How is cutting-edge technology changing the game?

Cutting-edge technologies are the latest and most innovative developments in computer science. The cutting-edge tools, solutions, and platforms are called game changers for a reason.

Probably everyone has heard about generative Artificial Intelligence or quantum computing. To create innovative solutions, software development projects utilise augmented reality technologies to a science-fiction level. These cutting-edge technologies are revolutionising the software development process and allowing businesses to develop faster, more efficient solutions.

Cutting-edge technologies are being used in a variety of applications, from medicine to customer service, and are having a lasting impact on the way humans interact with the world, changing our reality irretrievably.

Which technologies are considered cutting-edge?

The term “cutting-edge technology” refers to technological achievements, techniques, or devices, that employ the most current and advanced developments in the area of information technology. In order to be called “cutting edge”, technology must be current and innovative, representing the most recent advances.

And if you want to learn about other innovative technologies, take a peek here:

• AI implementation in business: how to do it successfully?
• How to build an effective data strategy?
• Generative design: how AI technology is transforming creation and innovation

The cutting-edge technologies are sometimes contrasted with the term “bleeding-edge technologies”.

While cutting edge technology is the latest and greatest, bleeding edge technology is even newer and more experimental. Due to its newness and experimental, untested nature, bleeding edges technology poses unreliability risks to users.

Some examples of bleeding-edge technologies will be: quantum computing, nanotechnology and brain-machine interfaces. The most cutting-edge technologies are: AI features enabling machine learning, generative AI, and low-code/no-code development.

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Machine Learning (ML) to enable AI features

Machine Learning (ML) powered by the advancement of Artificial Intelligence (AI) features is at the forefront of cutting-edge technology. At the heart of ML lies deep learning, a subset of ML that imitates the human brain’s neural networks. This allows AI systems to analyse vast amounts of data, recognise patterns, and make informed decisions.

From image and speech recognition to natural language processing, deep learning empowers AI to perform complex tasks with astounding accuracy. As a result of the innovative field of deep learning, ML makes remarkable breakthroughs in various business processes by mimicking the complexities of the human brain.

The emerging technology of AI features enabled by Machine Learning holds great promise for the future of software development industry. Industry-wide, the integration of ML into business processes is revolutionising business processes.

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Generative AI

Generative AI, a pinnacle of advanced software solutions, represents one of the best examples of state-of-the-art technology. Unlike traditional AI algorithms that focus on pattern recognition and predictions, generative AI employs machine learning algorithms to create outputs based on training data.

As a subset of Artificial Intelligence, generative AI uses algorithms and neural networks to generate new, novel content such as text, images, music, and even data patterns that may directly reflect human-produced content. By analysing patterns within extensive training data, Gen AI’s novel content closely resembles human creations.

Currently, there are two prominent generative AI models worth examining in greater detail:

1. Generative Adversarial Networks (GANs) are cutting-edge technologies capable of generating visual and multimedia artifacts based on both imagery and text input. To produce realistic and diverse outputs, GANs utilise a competitive framework involving a generator and a discriminator.
2. The Generative Pre-Trained (GPT) language model utilises information gathered from the Internet. The models can generate content for websites, press releases, and whitepapers. Using massive datasets to train their models, transformer-based models produce coherent and contextually relevant text.

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Low-code / No-code Development

Low-code/no-code development is emerging as a new cutting-edge technology that is revolutionising software creation. Without requiring any coding skills, using the drag and drop functionality, anyone can create powerful applications using these technologies.

There are several benefits to this approach, including:

• Speed: Applications that use low-code/no-code can be built much more quickly than those that use traditional coding methods.
• Accessibility: Low-code/no-code platforms allow non-technical users to build applications, which opens the development process to a broader audience.
• Agility: No-code/low-code platforms make it easy for businesses to make changes to applications, thus allowing them to be more responsive and agile.

The report “Gartner Forecasts Worldwide Low-Code Development Technologies Market to Grow 20% in 2023” predicts that by 2024, 80% of applications will be built using low-code/no-code platforms. This makes low-code/no-code development a cutting edge technology that is poised to change the way software is created.

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What are the benefits of using cutting-edge technologies in software development?

Cutting-edge technologies are increasingly used by software developers. In addition to offering increased efficiency and quality, these technologies provide access to new features, competitive advantages in the market, and the ability to attract potential clients and talent.

Let us examine the benefits of utilising cutting-edge technology in software development world in more detail.

Increased efficiency and quality

New cutting-edge technologies can significantly improve the efficiency and quality of software development. With these technologies, tasks can be automated, new tools and frameworks can be created, and new capabilities and features can be offered. This enables developers to produce better-quality software applications and be more productive.

Among the examples are:

• AI technologies used to automate software testing. Dev teams can then focus on other tasks, such as design and implementation. AI can also be used to identify and fix bugs in software, thereby improving code quality.
• The use of cloud computing. Developers can access powerful computing resources through cloud computing, reducing the need to buy expensive hardware and software for the development process.

Access to new features and possibilities

The ability to gain access to new features and possibilities plays critical role in utilising cutting-edge technologies in software development. Using these tools and frameworks, developers can maintain their position as innovators, utilising novel features and techniques to create superior software applications.

Continual integration of the latest technology enhances performance, scalability, and security, providing a competitive advantage in the rapidly evolving digital marketplace.

Innovative methodologies allow businesses to unleash their creative potential, create revolutionary products, and adapt quickly to changing market conditions.

Competitive advantage in the market

Cutting-edge technologies can provide significant competitive advantages in software development. Businesses can differentiate themselves and offer their customers differentiated solutions by staying ahead of the curve and using the latest technologies. Customer satisfaction, brand recognition, and market share can all be increased in this way.

Here are some examples of how cutting-edge technologies can give businesses a competitive advantage:

• Using cloud computing can improve scalability for businesses.
• Pricing, marketing, and product development can be made more effective through big data analytics.
• A number of tasks can be automated, customer service can be enhanced, and new products can be developed by using artificial intelligence.
• Chatbots developed by businesses using natural language processing can provide a more convenient and efficient customer experience than those not using this technology.

