, businesses or organizations face a huge loss of data, or data exfiltration, data breaches. This does harm to every businesses, as it can be extraordinary costly for business to regain control of their devices, as well as confidential information can be leaked with abnormal purpose.

In order to manage security risks towards IoT devices, it is suggested that we should use Blockchain or Artificial Intelligence (AI). Blockchain’s outstanding feature is decentralized system, which is suitable to help secure data within connected devices. Meanwhile, AI is believed to have huge potential in tackling IoT security challenges efficiently.  

In detail, AI acts as a brain to help devices make decisions. In this case, people can use AI to predict danger and abnormal act. For instance, when the neural network senses some suspicious action invaded in the devices, it can make that IoT device immediately shut down to avoid further damage.

Artificial Intelligence and Internet of Things are completely independent technologies. These are two important factors in Industry 4.0, and now they can be combined in order to bring more outstanding results. There even appeared a term called “AIoT”, which defines the connected and smart devices that are designed to be self-protected as well as self-corrected. The key difference between Internet of Things (IoT) and Artificial Intelligence of Things (AIoT) is IoT being proactive, while AIoT being reactive.

Source: Data Driven

In short, IoT security risk has always been a great concern for businesses, organizations. With an unstoppable growing volume of data nowadays, it can be extremely harmful for businesses if they lost their control of IoT systems to cyber-criminal. The problems remain unsolved, however, there appears a more comprehensive approach to improve the situation. AIoT is believed to not only solve the existing issue, but also hold great promise for the next development stage of Industry 4.0.

About us: 

TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/

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10 technology trends to be aware of in 2020

Trend No 1. Hyperautomation

Automation uses technology to automate tasks that once required humans. Hyperautomation deals with the application of advanced technologies, including artificialintelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans.

Hyperautomation often results in the creation of a digital twin of the organization.

hyperautomation today involves a combination of tools, including robotic process automation (RPA), intelligent business management software (iBPMS) and AI, with a goal of increasingly AI-driven decision making. 

 

Trend No. 2: Multiexperience

Multiexperience replaces technology-literate people with people-literate technology.

Currently multiexperience focuses on immersive experiences that use augmented reality (AR), virtual (VR), mixed reality, multichannel human-machine interfaces and sensing technologies. The combination of these technologies can be used for a simple AR overlay or a fully immersive VR experience. 

Trend No. 3: Democratization

Democratization of technology means providing people with easy access to technical or business expertise without extensive (and costly) training. It focuses on four key areas — application development, data and analytics, design and knowledge — and is often referred to as “citizen access,” which has led to the rise of citizen data scientists, citizen programmers and more. 

 

Trend No. 4: Human augmentation

Human augmentation is the use of technology to enhance a person’s cognitive and physical experiences.

Physical augmentation falls into four main categories: Sensory augmentation (hearing, vision, perception), appendage and biological function augmentation (exoskeletons, prosthetics), brain augmentation (implants to treat seizures) and genetic augmentation (somatic gene and cell therapy). 

Cognitive augmentation enhances a human’s ability to think and make better decisions. Human augmentation carries a range of cultural and ethical implications.

 

Trend No. 5: Transparency and traceability

AI and ML are increasingly used to make decisions in place of humans, evolving the trust crisis and driving the need for ideas like explainable AI and AI governance. 

This trend requires a focus on six key elements of trust: Ethics, integrity, openness, accountability, competence and consistency. 

Legislation is being enacted around the world, driving evolution and laying the ground rules for organizations. 

 

Trend No. 6: The empowered edge

Edge computing is a topology where information processing and content collection and delivery are placed closer to the sources of the information, with the idea that keeping traffic local and distributed will reduce latency. Empowered edge looks at how these devices are increasing and forming the foundations for smart spaces, and moves key applications and services closer to the people and devices that use them.

By 2023, there could be more than 20 times as many smart devices at the edge of the network as in conventional IT roles.

 

Trend No. 7: The distributed cloud

Distributed cloud refers to the distribution of public cloud services to locations outside the cloud provider’s physical data centers, but which are still controlled by the provider.

