Introduction to AI Part 2: Next-Level AI Terms Glossary 

2023 was a breakout year for Generative AI, and it has proven beyond all doubt that expanding your vocabulary with common AI terms is necessary now. Artificial intelligence technology is fast becoming an indispensable part of our lives on every level. Therefore, you must understand at least the basics of how it works and what it can do.

Devtorium will continue our series of articles about AI, its capabilities, and developments that are revolutionizing multiple industries. Today, we will expand our AI terms glossary with some more fundamental terminology. Understanding these concepts will help you get a better idea of how artificial intelligence models work with data. You can find the first post on basic AI terminology here.

AI Terms Glossary (Still in Alphabetical Order)

Bias

Bias is a phenomenon in machine learning (ML) that occurs when the outputs of ML algorithms are skewed. This happens due to the prejudiced assumptions made during the algorithm development. Simply put, it’s AI’s reaction to an error in the initial algorithm. This is often a reaction to human error or prejudice that occurs during programming the ML algorithm.

For example, it can happen if the data AI is given to learn from isn’t comprehensive enough or is programmed with cognitive human biases. In this case, the bias starts leading AI toward specific outcomes, affecting the results’ clarity and accuracy. If you are looking for a more technical explanation of how bias works in ML models, check out the relevant page on GeeksforGeeks.

Embedding

Embedding is a technique used to represent data (text, images, and audio) as a mathematical vector. Machine Learning models use data converted through embedding to capture semantic relationships and patterns. That’s the only data format they can directly process at this point of technological development, so embedding is one of the most important AI terms you need to understand right now.

Embeddings allow NLP models to process data, find contextual meanings, and perform tasks like querying, classification, comparison, and recognition. For example, Word2Vec and GloVe are popular embedding methods that are used for word embeddings. In simpler words, they help AI understand texts.

AI terms: Reinforcement Learning

Reinforcement Learning (RL)

Unsurprisingly, Reinforcement Learning is a type of Machine Learning that improves decision-making algorithms over time. It enables an AI-driven system to learn through interacting with its environment using the trial-and-error method. In very basic AI terms, this can be explained as the AI’s ability to learn from all its interactions with the user, both successful and not.

Also, RL uses the exploration-exploitation trade-off. It means that a computer balances the need to discover new, better strategies while exploiting the ones it already knows. The machine does this in order to achieve maximized rewards. This ML model is commonly used in robotics, gaming, and various autonomous systems.

Vector Database 

Vector databases are designed specifically for handling embeddings. The main difference between traditional and vector databases is in their data optimization and querying methods. Basically, instead of querying a row with a perfect value match, vector databases use a similarity metric, searching for a vector most similar to the query.

Devtorium developers used vector databases while working on AI-based recommendation systems, searching for images and text, NLP, and fraud detection software. We’ve also written an extensive article on the topic of vector database applications in AI and their pros and cons.

AI terms glossary: Vector Database

What’s After AI Terms Glossary?

The topic of AI is getting hotter and more relevant in our fast-developing world. Therefore, Devtorium will continue with our effort to explain exactly how this technology works and what it can do. The potential AI tech has is unlimited, and it has already changed human lives in significant ways. We hope that our developers and solution architects will be able to leave their mark on the world as well by creating new AI-powered products.

If you want to read more about AI, check out some of our previous articles:

Build an AI Chatbot with OpenAI Assistant API and LangChain

Technology has progressed so far that you can build an AI chatbot with minimum effort today. The world now really looks like some sci-fi stories come to life. OpenAI is one of the businesses standing at the forefront of this technological revolution.

We talked to Devtorium developers about how OpenAI’s Assistant API is reshaping how we develop digital assistants. Have you ever wondered what the development of chatbots looks like? Devtorium’s developers explore this superb AI-powered tool and share a tutorial on how to build a chatbot with Assistant API and LangChain.

Why Choose Assistant API to Build an AI Chatbot

Developers might have vastly different opinions on whether or not AI code-generation tools are helpful. However, everyone with experience working with OpenAI Assistant API agrees this is a magnificent tool. 

Assistants API is an NLP(natural language process) API currently available as a beta version. You can already use Assistants API for question answering, language translation, and code generation. However, its primary function is to assist developers in building chatbots within their apps. To start using Assistants API, you must have an OpenAI API account. 

Assistants API uses OpenAI-hosted models, access files, persistent threads, and call tools to respond to user queries. According to Devtorium developers, its most prominent and valuable features are:

  • Code interpreter and retrieval: Access and execute code from various sources.
  • Function calling mechanism: Call functions from other APIs.
  • Knowledge base: Store and access information from a variety of sources.
  • Easy conversation management with threads: Keep track of the context of a conversation.
  • Support for different models: Choose the best model for your specific task.
  • Customizable instructions: Control how your assistants respond to user requests and perform tasks.
  • Easy deployment: Deploy to a variety of platforms.