And if you are looking for other ways to gain technological advantages in the market, read also about:

• Data automation for business growth: everything you need to know
• How to conduct a successful UX audit in 5 steps?
• What is digital infrastructure and how can it help your business?

Attracting talent and potential customers

Top talent and potential customers can be attracted by the use of cutting-edge technologies in software development. A company that shows it is innovative and forward-thinking can attract the best and brightest employees who are eager to learn the latest technology.

Moreover, potential customers may be more inclined to choose a business that uses cutting-edge technology, as they perceive this as a sign of quality.

Cutting-edge technologies can attract talent and customers in the following ways:

• Open source technologies show potential employees and customers that the company is open and collaborative.
• An innovative business can demonstrate its creativity and innovation by using cutting-edge technology.

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What are the downsides of using cutting-edge technologies in software development?

There are many benefits to software development projects that can be achieved through the use of cutting-edge technology, but there are also some potential drawbacks.

Using cutting-edge technology can have some downsides, including:

• Lack of maturity and stability: it is often the case that new technologies are not as mature or stable as older, more established technologies. As a result, compatibility issues, bugs, and other difficulties may arise, which may delay or even derail the project.
• Limited community support: when problems arise, it may be difficult to locate help and support due to a smaller pool of developers who are familiar with new technologies.
• Higher costs: the cost of cutting-edge technologies can often be higher than the cost of older, more established technologies. As they are newer, there is less competition, which leads to a higher price.
• Increased risk: the use of cutting-edge technology can increase the likelihood of a project’s failure. New technologies are often untested, so there is a greater likelihood of something going wrong.

Experiencing problems and identifying solutions can result in unexpected costs and delays. Prior to using a technology for a project, it is important to thoroughly research and test it.

A successful outcome can be ensured by reducing the risk of failure.

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How could cutting-edge software solutions benefit your business?

Cutting-edge software solutions can help businesses achieve a number of key goals, including:

1. Increased market share: By staying ahead of the competition, businesses can gain a larger share of the market.
2. Improved profitability: By streamlining operations and reducing costs, businesses can improve their profitability.
3. Enhanced customer loyalty: By providing a better customer experience, businesses can attract and retain more customers.
4. Lower cost of development: By making it easier to build software without requiring specialized skills or knowledge, low-code/no-code solutions help businesses reduce their development costs.
5. Up-to-date technology: Cutting-edge software solutions are built with the latest technology, thus making it easier for businesses to maintain their software. 

If you’re looking for a way to boost your business, then cutting-edge software solutions are essential. Possibilities are endless. To give your business a competitive edge, cutting-edge software is a great place to start. Get in touch with our team of experts!

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Introduction

Generative AI and LLMs (large language models) have taken the world by storm in recent times.

Generative AI is a highly innovative field that enables machine learning algorithms to generate content, providing businesses with a wealth of opportunities to generate content, streamline their processes, reduce costs and enhance their operations.

Andrew Ng, a renowned computer scientist and Coursera founder, said that ‘Artificial intelligence is the new electricity’, and that not a single industry will escape the AI transformation that will take effect within the next few years.

Just as electricity and the birth of the internet transformed the world in past generations, Generative AI is poised to do the same. Therefore, making the best decision possible when it comes to incorporating Generative AI into businesses is crucial for staying ahead of the curve and remaining competitive.

But what could be achieved for companies who not only embrace Generative AI into their businesses but also go one step further by utilising it to drive real-world solutions? Enter Future Processing.

Future Processing – Generative AI products

At Future Processing, we use a number of Generative AI products. One that particularly stands out is Amazon Bedrock, an innovative tool offered by Amazon Web Services which offers an easy-to-use developer experience to work with a broad range of high-performing foundation models, like Claude 2 from Anthropic.

Using AWS and Claude 2, we are able to deliver artificial intelligence and machine learning solutions for businesses by providing expertise in predictive maintenance, recommendation engines, image analysis, NLP chatbot and sentiment analysis, and timeseries. We look at businesses’ case designs, work on data access and engineering, deliver a suitable model, monitor and manage the model, and then finally develop the full application.

By integrating the foundation model Claude 2 into our GenAI toolkit, we are able to create interactive PoCs of companies’ AI or ML products that verify the initial ideas. This allows us to make excellent, data-based decisions on our clients’ investments, before finally delivering a world-class product.

These products serve as the backbone for our transformative GenAI solution, which enables us to tackle complex data challenges head-on.

Why we turned to Generative AI

The Challenge

Our journey into Generative AI was driven by the needs of our clients. One of them had the issue of having to do lots of manual labour each year in order to feed his job search platform with data from their partners. This was a time-consuming, costly and inefficient process, so they asked us to create a digital product to automate this process. Traditionally, programming for this type of task would have been far too expensive (if possible at all). However, Generative AI opened the door to discovering a better solution.

It was for a good reason that we searched for a better solution to this issue – typically, our clients would need to create a new adaptor for these partner websites and adapt them in the case of any changes (e.g. structures, formatting, updates, and so on). This was time-consuming, costly and not an efficient way to operate. In order to avoid this issue, we came up with a general solution that would create the same output for every website from a variety of sources.

Traditional programming had always been a barrier to creating such a product due to the costs involved with building and maintaining an algorithm that would be required for such a versatile and changing environment. However, now with the aid of the more general capabilities of Generative AI, we have finally been able to bring this creation to life.

The Solution: Leveraging GenAI and Amazon Bedrock

Thanks to the help of Generative AI, we were able to build a solution that proves it is possible to solve this issue in a straightforward and efficient manner.

We created a simple web application that allows users to input the URL of a job offer they want to migrate to the new partner system. After pasting the direct web link, we simply press the “Process” button to begin.

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Once processed, the AI scrapes the webpage in the background, using Amazon Bedrock Model to extract the necessary information. The output is presented in a structured JSON format that is retrieved from the screen.