Distributed cloud allows data centers to be located anywhere. This solves both technical issues like latency and also regulatory challenges like data sovereignty. It also offers the benefits of a public cloud service alongside the benefits of a private, local cloud. 

 

Trend No. 8: Autonomous things

Autonomous things, which include drones, robots, ships and appliances, exploit AI to perform tasks usually done by humans. This technology operates on a spectrum of intelligence ranging from semiautonomous to fully autonomous and across a variety of environments including air, sea and land.

Trend No. 9: Practical blockchain

Blockchain, which is already appearing in experimental and small-scope projects, will be fully scalable by 2023.

In the future, true blockchain or “blockchain complete” will have the potential to transform industries, and eventually the economy, as complementary technologies such as AI and the IoT begin to integrate alongside blockchain. Blockchain, which is already appearing in experimental and small-scope projects, will be fully scalable by 2023.

 

Trend No. 10: AI security 

Evolving technologies such as hyperautomation and autonomous things offer transformational opportunities in the business world. However, they also create security vulnerabilities in new potential points of attack.

AI security has three key perspectives:

1.      Protecting AI-powered systems: Securing AI training data, training pipelines and ML models. 

2.      Leveraging AI to enhance security defense: Using ML to understand patterns, uncover attacks and automate parts of the cybersecurity processes. 

3.      Anticipating nefarious use of AI by attackers: Identifying attacks and defending against them. 

Source: https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2020/

About us: TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,400 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects.
Visit us at: https://www.tmasolutions.com/

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Artificial Intelligence (AI) discovers disease related genes

   

   Base on artificial neural networks, people can observe an impressive amount of gene data expression, also discover specific groups of disease-related genes. Researchers at Linköping University had published this important study in Nature Communications that they all looking for whether the method can be applied within accurate medicine and personalized treatments. 

  For any social media platforms that you commonly use, the suggestions feature may recommends you whom you may want to add contact with. This process depends on you and others’ activities that may have common contact, which indicates that you might have known each other before. Similarly, the maps that scientists trying to create based on the interaction between genes and proteins. The new trial using artificial intelligence, or AI, to investigates the possibility of adding deep learning as a method to discover biological networks, entities known as “artificial neural networks” being trained by experimental data. Since this networks get used to learn how to search for patterns in complex data storage, it is easy to transform this into applications such as image recognition. Unfortunately, this method hasn’t been popularized in biological researches yet.

 
  The scientists contain any databases with information about the expression patterns of over 20,000 genes correspond with the same number of samples. The “raw” information, in terms of researchers did not attach the network information about which gene belongs to healthy or people who have diseases.

 There is one of the challenges for machine learning: Is it possible to get exactly how an artificial neural network can solve a given task. AI sometimes was called as a “black box” – we only get what we have put into the box and it produced results. No specific steps included. The networks consist an input and out layer that bring the result of the carry out information processing by the whole system. When the network been trained, scientists wondered whether they could “lift” the lid of the black box and understand the process.

 
  The scientists then investigated to confirm that whether the model of gene expression could be used to determine which patterns are abnormal and which is fine. The result showed that the model find relevant which agree well with biological mechanisms in the body. Since it has been trained using unclassified data, it proves that the network has possibly found brand new patterns, relevant form a biological respective.        

About us:

TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/   

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Programming languages: Why developers want to learn Golang and Python most?

The top two programming languages that worldwide program engineers want to learn next, surprisingly, are Golang and Python, reported after a survey over 116,000 developers from 162 countries to come up with this year's results about related topics (such as their education levels, job prospects, skills acquisition, and wanted salaries). The whole survey is done by HackerRank – a developer skills-matching platform.

In fact, Golang isn't listed in the top-10 of the most widely known programming languages recently, but it already comes top for languages that developers are wanted to learn. The percentage of developers who are eyeing Golang as their next language reached 36%, followed by 28% who nominate Python as their next target. Among the list, there also other languages ranked high on the learning priority, including Kotlin, which is popular among Android app developers, TypeScript, and R, a popular language among data scientists. The remaining top 10 desired languages are Scala, Swift, Rust, Ruby, and JavaScript. 

