Top 5 considerations for creating a cloud-based pipeline (Part 2)

This part will cover the last three considerations when creating and running an automated, cloud-based pipeline.

 3. It's All About Continuous Improvement

Steep Learning Curves

Before you start creating your cloud-based pipeline, there is some learning you have to do. It might be learning Kubernetes, AWS products, Google Cloud products, Microsoft Azure products, etc. As a community, we must spend time to explore new technologies, learn how to apply them, and how to advance these skills in our industry, even if it takes us weeks to find out and understand how to deploy such technology.

(Source: Valamis)

Keep Fail-Safes in Mind

In general, you should inspect ways your application might fail if a configuration file is changed or a file is incorrectly updated to the pipeline. Therefore, spend time on planning and you can limit the possibility of this happening.

4. Enable Self-Service Features

Rapid Onboarding to New Teams and Pipelines

Adding a role to your architecture should be simple and easy when you onboard new engineers. Spending countless hours accessing things can hinder the process for you and your new team members as they took to start development immediately.

Visibility of Applications

Your team should be provided with tools to monitor their application day-to-day. You can also utilize integrations to run audits on your application's health.

5. Track Your Pipeline, Microservices, and Compliance Policies

The Importance of Dashboards

Having a general-purpose dashboard to manage or view your clusters will allow you to troubleshoot defects and manage clusters' health of all your applications. Having a birds-eye view of all microservices running and an easy dashboard to view will make your life much simpler.

Enforce Policies: Approval Gates, Compliance Checks, and ACLs

Setting up roles for your engineering team and understanding the roles everyone will have to the application is very important. Finally, you should set-up compliance checks to keep track of roles and their access to the application.

Source: Dzone

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 2,500 engineers.

Visit us at https://www.tmasolutions.com/

Read More

Combination Of AI & Blockchain - The Revolution Of Financial Industry (Part 1)

The revolution in ICT has affected finance industry at an increasing rate for decades. The financial firms are trying to cope with these changes by adopting new kinds of technology to deal with the increasing demand and the huge increase in the competition worldwide in the financial sector.

While so many industries are beginning to embrace the amazing options these technologies – Artificial Intelligence and Blockchain technology offer – helping them to create more value,  boosting sales, and so on,  it’s interesting to know that the combination of both will positively revolutionize the future of the fintech industry.

The convergence of Artificial Intelligence and Blockchain brings a better future for the Financial Industry.

With the superb benefits of Blockchain and AI, this combination will yield bewildering results and take an entirely new level across all industries especially with the financial sector. Here are amazing features and underlying capacities that come to play as below:

1. A Secured Payment Network

One of the underlying benefits of blockchain technology is its unique ability to operate as a borderless payment network. Blockchain facilitates a frictionless payment with low prices and at a faster pace compared to the traditional methods. 

Unfortunately, there are still some existing security concerns affecting its widespread adoption. Theft is increasing and getting more sophisticated daily since it requires a set of public and private keys to run a blockchain business.

By leveraging the power of AI and ML, any improper activities on your blockchain account can be identified, thereby alerting the account owner about some human involvement. Moreover, AI can analyze the behavior and biometrics to help eliminate any security susceptibility in payment networks.

2. Controlled Automation for Financial Activities

There is no doubt that finance is moving towards automation. On the other hand, there are pending issues that could pose threats to the finance sector if ‘calculated restrictions’ aren’t placed on automated processes. Meanwhile, to run a smooth automation financial system, it must occur synchronically with built-in checks and balances. In this case, smart contracts facilitate automatic processes, while AI and ML can look for irregularities simultaneously. Therefore, merging blockchain-powered smart contracts with AI can help verify the smart contracts and predict its vulnerability that can be exploited by theft. The resulting infrastructure would facilitate a completely secure, transparent, and efficient financial transaction.

3. An Efficient Financial Service

About 57% of businesses said that cost-saving is the primary benefit of participating in a consortia blockchain network, according to the 2019 Deloitte’s Global Blockchain Survey. The main reason why financial companies implementing both AI and Blockchain solutions is to improve their service speed and service quality. The result of this combination will help businesses minimize costs, maximize profits while still providing excellent value to customers.

Source: DZone

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 2,500 engineers.