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A new window then opens with the completed form already filled out. This is done through the use of an RPA solution (Robotic Process Automation).

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By using this model, we were able to present a successful proof of concept that demonstrates that the desired state can be delivered in just a few days – much faster than anything that could have been achieved without the use of Generative AI. This model has been completed and is now ready to be fully rolled out for use in production. The best part? It took just a few weeks of engineering work!

Expected Outcomes and Impact

Our GenAI solution has achieved remarkable results. It has not only automated expensive tasks that were previously performed by individuals. This has significantly streamlined the data-gathering processes for our clients.

By leveraging Generative AI tools, we’ve demonstrated that data aggregation from various sources can be standardised, saving time, reducing operational costs and boosting efficiency.

What our experts say

Krzysztof Szabelski, Head of Technology at Future Processing, sums our paradigm-shifting solution up very well:

Future Processing – our story

Founded with a mission to push the boundaries of technology, Future Processing has been at the forefront of innovation for over two decades. As cutting-edge technology consultants, software engineers and delivery partners, we are at the very forefront of this AI revolution and well-poised to assist businesses with their AI and ML needs. Our story is one of constant evolution, where we’ve harnessed the power of Generative AI to create game-changing products that save our clients both time and money.

Our journey has been marked by a relentless pursuit of excellence, and today we stand as a trusted technology partner who has successfully delivered business solutions to numerous companies around the world. With a strong commitment to delivering tangible business value, we’ve consistently pushed the envelope, driving innovation through technology.

Looking to the future

As we continue to refine our GenAI solution, the future is bright at Future Processing. Our huge success in the case study herein illustrates the transformative power of Generative AI. It underscores how Generative AI, backed by AWS, Amazon Bedrock and Claude 2, is poised to redefine the way businesses handle data. It’s a reminder that innovation isn’t a one-time event but a continuous journey. Embracing technology and adapting it to meet real-world needs is the key to staying ahead in the digital age.

We are firmly committed to exploring new possibilities and innovative applications of this technology (and many others), all while delivering exceptional value to our clients and the industry as a whole.

To learn more about our GenAI solution and our AWS partnership, visit other articles on our blog, explore our AI and ML services, and get in touch to discover the power of our AWS-powered cloud services.

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Native, hybrid and web apps represent distinct categories of applications, each characterised by its unique development approach and functionality.

• Web Apps: These are essentially websites that look and feel like apps. Users access them through web browsers on either a desktop or mobile device without needing to download them from an app store. They’re convenient because they don’t take up space on your device.

• Native Apps: Developed for a specific platform, like iOS or Android, native apps are downloaded from app stores. They’re designed to work smoothly with your device’s hardware and software, offering fast performance and a high-quality user experience.

• Hybrid Apps: A mix of web and native apps that can be installed on your device but still run partly through a web browser. They’re like web apps but wrapped in a native app shell, allowing them to work across multiple platforms while being written just once.

Why are there so many different types of applications?

The variety of apps available today is mainly due to different factors like user needs, technology, and cost.

For example, native apps are great for using a device’s full features, like the camera, offering a rich experience. Web apps, however, are more about easy access from any device with a browser, perfect for those who value convenience.

The development process itself also influences the variety of apps. Creating native apps for different platforms like iOS and Android can be costly and time-consuming, often requiring separate development for each system. Web and hybrid apps, however, present more economical alternatives.

Another key point is internet connectivity. Web apps need it to function and stay updated, while native apps can often work offline, which is useful where internet access is spotty.

Lastly, the tech world is always changing, with new devices and user wants. This drives the creation of different kinds of apps, keeping up with the latest trends and technology.

So, the range of available applications keeps growing and changing to match the evolving digital landscape.

Differences between web apps vs. native apps

When comparing native and web apps, it’s important to understand that they cater to different needs and technical requirements.

Here’s a breakdown of their differences:

Development:

• Web applications are built using standard web technologies like HTML, CSS, and JavaScript and are accessed through a web browser.

• Native applications are developed using platform-specific languages (Swift or Objective-C for iOS, Java or Kotlin for Android) and tools tailored specifically for the platform.

Performance:

• Web applications often have slower performance and require more data transfer compared to native apps, as they depend on the web browser and internet connection.

• Native apps are optimised for specific platforms, offering better performance and detailed integration, even for heavy graphics.

Device Features:

• Web applications face challenges in accessing external device features like fingerprint readers and have limited integration capabilities.

• Native applications can fully leverage the platform’s specific features and technologies, providing a more robust experience.

Distribution:

• Web applications are not distributed through app stores but are accessible universally through a web browser, while native applications are distributed through platform-specific app stores and must adhere to their guidelines.

Cost:

• Developing web applications is generally quicker and less expensive, with no need for frequent updates through an app store.

Differences between native apps vs. hybrid apps

When you face the choice of native vs hybrid app, it’s essential to understand their distinct characteristics.

Here is our comparison:

Development approach:

• Native apps are developed specifically for one platform using platform-specific languages and tools, like iOS or Android.

• Hybrid apps combine web technologies (like HTML, CSS, JavaScript) with native elements. They are built on a single codebase, allowing them to function across multiple platforms.

Advantages:

• Hybrid apps are quicker and less expensive to develop since they use a single codebase. They can be installed like native apps but are easier to manage due to their singular codebase. They are also distributed through app stores and can run offline.

Disadvantages:

• Hybrid mobile apps may have reduced performance compared to native apps. Achieving a native-like look and feel might require significant platform-specific modifications, increasing costs.

Distribution

• Both native and hybrid apps are distributed through app stores.

Developer Expertise:

• Developing native apps requires knowledge of platform-specific languages and tools.

• Hybrid app development might be more accessible to developers with a background in web or backend languages.

Differences between hybrid apps vs. progressive web apps

Progressive web apps are changing how web apps are built. They work better and offer a smoother user experience, almost like native apps.

How do they compare to hybrid apps?