HackerRank found that C, created in the 1970s, is used by nearly 40% of Gen Z respondents to learn how to code, making it by far the most popular language to cut your teeth on for that generation. Besides, the result pointed out that only 30% of millennials started out with C, while Gen X and Baby Boomers mostly started out learning BASIC – a programming language created in 1964.

The most concern for recruiting in 2020, with 38%, is looking for full-stack developers in manager levels (the following second and third are back-end developers and data scientists). However, they have to face with more pressures than others, with 60% tasked learning a strange and completely new framework, and while 45% required to learn a new language the previous year. That proportion is much higher than any other cateGolangries. But the thing is, across all groups no less than 40% said they have had to learn a new language in the last year. 

JavaScript is always in the top programming language skill that most recruiters in some big locations are looking for, and the followers are Python, Java, C#, C++, PHP, C, Golang, and Ruby. The most well-known languages among developers somehow reflect the sought-after languages. JavaScript also rank 1 in this list, followed by Java, C, Python, C++, C#, PHP, TypeScript, Pascal and R. Although JavaScript is the most widely known language in the world, the final result showed that only 5% of feedbacks decided to choose it as their basic programming language. 

About us:

TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/

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Which language is best to be used in AI? Golang or Python?

Launched in 2009, Golang recently turned ten. Programmers become more productive because this language developed by Google. Golang's purpose was to create a language that would eliminate the so-called “extraneous garbage” of programming languages like C++. It provides the capability of compiling to machine code, the ability of run-time reflection, and provides the convenience of garbage collection.

The question is: Will Golang replace Python? No, it won't.

Has been widely used for numerous purposes, it's hard for Python to become obsolete. It is a programming language that compiles a thousand components from individual modules to packages of the entire development. Python also has a strong community that promises to keep it alive for the next few decades. Being tested for multiple numbers of environments, it was found to be easy for beginners to work with Python programming and has been deemed favorite amongst young developers. Go language outperforms Python while writing server-side scripts. Thus, when looking for ultra-performant concurrent services that have quick deployment cycles Golang is said to outperform Python.

However, in recent times Golang and Python have been termed as the most popular languages that are perfect for AI professionals. As organizations work with both these languages, it can be challenging for you to come up with a stern solution.

Advantages gained from using Golang for developing AI.

High scalability and computation: Golang has a higher potential in scalability and performance as compared to Python. The idea of using Go is because of its high speed as compared to the speed of math computation. For instance, it can cope with complex math problems of up to 20-50 times higher and much faster as compared to Python.

Vast AI purposes covered by Golang: Although Go offers small libraries it is consistently growing thus, addressing a large range of AI purposes. Go libraries such as GoLearn (data handling), Goml (passing data), and Hector (binary classification problems) are some of the libraries that serve AI and its applications.

Offers a good amount of code readability: Algorithms used in Go offers a minimalist approach allowing developers to easily create readable codes.

Ease of usage of Go libraries by Go developers: Most of the Go developers do not need to opt for libraries written in other programming languages. The core advantage of having libraries in Go is that it gives the AI professionals working programming with Go a developer’s comfort.

The benefits of using Python for developing AI.

Multiple numbers of libraries: Multiple libraries can now help AI engineers build new algorithms, conduct dataset processing, do model processing, work with the most complex data, and many more other functions. Not to forget, TensorFlow is one of the most popular libraries (open source) that is utilized for many machine learning applications of Google.

Python as a language is accessible: In business terms, language accessibility simply means having a vast market of experts in Python programming. Moreover, as we’re aware these programming languages are widespread across the globe.

Strong community: Python has a well-established and strong community. Based on GitHub’s report in 2019, there was nearly 1 million pull request sent over worldwide. The community tends to contribute toward creating new libraries to extending toolset and updating documentation.

About us: 

TMA Solutions was established in 1997 to provide quality software outsourcing services to leading companies worldwide. We are one of the largest software outsourcing companies in Vietnam with 2,600 engineers. Our engineering team was selected from a large pool of Vietnam IT resources; they are well-trained and have successfully completed many large and complex projects. Please visit us: https://www.tmasolutions.com/

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