Visit us at https://www.tmasolutions.com/

Read More

Some Predictions for the Future of IoT and Mobile App Integration (Part 2)

The combination of Internet of Things (IoT) and mobile apps is believed to increase in this year and in the near future which is shown in these following exciting trends. With these predictions, researchers and companies should pay more attention to develop them as well as take advantage of them via paving the way.

The application of IoT and mobile apps combination (Photo: Key Universal)

This continued part is used to discuss about the other best predictions that depict real-world applications of IoT technologies:

3. Improved Retail Shopping Experience

There is some difference between the combination of IoT and mobile apps in the retail industry. In spite of a few good cases recorded, it’s clear that the technology will be popular among retailers. 

The retail giant has utilized IoT sensors, cameras, and other equipment in a brick-and-mortar store to exclude checkout lines. A customer enters the store and then scans the special app’s barcode of the retail store, takes the products, and just leaves. 

After exiting the store, the customer is sent a receipt. The concept, enabled by IoT and AI technologies, takes the traditional convenience store shopping experience up several notches.

Needless to say, other companies are simply unable to afford. That is the reason why they lose an opportunity to improve the shopping experience with IoT. Combining the advantages of mobile self-service apps with connected devices is an opportunity that’s too good to pass up. 

4. More Use Cases in Home Automation

Wireless kitchen appliances, smart mirrors, video doorbells, smart lightning, robotic vacuum cleaners – home automation technology is already used by millions people around the world. The overall awareness of tools like AI-powered voice assistants increases rapidly. As the technology grows, there is little doubt over the future of smart home systems. 

Current home automation systems are considered to be an impressive combination of IoT components, apps, and physical equipment. Despite the fact that the apps perform very complex operations, they’re incredibly user-friendly and easy-to-use. 

Based on some research conducted around the world, there are some emerging trends that are likely to advance home automation in the future. The reports demonstrated some following trends: A greater role for AI software; more use cases in security and surveillance; more control over home objects (voice-controlled smart showers, shape-shifting furniture, and etc); more health-related devices (smart sensors and cameras in refrigerators suggesting product alternatives and reminding them to do shopping).

5. More IoT Wearables for Everyday Use

There is an increase in the demand of mobile app development services in the creation of apps which are not only simple applications such as fitness trackers, but also smart homes, sleep quality assessment tools, and others. It is no doubt that IoT has been playing a major role in all of this, providing new opportunities and making wearables get better and more functional. 

According to a recent Clutch survey, about 35 percent of people participating in the survey said that they owned a wearable device. It also depicts that smartwatches and fitness trackers are the most popular wearables that people use in daily life. Interestingly, more than 90 percent of the surveyed admitted that they have their wearables connected to a smartphone via an app. 

With so many smartphone users preferring wearables, we should make more efforts to make the technology smarter and more useful. After 2020, the adoption of the technology certainly increases, as more use cases and functions emerge.

Source: DZone

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 2,500 engineers. Visit us at https://www.tmasolutions.com/

Read More

Artificial Intelligence turns human thoughts into text applying brain implant

By analyzing human brain activity, an artificial intelligence system can translate a person’s thoughts into real words with an accuracy rate of 97%. From a set of between 30 and 50 sentences, AI is able to decipher up to 250 words in real-time.

The researchers set the algorithm utilizing the neural signals of four women with electrodes implanted in their brains, which were already in place to monitor epileptic seizures. While the people were constantly reading sentences aloud, the researchers provided the brain data to the AI to eliminate patterns that may be related to individual words. The average word error rate per repeating population is as low as 3%.

Speed ​​and accuracy, compared to natural speech, are tough standards for scientists to develop artificial intelligence systems that decode human brain signals. A trained repetitive neural network for the advancement of machine translation can encode each sentence-length sequence of nerve activity into an abstract representation and decode them into complete English sentences.

AI can translate neural activity into sentences with an accuracy rate of 97 percent (Photo: Getty Images)

However, the system is still deficient. In fact, the average working vocabulary of an English speaker is estimated to be around 20,000 words and this is what hinders normal verbal understanding of the system. Each new word increases the number of possible sentences while the AI system improves prediction based on learning the structure of a sentence. As a result, the scaling of the system is hampered and the overall accuracy also decreases.