Development:

• Hybrid apps combine web technologies (HTML, CSS, JavaScript) with native app features, while Progressive Web Apps (PWAs) are websites with an app-like experience.

Performance:

• Hybrid apps typically offer better performance and device feature access than PWAs, which depend more on browser capabilities and internet connection.

Device Features

• Hybrid apps have broader access to device functionalities like camera and GPS, whereas PWAs have limited access, though this is improving.

Distribution

• Hybrid apps are distributed through app stores and must comply with their rules, while PWAs are accessible via a URL and bypass app store restrictions.

Cost

• Developing and maintaining hybrid apps can be costlier than PWAs, which use a single codebase and standard web technologies.

When to use web app, native app or hybrid app?

Considering the front-end, we need to remember that each IT system is based on a particular way of interacting with the user. Native, web and hybrid solutions have their own benefits and challenges, but finally, reaching the best ROI is pivotal.

Choosing an option that fits the needs, it is best to answer these questions:

• What goals (UX and business) do we want to reach by developing software?

• Who will be using the app, and what functionalities will be crucial?

• What benefits will the application bring to its users?

• What possibilities does the budget give us?

When creating native, hybrid or web apps, consider long-term maintenance and scalability. Web apps are easier to update, while native apps require more structured maintenance. Hybrid apps are flexible but may have performance issues.

By carefully assessing these factors, choose the best approach for your business and users.

Open or closed app?

If we want to create an application accessible to mass users, UX is vital.

The popular solution here is to create a dedicated web application for desktop and a separate native mobile platform for iOS and Android. In the case of an open app, a native application would be the best choice.

If the costs are too high, a cross-platform solution is the one to consider as it also should give satisfying results.

In closed apps (enterprise applications), functionality and business values ​​are far more important than UX standards so that hybrid solutions may be the best option here.

However, some enterprise applications need to deal with very complex forms and display methods that simply cannot fit mobile screens.

We can write one main web and mobile apps containing only the most necessary data and functionalities. For example, in the insurance industry, web applications can provide full support for office workers to process claims on desktops.

At the same time, insurance agents use different mobile apps only for tasks completed outside the office.

Find out more about IT solutions tailored to Insurers’ needs:

• Data-driven insurance: exploring the latest trends

• Insurance digital transformation: (r)evolution in the industry

• The role of insurance in emerging digital ecosystems

The future of App Development: emerging trends

The app development is constantly evolving, driven by the need for innovation, enhanced user experiences, or the cutting-edge technology in software development.

Here are the exciting trends to follow in the near future:

• Artificial Intelligence and Machine Learning solutions: AI and ML are making apps smarter. They help create personalised user experiences, predict what users might like, and automate tasks.

• 5G Technology: The introduction of 5G will change app development. It means faster and more reliable internet, allowing developers to create more complex and engaging apps.

• Augmented Reality (AR) and Virtual Reality (VR): AR and VR are expanding beyond gaming. They’re being used in different types of apps to provide unique user experiences.

• Blockchain Solutions: Blockchain is gaining attention for making apps more secure and transparent. It’s especially useful for apps that need high security and trust.

• Internet of Things (IoT) Applications: With IoT, apps can connect with various devices, leading to innovative features and smarter homes and workplaces.

• No-Code and Low-Code App Development: No-code and low-code platforms make app development easier and faster. They allow more people to create apps without needing deep programming knowledge.

How can Future Processing help you with application development?

To make the right choice, it’s vital to understand the options. The more native and adapted to the platform the application is, the better its quality, UX, performance and rating are.

Notably, the cost is also higher. The more general the solution is, the lower the prices are, and the greater the compromises and possible limitations are. The whole spectrum of hybrid solutions offers a wide range of opportunities and helps reach a compromise.

Before you decide on any of the above options, define your requirements, analyse possibilities, and make sure you get the one you need. Contact our software experts, and let’s talk about creating the best-fitted app for your business.

With its extensive experience in software consulting and development, Future Processing can guide you through this complex process, ensuring that you choose a tailor-made solution that aligns with your business needs.

Keen to know more? Before jumping into the extensive portfolio of available solutions, let us elaborate more on AI, Machine Learning and Deep Learning technology.

Understanding the power of AWS AI services

Artificial intelligence is a broad concept. Overall, it aims to mimic human decision-making processes and perform complex tasks in a more human way than ever before.

This is understood as, inter alia, the ability to adapt independently to changing conditions, and also includes machines that can perform tasks characteristic of human intelligence and do it faster and more efficiently than humans.

It is also worth noting that this sector is a much broader concept than machine learning. Behavioural algorithms, virtual agents, or autonomously powered, self-propelled vehicles with predictive capabilities – these are but a few of examples of the use of artificial intelligence today.

The role of Machine Learning in AWS

Machine learning is a technique in the field of computer science and statistical modeling that allows a computer application based on independent analysis – without the need to program it – to predict the result or make a decision.

This technology is closely related to data analytics, data mining, and data science engineering. Both machine learning and data mining use mathematical algorithms to explore data and search for patterns. Machine learning uses algorithms to detect patterns in data sets and adjusts program performance accordingly.

Predictive analytics services, regardless of all big data challenges, help developers and data researchers use machine learning in new ways.

Advanced Deep Learning technologies

Deep learning is one of the varieties of artificial intelligence (AI), a subcategory of machine learning – a technique involving the creation of neural networks, the main task of which is to improve the techniques of computer vision, voice recognition and natural language processing.

Simply put, deep learning process can be seen as a way to automate predictive analytics. Deep learning applications cover many types of big data analytical applications, in particular those focused on natural language processing (NLP), translation of foreign languages, medical diagnostics, stock transactions, cybersecurity services and image recognition.

Read more about the different applications of AI in business:

Things Artificial Intelligence can do for your business

The power of Artificial Intelligence in healthcare – best examples

Artificial Intelligence in FinTech: maximise benefits by innovating responsibly

Predicting stock prices and market shifts using AI

Selection of AI-based services offered by Amazon

With all this theory in mind, let’s now look at the selection of AI-based services offered by Amazon.