How to Build an AI Chatbot with Assistant API and LangChain

The range of AI software development services offered by Devtorium is vast. Therefore, we explored multiple AI solutions and technologies available today. One of our developers’ favorites is LangChain, a framework built around LLMs (large language models) and designed to simplify the creation of complex apps. This tool connects components: prompt templates, LLMs, agents, and memory to create a chain, hence the name LangChain.

In order for LangChain to work correctly with Assistants API, make sure you download version 0.0.331rc2 or higher. The latest RC version of LangChain can support Assistant API using an experimental package. The only class you need is OpenAIAssistantRunnable, which makes code much cleaner. 

Now, let’s get on with the guide on how to build an AI chatbot using these tools. Using the tips below, you can make an MnA assistant that will answer queries using a retrieval tool. No Chunking, no embeddings, and no vector database are required.

The steps to build an AI chatbot using this approach include:

  1. Create an Assistant API account and get an API key.
  2. Create an Assistant in the API by defining its custom instructions and picking a model.
  3. Install LangChain and create a LangChain project.
  4. Write a script that uses the Assistant API to send and receive messages from users and access and store information from LangChain.
  5. Deploy your chatbot to a web server, messaging platform, or mobile app.

Technical Instructions on Working with Assistant API and LangChain

1. Set up Assistant API 

  • Sign up for an OpenAI account
  • Get API key
import openai

     openai.api_key = "YOUR_API_KEY"

2. Create an Assistant

  • Define instructions for the scope of your chatbot, tools it can access, etc. 
  • Pick a model (code recommendation, text embedding, etc.)
assistant = openai.Assistant("assistant name", model="Davinci")

3. Install LangChain

  • Install LangChain and LangChain-experimental package
  • Import OpenAIAssistantRunnable
from langchain.llms import OpenAIAssistantRunnable

4. Handle user input and get assistant response

  • Take user message as input 
  • Process with OpenAIAssistantRunnable to get assistant response
user_message = input("User: ")

     assistant_response = OpenAIAssistantRunnable(assistant).run(prompt=user_message)["response"]

5. Connect LangChain memory

  •   Store data to use across conversations
  •   Access external APIs through LangChain agents
memory = {"context": {}} 

     agent = ExampleAgent()

     assistant_response = OpenAIAssistantRunnable(assistant, memory=memory, agent=agent).run(prompt=user_message)["response"]

6. Deploy chatbot

  •   Wrap in a web app/API, connect to a messaging platform, etc.

Bottom Line: Who Can Build an AI Chatbot with Assistant API and LangChain

As you can see from the post above, anyone with minimal coding knowledge can build an AI chatbot using tools like LangChain and Assistant API. Of course, an average person with no software development background won’t be able to do this unless they learn extensively.

However, the essential factor is that any small business can now access all the benefits of using a chatbot with minimal investment. All you have to do is contact our team and set up a free consultation. Our experts will discuss your ideas and requirements and come up with a plan that will fit your budget.

No reason for any business to not benefit from a chatbot today exists. So, contact us and take the next step in your tech growth!

If you want to learn more about how Devtorium developers work with AI, check out the following articles:

Devtorium Offshore Software Development Company: Progress Report 2023

As an offshore software development company, Devtorium did not escape the turmoil shaking up the global economy today. However, no matter how trying the times might be, we firmly believe that investing in people is the best way for any business. That’s the core of our values, and we are proud to say that putting our trust in our employees has never failed this company. We can see evidence of it when looking at the 2023 company performance report results.

This year was wrought with conflict, and many businesses struggle with the volatility of markets and economic downturns. Devtorium also faced many challenges during this year. However, we are happy to say that the year’s results are positive despite it all.

What We Achieved as an Offshore Software Development Company in 2023

  • Devtorium started five new projects in 2023, engaging 40 developers and other technical professionals. The projects come from a range of industries, including Health and Education.
  • Over the year, our company welcomed 14 new specialists. Our teams grow, and we actively search for new talent when the projects demand it. You can always find a list of our open vacancies here. If there isn’t a suitable position at this time, leave your CV using the form on the page. Our Recruiting Department will reach out to you when we have an opening.
  • To ensure that Devtorium developers master cutting-edge technologies and can offer top-quality services to our clients, our company launched a Research and Development Department. This department is currently focused on NLP, Deep Learning, Machine Learning, and Neural Networks Training. Developers working within the R&D Department also study Python and contribute to our AI software development services greatly.
  • According to our project statistics, React, NodeJS, .NET, and Angular are the most popular technologies today. However, the interest in no-code development services is also growing. This year, we had some clients interested in developing solutions using Bubble.io.
  • Devtorium launched two in-house solutions in 2023. One is an ERP system that mainly serves our Accounting, HR, and PMO Departments. However, all our employees use it to track working hours on various projects and manage leave requests. The solution is created using the Bubble no-code platform, and it’s constantly evolving. The second in-house project we launched is a CMS system based on Frappe.io. Our Sales Department is using the many capabilities of this platform to manage and grow our leads database.
  • Devtorium completely redesigned our website, devtorium.com, to ensure its design matches our updated brand style and expanded list of services.