In order to partially solve this problem, a possibility is presented to integrate the system with other brain-computer interface technologies using different types of algorithms and implants. In 2019, a report by the Royal Society claimed that the neural interfaces connecting computers to human brains would enable mind reading between humans. Besides, within two decades, diseases like Alzheimer's are able to be treated with the use of these interfaces, which will be an “established option”.

In the future, applications for linking the human brain to technology will be upgraded to a variety of ways such as humans can taste and smell with no sensory experience.

Source: Independent

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 2,500 engineers.

Visit us at https://www.tmasolutions.com/

Read More

Top 5 considerations for creating a cloud-based pipeline (Part 1)

If you have already monitored your deployments in the development operation, why don't you automate the process behind them? This article will cover the top 5 considerations when creating and running an automated, cloud-based pipeline.

1. Consider Your Business Needs First

Making all of your applications and environments is pivotal to hybrid computing and should be a goal for every company to achieve.

Hybrid cloud is a combination of mixed computing, services, and data storage that can be spun up in person, via private cloud, or via public cloud services. Public cloud services with orchestration between the two platforms and are widely used today with Amazon Web Services (AWS) or Google Cloud Platform.

Am I Hybrid?

If you are adopting a public platform that sends data to a private cloud or leveraging your SaaS applications and transferring data between independent resources - then you are already using hybrid computing. The goal of this model is to combine services and data coming from different places to build a unified, automated, well-managed computing environment.

What do I need to research?

It is necessary for you to define that if your organization needs a private cloud to meet the security demand. For example, those companies in Finance, Law, Healthcare, etc. sectors have to limit what cloud services they can use due to some confidential issues. However, if you are running an e-commerce store, you don’t have to concern so much about it until your business grows and has a larger customer base.

(Source: sdxcentral)

2. Develop Your Cloud-Based Pipeline As Part of Your Apps

Everything As Code: Configurations, Environments, Automations, etc.

To develop a pipeline of your cloud service, you need to set up your configuration and environment files. The bad practices of setting up servers without any configurable way to spin up a new instance immediately will not work when creating automation.

Moreover, you have to model everything in case of any application to be reused and automate everything: scheduled jobs, migration, compiling jobs, etc. By doing this, you will find is easier to maintain the system.

Put Everything in the Source Code

Keeping a repository for your application is key to being able to deploy. Your codebase needs to be set up in different environments in the deploy process for master release, staging, and development branches.

Process, Architecture, Deploy

Everything is a process. It is important to build an architecture that helps your team work better to produce great software. Deployment stages should be quick and easy and shouldn’t be a burden for team to spend so much time to properly release. 

Source: Dzone

 

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 2,500 engineers.

Visit us at https://www.tmasolutions.com/

 

Read More

Some Predictions for the Future of IoT and Mobile App Integration (Part 1)

With many benefits of the connection between the Internet of Things (IoT) and mobile applications, especially bringing mobile apps to a new level, the paper demonstrates five predictions that represent the real-world application of IoT technology. In part 1, there are two of them mentioned. 

The connection between the IoT and mobile apps (Photo: Clearbridge Mobile)

Smartphones provide IoT solutions with entire portability. To help the user be familiar with the process, they are able to manage IoT devices easily through a mobile application.

Besides, IoT will advance mobile app development to a whole new stage. There is no doubt that businesses around the world are watching and waiting to see how they can have some control over a smartphone. IoT app development is considered to have real potential to become a multi-million-dollar industry. It is not, however, just about the money. With a great deal of exciting devices and equipment, online can have an increase every single day. 

To acknowledge how apps and IoT can work together, some of the best predictions that depict real-world applications of IoT technologies are explained by following: 

1. The Rise of Automotive Apps

IoT automotive apps have been nowadays becoming a serious deal for auto manufacturers. With some big companies like Tesla, setting the tone by releasing connected, autonomous vehicles, the time these apps becoming a norm is all quickly approaching. 

IoT automotive apps also make perfect sense. Helping people with handling tasks they do every day is the very promise of IoT , and in fact, we spend a lot of time in our cars. IoT makes this one go further by automating maintenance, infotainment tasks, safety procedures, and diagnostics. 

2. More Apps in Industrial Production Management

The rapidly approaching industry 4.0 is one of the important reasons making manufacturers change their way to run plants and factories. Additionally, IoT sensors which are the application of industry 4.0 are now used to track both moving and non-moving assets and assist people on the production function in improving their management and usage.  