Amazon Lex

Amazon Lex is an AWS service that allows you to build conversational interfaces into text and speech applications. Due to the use of automatic speech recognition and its conversion into the text, as well as natural language understanding, it allows the user to experience a real interaction.

It is widely used in the implementation of chatbots that improve communication and customer service, it also allows you to automate simple tasks. It does not require infrastructure management.

In combination with other AWS services such as Lambda and Polly, it can handle various business scenarios.

Amazon Sagemaker

Amazon SageMaker is dedicated primarily to programmers and data scientists who want to build, train and implement machine learning models. Amazon SageMaker algorithms adopt a stream computing model that can process an infinite amount of data.

The algorithm goes through the data set only once and then takes a persistent memory trace. This solution excludes storing, shuffling, and multiple reading of data, as well as random access to individual records.

Besides, streaming algorithms natively retrieve data from short-lived sources, while traditional machine learning algorithms typically retrieve data from persistent sources such as local disks.

As a result, a training task that takes ten hours on a single computer can be run on ten computers and be completed within an hour. You can reduce learning time even further by replacing your device with one with GPU support.

Amazon Rekognition

Amazon Rekognition allows advanced image processing, which in the past would require to build quite a sizeable database and implement certain algorithms. Today, the user can write and run an application in less than an hour, and the complicated algorithms come down to calling one AWS SDK function.

Rekognition enables the analysis of static images and video sequences (also streaming). The service can identify objects, people, text, scene and activity depicted in the image. It’s also great for filtering out inappropriate content posted by users.

In combination with AWS Lambda (Function as a Service), API Gateway and S3, we can build an advanced application without running any virtual machine, all in the spirit of event-driven and serverless programming.

Amazon Personalize

Amazon Personalize enables you to increase customer engagement by delivering personalised product and content recommendations, as well as targeted marketing promotions. Amazon Personalize uses machine learning (ML) to create higher-quality recommendations for your sites and applications.

You can get started with no prior ML experience by using simple APIs to easily create advanced personalisation features with just a few clicks. All your data is encrypted to maintain a high level of privacy and security in the cloud and is only used to make recommendations to users.

Amazon Translate

Amazon Translate is a neural machine translation service that provides fast, high-quality and affordable language translation. Neural Machine Translation is a form of language translation automation that uses deep learning models to provide a more accurate and natural-sounding translation than traditional statistical and rule-based translation algorithms.

The translation service is trained on a wide variety of content in a variety of use cases and domains to perform well on many types of content. Its asynchronous batching feature allows you to translate a large collection of text or HTML documents with a single API call.

Amazon Fraud Detector

Amazon Fraud Detector is a fully managed service that uses ML and Amazon’s years of fraud detection experience to identify potential fraudulent activities so you can spot online scams faster. Amazon Fraud Detector automates the time-consuming and costly steps of creating, training, and deploying an ML model for fraud detection, making it easier to use this technology.

Amazon Fraud Detector adapts each model it creates to the dataset, so the accuracy of the models is higher than in current universal ML solutions. And because you only pay for what you use, you avoid large upfront costs.

Amazon Extract

Amazon Extract automatically extracts text and data from scanned documents. However, the solution goes beyond a simple OCR and also identifies field content in forms and information stored in tables.

This allows Amazon Textract to read virtually any type of document and accurately extract text and data without any manual steps or custom code.

Amazon Kendra

Amazon Kendra is an easy-to-use search engine service based on machine learning. It is dedicated to organisations with a large document database, in which it is difficult to find something and the implemented search methods based on specific solutions do not allow for returning valuable answers.

Real-world applications of AWS AI and ML service

Amazon Web ML and AI services can be applied to various real-world scenarios.

Some of examples include:

1. Recommendation Systems using Amazon Personalize. This technology is widely used in e-commerce platforms, streaming services and content delivery systems to provide personalised recommendations to users based on their preferences and behaviours.

2. Natural Language Processing (NLP) using Amazon Comprehend to extract insights and relationships from text data. NLP techniques can be applied in sentiment analysis, content categorisation, entity recognition and language detection for applications such as social media monitoring and customer feedback analysis.

3. Chatbots and Virtual Assistants: Amazon Lex and Amazon Polly can be used to build chatbots and virtual assistants. These services find applications in customer support, interactive applications and accessibility tools.

4. Image and Video Analysis using Amazon Rekognition. This service is used in various industries including security, content moderation, retail and entertainment.

5. Anomaly Detection: Amazon Lookout for Metrics uses machine learning to automatically detect anomalies in business metrics and time-series data. This is particularly useful for detecting anomalies in operational data, helping businesses identify issues and take corrective actions.

6. Predictive Analytics with Amazon Forecast, used in demand forecasting, inventory planning, resource allocation, and other applications that require predicting future trends based on historical data.

7. Healthcare Applications: Amazon Comprehend Medical can extract medical information from unstructured text, making it useful for medical research, coding medical records, and clinical decision support.

8. Financial Services: Amazon Fraud Detector uses machine learning to identify potentially fraudulent activities in real time. This is valuable for financial institutions and e-commerce platforms to prevent fraudulent transactions.

Is it the right moment to invest in AWS ML and AI-based solutions?

McKinsey analysts expect that in 2025 the market for AI-related hardware and software solutions will be worth as much as $130 billion.

According to Werner Vogels, chief technology officer and vice president of Amazon in charge of driving technology innovation within the company, now is the best time to develop intelligent applications. It is due to 3 factors.

First, companies collect more and more data, including much from the physical world (e.g. GPS locations).

Second, computers are now efficient enough.

Third, it is already possible to train even trillions of algorithms simultaneously, which greatly speeds up the learning process.

This allows for more research, which in turn means that the critical mass in terms of knowledge about artificial intelligence is exceeded.

As a result, work on new algorithms and architectures has been significantly accelerated, enabling faster and more efficient digital transformation.

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Embrace the cloud to support your strategy, accelerate your business and ensure data security.

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To answer that question, we listed all advantages and concerns related to the topic. Afterwards, we broke down the entire process into smaller parts, so that you can make sure your organisation is ready for the change.

When is the right time to migrate to the cloud?

Determining the right time to migrate to the cloud depends on several factors specific to your organisation. Here are some considerations to help you assess whether it’s the right moment for your business to do so:

1. Business Needs and Objectives

   Evaluate your current business needs and long-term objectives. If you have specific goals such as scalability, cost optimisation, agility, or global reach, migrating to the cloud may be beneficial. Assess how cloud services align with your business strategy and if they can help you achieve your goals more effectively than traditional on-premises solutions.

2. Aging Infrastructure or Technology

   If your existing infrastructure or technology is becoming outdated or difficult to maintain, migrating to the cloud can provide an opportunity to modernise your IT environment. Cloud services offer access to the latest technologies, hardware, and software, eliminating the need for costly hardware upgrades and reducing maintenance efforts.

3. Cost Considerations

   Evaluate your IT budget and cost structure. Moving to the cloud can offer cost advantages such as reduced upfront capital expenses, pay-as-you-go pricing models, and economies of scale. Assess whether the potential cost savings, increased operational efficiency, and improved resource utilisation outweigh the cloud migration costs and ongoing cloud-based service expenses.

4. Scalability and Flexibility

   Consider your organisation’s need for scalability and flexibility. If you experience seasonal spikes in demand, require rapid resource provisioning, or anticipate significant growth, the cloud can offer on-demand scalability and elasticity, allowing you to scale resources up or down as needed.

5. Security and Compliance Requirements

   Assess your security and compliance needs. Cloud service providers invest heavily in security measures and often offer robust security features and compliance certifications. If you have specific security requirements or struggle to meet compliance standards with your current infrastructure, migrating to a cloud environment with built-in security controls can enhance your overall security posture.

6. Data Accessibility and Collaboration

   Consider the importance of data accessibility, collaboration, and remote work capabilities for your organisation. Cloud services enable easy access to data and applications from anywhere, facilitating collaboration among geographically dispersed teams and supporting remote work arrangements.

7. IT Resource and Skillset

   Evaluate your organisation’s IT resources and skill sets. Migrating to the cloud may require specialised knowledge and expertise to plan, execute, and manage the migration process. Assess whether your internal IT team has the necessary skills or if you need to find a cloud service provider or seek external assistance to ensure a smooth migration.

8. Industry Trends and Competitiveness

   Consider industry trends and competitive factors. If your competitors are adopting cloud technologies and gaining a competitive edge through increased agility, innovation, or cost savings, it may be advantageous for your organisation to follow suit.

You could take a look at companies that migrated to the cloud to verify your thoughts, but ultimately, the decision to migrate to the cloud should be based on a careful analysis of your company’s unique needs, objectives, and constraints.

It’s important to conduct a thorough assessment, develop a well-defined cloud migration strategy, and consider the potential benefits, risks, and challenges associated with cloud adoption.

Types of cloud migration strategies

When planning a cloud migration, organisations can choose from various strategies based on their specific needs, priorities, and the nature of their applications and data.

Here are some common types of cloud migration strategies:

Lift and Shift Strategy (also known as Rehosting)

The lift-and-shift is a migration strategy that relies on moving data and applications from a physical location to cloud-based virtual machines. This approach is popular, largely because of its relative speed and smoothness. In most cases, workloads are transferred to the IaaS cloud unchanged.

Thus, the IT operations management tools previously used in the data centre are implemented in a largely unmodified cloud environment. Native cloud functionalities are not used to a large extent or at all.

The lift-and-shift approach enables the fastest migration of solutions to the cloud and is a good solution for disaster recovery operations. It allows you to forget about problems with managing your own server room or damage to e.g. disks in the server.

Lift-Tinker-and-Shift Strategy (Also Known As Refactor Or Replatform)

Re-platform, also known as lift, tinker, and shift – is a strategy that also does not allow any changes to the basic information architecture.

However, contrary to the “lift and shift” strategy, we have one additional element here – “tinker”, which translates to the possibility of making small optimisations in order to achieve measurable benefits.

The indubitable advantage of this strategy is the minimisation of the costs and the level of customer involvement.

Most often (but not always), it is regarded as an ad hoc solution aimed at bringing a quick, noticeable benefit and is used when the most important factor determining the migration method is time. It is the so-called “golden mean” between “re-host” and “re-factor” solutions.

Repurchase Strategy

Repurchasing involves replacing existing applications with software-as-a-service (SaaS) solutions.

Rather than migrating and managing applications in the cloud, organisations adopt cloud-based applications offered by third-party vendors. This strategy reduces the need for application management and allows organisations to focus on their core business activities.

Retire Strategy

Retire strategy refers to the decision to decommission or retire certain applications, services, or infrastructure components during the cloud migration process. Organisations may identify legacy systems, redundant applications, or outdated infrastructure that are no longer necessary or cost-effective to maintain.

Rather than migrating these assets to the cloud, the retire strategy involves phasing them out or replacing them with more modern and efficient alternatives.

Retain Strategy

The retaining strategy involves keeping some applications and data on-premises while selectively migrating others to the cloud.

This approach is often used when certain applications or data cannot be easily migrated due to technical, regulatory, or compliance reasons. It allows organisations to maintain a hybrid or multi-cloud environment, leveraging both on-premises infrastructure and cloud services.

Relocating Strategy

The relocation cloud migration strategy involves moving applications, services, or data from one cloud provider or cloud region to another. This strategy is typically employed when organisations want to take advantage of different cloud providers, achieve better performance, comply with data residency requirements, or optimise costs.

The relocation cloud migration strategy requires careful planning, coordination, and testing to minimise any disruptions or potential impact on users or business operations. Organisations should thoroughly assess the costs, benefits, and risks associated with the relocation and develop a detailed migration plan to ensure a smooth transition.