A smartphone app can display the movement of the connected equipment and people inside production facilities. For plant managers, it could be a blessing. Having an app collecting the movement data from assets helps to: 

• Track shift performance
• Identifies employees or assets entering restricted areas
• Find the location of an employee in real-time in case of the need to reassign them to another task
• Monitor manufacturing flow by tracking product parts of equipment like toolboxes.

Source: DZone.

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 2,500 engineers. Visit us at https://www.tmasolutions.com/

Read More

The bio-inspired AI system allows higher precision of gesture recognition

Scientists in Singapore have developed an AI system that recognizes hand gestures by combining skin-like electronics with computer vision.

Over the last decade, AI gesture recognition systems have become a valuable development in various fields and adopted in high-precision surgical robots, health monitoring equipment, and gaming systems.

This advanced technology first was visual-only then has been improved thanks to integrating inputs from wearable sensors, an approach called 'data fusion'. The wearable sensors recreate the skin's sensing ability, one of which is known as 'somatosensory'.

Nevertheless, the precision of gesture recognition is hindered by the low quality of data coming from wearable sensors. This problem happens due to poor contact with the user, the effects of visually blocked objects, and poor lighting. More challenges are triggered by the mismatch between visual and sensory data and datasets, leading to inefficient and slower response times.

Photo: Medgadget

To address these challenges, scientists in Singapore created a 'bioinspired' data fusion system that uses skin-like stretchable strain sensors made from single-walled carbon nanotubes, and an AI approach that resembles the way that the skin senses and vision are handled together in the brain.

These scientists developed their bio-inspired AI system by combining three neural network approaches in one system: they used a 'convolutional neural network', which is a machine learning method for early visual processing, a multilayer neural network for early somatosensory information processing, and a 'sparse neural network' to 'fuse' the visual and somatosensory information together.

The data fusion architecture has its own unique bioinspired features which include a human-made system resembling the somatosensory-visual fusion hierarchy in the brain. Plus, wearable sensors use stretchable strain sensors that comfortably attach to the human skin. Both mentioned high-tech features make gesture recognition more accurately and efficiently compared with existing methods.

Photo: ISARQ

High recognition accuracy even in poor environmental conditions

Scientists tested their bio-inspired AI system using a robot controlled through hand gestures and guiding it through a maze. Results showed that bio-inspired AI gesture recognition was able to guide the robot through the maze with zero errors, compared to six recognition errors made by a visual-based recognition system.

The high accuracy was also maintained under poor conditions including noise and unfavorable lighting. The findings from this paper bring humans another step forward to a smarter and more machine-supported world. This achievement gives us hope that one day we could physically control everything with great reliability and precision through a gesture.

Source: Science Daily

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 2,500 engineers.

Visit us at https://www.tmasolutions.com/

Read More

Telemedicine is replacing in-person care amid the pandemic

Not only does it provide care that otherwise would not be accessible to patients in need, but telemedicine is also a safety measure for medical staff to avoid the risk of virus contraction.

Many people with health problems, especially chronic illnesses are going to struggle during the pandemic, provided that we are all following the stay-at-home policies. But the fear of catching COVID-19 and the restriction order should not keep people with serious non-COVID-19 symptoms from seeking medical care. Delaying care for medical emergencies can be life-threatening or prone to other severe complications. 

Telemedicine is replacing in-person care amid the pandemic. (Photo: ScienceSoft)

And this problem can be solved by telemedicine as told by health care executive Kerry Palakanis. "For people with chronic health conditions, we don't want them coming into the traditional health care environment and exposing themselves to COVID," she said.

The executive director for Connected Care at Intermountain Healthcare in Salt Lake City, Palakanis, stressed the benefits of remote medical care to patients with critical conditions that need regular follow-up visits and patients living in remote areas where hospitals are inconvenient to access during this time. 

On the other hand, experts have concerned the challenge of implementing the new digital approach due to the public perception of not having in-person meetings with a doctor.

Source: CNET

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 2,500 engineers.

Visit us at https://www.tmasolutions.com/

Read More

5 Steps To Make Chatbots More Intelligent With Contextual Intelligence

Chatbots need to have contextual awareness if they have to sufficiently resolve a query. Conversational UX relies on effective contextual intelligence to handle millions of queries over periods to create more meaningful relationships with customers. 