Reprovision From Scratch Strategy

The re-provision from scratch cloud migration strategy, also known as the re-architecting or rebuild strategy, involves rebuilding applications and infrastructure components from scratch in the target cloud environment. This approach allows organisations to take full advantage of cloud-native capabilities, scalability, and efficiency.

The re-provision from scratch strategy requires a significant investment of time, resources, and expertise.

However, it allows organisations to fully leverage the benefits of cloud-native architectures and technologies. It provides flexibility, scalability, and improved agility, enabling organizations to effectively innovate and respond to changing business needs.

Cold Migration Strategy

The cold migration strategy is an approach where applications and infrastructure are moved from on-premises or existing environments to the cloud without making significant changes to the architecture or code. It involves transferring the applications and data “as-is” to the target cloud environment.

The cold migration strategy offers a relatively quick and straightforward migration path. It allows organisations to benefit from the scalability and flexibility of the cloud without making significant changes to their applications or infrastructure.

However, it may not fully leverage the cloud-native capabilities and may require additional optimisation efforts post-migration to maximise the benefits of the cloud environment.

Live Migration Strategy

Live migration, also known as live cutover or live migration with minimal downtime, is a cloud migration strategy that involves moving applications, services, or data from one environment to another while minimising or eliminating disruptions to ongoing operations. This strategy aims to ensure continuous availability and a seamless transition for users.

The live migration strategy requires careful planning, coordination, and technical expertise to ensure a seamless transition without disrupting ongoing operations. It often involves using advanced cloud migration tools, load balancers, and replication mechanisms to facilitate the live migration process.

The goal is to minimise user impact, maintain data consistency, and ensure business continuity throughout the migration journey.

5 steps to successful cloud migration

The process of migrating to the cloud requires careful planning and execution to ensure a smooth transition. Here are the essential steps to guide you through a successful migration.

Step 1. Set Up Your Business Goals And Requirements For The Cloud Migration

You have to know why you’re doing this and what you expect from your new solution. Improve system availability or business agility through deployment frequency, boost your scalability and collaborate more productively. Write everything down and build the requirements of all potential stakeholders in your organisation.

And if you need any help with shaping your cloud migration vision and strategy, you can always seek assistance from external experts.

Step 2. Build A Migration Team

You cannot undertake an extensive cloud migration with a bunch of random people; you need to engage professionals with certain areas of expertise, for example:

• a solutions architect – an experienced specialist who builds and maintains the solution architecture,

• a Dev-Ops engineer with expertise in cloud systems – responsible for making collaboration more efficient,

• security and compliance expert – responsible for managing access to your cloud-based resources and meeting all security requirements, as well as any government privacy regulations.

Step 3. Decide What Kind Of Cloud Services You Want To Use

SELECT A SERVICE MODEL

• SaaS (Software as a Service) – this kind of platform manages everything for you: from apps and runtime, down to storage and networking.

• PaaS (Platform as a Service) – these platforms provide a framework for delivering and managing customised applications, and they also take care of some other things (like storage and virtualisation).

• IaaS (Infrastructure as a Service) – platforms like this are the most flexible: you can manage almost everything besides actual hardware, although it requires a lot of effort to maintain. Should be considered only when PaaS or SaaS is too restricted for your case.

This is just a general overview of cloud service models – your migration team will be able to provide you with much more information, and help you select the best fit based on your requirements.

CHOOSE A SOLUTION TYPE

• public cloud – infrastructure is delivered to all organisations via the Internet; this is the most scalable option, however, it doesn’t offer the best security,

• private cloud – dedicated exclusively to your organisation, so you can control your entire system, including full privacy options, however you lose on scalability and take more maintenance costs inhouse,

• hybrid cloud – combines public and private solutions, so you can choose to control more sensitive data in a private cloud and also scale with ease via a public cloud.

• multi cloud – means using multiple cloud service providers rather than relying on a single cloud provider.

You can read more about them in our article: “Public Cloud vs Private Cloud vs Hybrid Cloud: What are the differences?”

SELECT YOUR LEVEL OF INTEGRATION

• deep – making significant modifications to the application, so you can take full advantage of your new cloud solution,

• shallow – making minimal or zero changes to the application, but do not expect to use all of the cloud-based features.

CHOOSE A CLOUD PROVIDER OR PROVIDERS

There are plenty of available options, where most popular are AWS and Microsoft Azure. There are plenty of available options, where most popular are AWS and Microsoft Azure. You can bet on a single cloud provider or decide on multi-cloud solutions – depending on your requirements.

We strongly recommend you to take a look at Cloud Services Comparison: their characteristic and main differences. 

Step 4. Create A Plan/Roadmap

Don’t just grope around in the dark – you need to have your migration team prepare a solid plan! This should include:

• setting up migration priorities – so that the most crucial things have first priority in the cloud migration process,

• establishing milestones – in order to monitor progress and keep track of the pace and efficiency of your work,

• preparing a schedule – in order to have a general idea of the project timeline; this will also help you estimate costs,

• determining KPIs – so you know if the results of the cloud migrations meet your expectations.

Step 5. Begin The Cloud Migration: Monitor, Test And Adjust

Proceed with your cloud migration and follow your plan, but don’t be too conservative about it. You need to keep your finger on the pulse, monitor the situation and test your assumptions, as well as your chosen options and features. This will allow you to modify your plan, whenever needed, and make adjustments to the selected cloud solution accordingly.

Benefits of cloud migration strategy

A vital part of modernising your existing software infrastructure consists of moving everything to the cloud. And if you decide to move forward with your digital transformation, adopting cloud technology is definitely a must, and the benefits that this kind of platform provides are impressive:

Lower Costs

In the cloud, you can store all the databases, programs and applications that you use every day in your organisation. How much you pay depends entirely on you and your company’s needs. The cloud is fully scalable, so you only use the server space you need and thus pay only for the resources used.

Additionally, when you decide to migrate to the cloud, you do not have to be concerned about purchasing and maintaining the infrastructure, servers, hardware, updates, and software. For some workloads, cloud is definitely a much more cost-efficient option.

Availability

The cloud model allows users to work anywhere, anytime. All you need is Internet access so that each employee can check changes, operations and processes in the organisation on an ongoing basis. Entrepreneurs gain full control, flexibility and convenience of work.

Scalability

Cloud-based solutions guarantee great scalability, enormous performance and a huge data storage container. The cloud offers users scalability that is combined with the ability to allocate resources with flexibility when there is an increased demand for them. In the case of the standard model – desktop servers – it is not possible to cope with the sharp increases in demand.

Increased Efficiency

With cloud computing, you can enjoy virtually unlimited performance which, until now, has not been available to you. Even the most complex workstations are not able to provide your company with comparable resources.

Increased Security

The data stored in the cloud is safer. Cloud solutions not only protect information from falling into the wrong hands but also provide a lot of opportunities to limit access to it. An additional advantage is the fact that in the event of a possible deletion of data, it can be easily restored.

Likewise, if a computer that contains key data is stolen, it can be remotely wiped. Backups are performed automatically, which means you do not have to remember about it, as in the case of the traditional model.

Additional Support

Companies that offer cloud services usually have an additional department that not only watches over your security, but also tackles the threats.

Very often, such companies also offer access to the help desk department and support of specialists even 24 hours a day, which is extremely important, especially for small companies, which can very rarely afford additional employment of IT specialists who will constantly watch over cloud security.

Common concerns and fears regarding cloud migration process

Addressing common fears and concerns related to cloud migration is essential to ensure that businesses can embrace the cloud’s benefits while mitigating potential risks and challenges. With thorough planning, proper research, and expert guidance, however, companies can confidently migrate to the cloud and unlock its full potential for growth and innovation.

Loss of Data Control

Companies are often concerned about migrating business systems, applications and data to cloud environments for fear of losing control over them. There is a belief that, in the case of an environment based on in-house servers, the company has full control over data location, security and availability of resources.

Moving your data to the cloud does not mean you lose your data. Quite the contrary – it gives you more control over it, and you can access it anytime from anywhere.

Issues With Possible Vendor Lock-In

There is always a risk of a supplier going out of business or changing the terms of service in our region. In the mind of every IT manager, there are difficulties (organisational, personal, technological, etc.) and costs related to a possible transfer to a new supplier. Such a change can be even more costly than the original on-premise cloud migration.

Problem With Choosing The Type Of Service And Migration Model

Before starting the project, there are many things and common problems in cloud implementation to consider. Should one opt for a public or private cloud? Or maybe it is better to use an environment based on hybrid solutions?

The latter, i.e. the combination of public and private clouds, has become increasingly popular recently. They make it possible to store some data locally on the server and some in the cloud. Before migration, you should also consider the model of transferring the application or the entire infrastructure to the cloud.

Costs Of Migrating And Maintaining The Cloud Environment

How much do you have to invest and after what time will the investment pay off? Can the already existing applications in the company be transferred to the cloud environment and will such an application work without interruption?

It is difficult to answer these questions on your own without previous experience with cloud services. Here, too, a supplier who has carried out many implementations, will be able to offer a cost estimate and facilitate the decision-making process.

How to make sure cloud migration will be a success?

This transformative journey comes with its challenges, necessitating a strategic approach to ensure its success. To accomplish a seamless transition to the cloud, organizations must assess current needs, existing resources and meticulously plan their strategy.

Know Your Motivation

The most important issue that needs to be addressed in the first place is to establish motivation. By answering the question of why you are considering a step into the clouds, you will be able to narrow down all migration options. Do you simply want to solve a pressing business problem quickly? If so, maybe the best solution would be to look at ready-made applications offered within the subscription model (SaaS)?

This increasingly common licensing model allows not only to reduce the time and costs of implementation significantly but also to ensure appropriate service conditions under the SLA provided. As a subscription, you can now purchase not only basic office software but also CRM, ERP systems and dedicated industry solutions.

Another popular reason to consider migrating to the cloud is to increase your existing systems’ reliability, availability, or scalability. This is of particular importance today, as it turns out that many of the existing environments are unprepared for new usage, such as a significantly increased number of remote workers requiring interaction with the central system.

Reduction of costs on hardware and software solutions can also act as a great argument for starting a migration. A well-used cloud can reduce expenses. However, you should be aware of the specific nature of cloud service price lists, which for many novice users may turn out to be a significant entry barrier.

Analyse

Find and evaluate existing applications, databases, and infrastructures. Gain insight into dependencies with automated cloud migration tools and take an inventory of infrastructure, and assess local environments.

Calculate the Total Cost of Ownership to get the business case for migration. Assess the potential cost savings of migrating to the cloud by calculating and comparing the Total Cost of Ownership with the cost of a comparable on-premises deployment.

Find A Trusted Partner

Migration to the cloud (especially in the first stage) is not easy and cooperating with a qualified, experienced partner is often necessary. A partner is a company that operates on behalf of a cloud service provider, such as Amazon Web Services or Azure.

The partner knows the mechanisms of migration, knows the solution to which the migration will be carried out, can plan the process, carry it out, and is aware of potential threats. It prepares the organisation for introducing changes not only in terms of technology but also helps to revise processes or adjust the budget to a new solution.

Additionally, it supports the organisation in the subsequent operation of the infrastructure and solving possible problems. If you are wondering how to choose the best IT partner to conduct your migration – feel free to use our ready-made RFI template for Cloud Services.

Conclusions

In order to conduct a successful cloud migration, you need to have a solid cloud computing strategy that takes into account the nature of your products/services and your business needs and goals. Also, this is not something that can be handled without experienced experts who can plan, execute and verify the migration process. Remember, this is a significant step in creating your digital transformation journey! 

So, if you need any help with your cloud migration or simply want to know more about how the cloud can help your business develop – feel free to contact us! 

Adapt your business to the changing world!

Embrace the cloud to support your strategy, accelerate your business and ensure data security.

Let's join forces!