Designing a Contextual Chatbot

Embedding contextual analysis is an important first step from the beginning. Besides, designing a contextual chatbot requires a strategic plan about key characteristics and use-cases for the technology. 

Planning can be optimized by analyzing existing features & area and mapping out future requirements for specific use cases. Through this process, various technology integrations can be put in place to ensure that there is congruence. 

Added to that, a contextual chatbot requires an integrated approach, massive data lakes and the right analytics methodology to design and development. 

Training With the Right Data Sets

To make chatbots more contextually intelligent, you need to provide the right data sets. It can source the true meaning behind critical keywords to strengthen its neural network. This makes the context richer, especially in the case of customer-oriented chatbots.

The probability model needs the right type of data to adequately perform significant functions. The chatbot needs to understand real conversations to be able to derive real responses to future queries. A high-quality intent classification model needs to be designed keeping focused raw data at the center of the process.

Integrating the Right Technologies

Whether that’s open-source technologies or vendor-driven systems, you need to find the right integrated technologies. The contextual chatbot needs complex technology such as Tensorflow or Dialogflow to handle complex queries.

Chatbots must be able to store and retrieve important information related to the context being analyzed. Moreover, you can even timecode the interaction to extract information using for analysis. For example, you can understand the type of action that is being conveyed in a query or a sentence. Then it conveys the right response based on this action-oriented model. 

Applying NLP and Deep Learning

Traditional chatbots rely on a retrieval-based model that works within specified parameters. But the contextual chatbots require a more powerful NLP network and greater access to deep learning resources so that the system can learn key phrases to implement to create new chains of responses.

When chatbots are having thousands of simultaneous conversations, they automatically iterate on the best responses by using NLP. NLP helps to understand new information as it enters the systems and you can test out various responses

Sophisticated data mining tools are also required to ensure that there is a deeper context for every dialogue had. Through greater resource allocation and complex analytical models, the incoming data can be parsed and categorized effectively into segments that are run independently through the network. After that, nodes can act as connectors to ensure that there is a contextual response given to each query.

Differentiating between Sessions Context vs User Context

The chatbot needs to be complex enough to capture bigdata about the conversations as well as the customer’s profile for session context, which helps it to be more contextually intelligent and relevant for customers. 

When moving on from subject to subject, chatbots are contextually aware and create the most suitable responses on the context detected. As a result, this leads to the retention of the customer while engaging them in a more meaningful conversation.

In conclusion, to make chatbots become more intelligent, you need to analyze large data sets through a more complex model in real-time to understand the context. Chatbots also need constant training to enhance the ability to respond appropriately because each industry has unique requirements.

Source: DZone

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 2,500 engineers. Visit us at https://www.tmasolutions.com/

Read More

Identifying students who need help with AI enhancements

An artificial intelligence (AI) model is created to more effectively predict how students are learning through educational games. The improved model called multi-task learning utilizing AI training concepts can be applied to boost the advantages of instructional and learning results.

Multi-task learning is an approach in which a model is required to perform various tasks. For example, the model is applied to predict students' ability to correctly answer test questions and the task of the model is based on the questions and the overall score of the test.

The AI model identified common behaviors of students

In this study, 181 students who are the subjects of the research are examined and data mining by AI through how students play games and answer Question 1 in the test. Common patterns of students in answering right or wrong to Question 1 will be the background for AI ​​to determine a new student's way of answering Question 1. This function is performed for every question at the same time with the same gameplay but the different questions.

The results obtained from the model application are completely different. Relied on typical AI training methods, the researchers noticed that the multi-task model was about 10 percent more accurate than other models. Specifically, the model can send a notification to the teacher if the student needs further instruction through student participation in the gameplay. The model can also aid in-game features such as plot changes to help students clarify struggle issues.

In psychology, each question posed has a different value. With deep learning and machine learning approaches to AI, the researchers have the ability to take an interdisciplinary approach that combines this aspect of psychology. This also provides the opportunity for more complicated modeling techniques to be incorporated into educational software, adapting to the requirements of students in learning.

Source: Science Daily

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 2,500 engineers.

Visit us at https://www.tmasolutions.com/

Read More