Devtorium: Plans for the Future

Our main priority as an offshore software development company is to focus on trending technologies and ensure we can deliver the services our clients need. At this time, this means shifting the focus to the rapidly evolving AI industry. We are proud to see that our developer teams have mastered this technology and learned how to use it to its full potential in the service of our clients.

Next year, we will continue our work to expand the company and introduce new technologies to our tech stack. Moreover, we will continue searching for projects in a variety of industries. However, our primary focus is maintaining the integrity and quality of service that our clients value.

Progress of Devtorium offshore software development company in 2023.

Introduction to AI Part 1: Basic AI Terminology Cheat Sheet

Without a doubt, artificial intelligence technology started a new round of modern progress. Soon, understanding it, at least on a basic level, will become crucial, so you must start learning AI terminology fast. Today, we will begin our series of articles that provide a basic guide to AI by explaining some of the terms essential for understanding this tech. In future articles, we will explain how artificial intelligence works and AI software development services in greater detail.

You can already see how big and small businesses, governments, and ordinary people use AI in everyday activities. When we discover new technology, we try to make it a part of our daily lives. For example, with the invention of near-field communication (NFC), humankind came up with the idea of using it as a way of payment. Now, no one is surprised to see others paying with just a phone or hear NFC in regular conversation. 

The same thing is happening to AI. First of all, AI is a set of techniques that imitates human behavior and completes the tasks that would usually require human intelligence. According to Forbes, the AI market is expected to reach $407 billion by 2027. Thus, providing yourself with AI techs is a win-win investment in your business success.

Introduction to basic AI terminology.

AI Terminology Cheat Sheet (in Alphabetical Order)

Chatbot

A chatbot is an app made to simulate human conversations. It uses NLP to process inputs and generative AI to automate responses. A chatbot can perform multiple functions. For example, it can assist businesses from within or to engage customers.

Computer Vision

Computer vision is a set of AI technologies that allows machines to analyze and interpret visual content. Driven by deep learning models, it can recognize patterns, objects, and even emotions in images. In addition, computer vision can process dynamic content and perform gesture recognition and motion analysis. Today, computer vision can analyze images at extreme speeds and identify objects with 99% accuracy. This technology is applied in various industries, from security to healthcare and self-driving vehicles.

Datasets

Datasets – are large collections of various types of digital data. They are a crucial element of any ML algorithm and are used to train AI systems to complete assigned tasks. The most popular public datasets are Kaggle, UCI, ImageNet, and Quandl.

Deep Learning (DL)

It is a subset of machine learning that relies on neural networks trained on massive amounts of data. In this context, “deep” refers to the use of multiple layers in the network. As AI networks become more complex, the importance of deep learning in the scope of AI terminology increases.

Generative AI

Generative AI is an AI algorithm whose primary function is to generate new output from the training dataset. Whereas traditional AI models mostly follow predefined rules to respond to inputs, generative AI can produce variable content such as images, video, text, and code. Also, it can create outputs either in the same prompted medium, like text-to-text, or in a different one, like text-to-image or image-to-video. A great example of generative AI is Midjourney, with its multiple features.

Large Language Models (LLMs)

LLMs are machine learning models trained on vast amounts of textual data. The most well-known example of an LLM is ChatGPT. A part of Devtorium AI software development services includes creating and training LLMs to deliver the output you need automatically.

Essential AI terminology to know today.

Machine Learning (ML)

ML is a subset of AI development that enables machines to self-learn when dealing with specific tasks without preset coding. It’s one of the most basic terms in AI terminology today. There are many machine learning types and methods. Most of them use conditions (ifs), cycles, and internal variables to train the system`s algorithm. The developer needs to train the model using training datasets but does not change the code itself. Then, the model can be saved, loaded, or used to process new data.

Natural Language Processing (NLP) 

The ability of AI-driven systems to analyze, comprehend, and generate human language is called NLP. The three main parts of any NLP are computer science, human language, and AI. Applications that require NLP include chatbots, text generators, translation tools, and autocorrect solutions. Chatbots, like Amazon’s Alexa and Apple’s Siri, utilize NLP to process user queries and find answers.

Neural Networks

Neural networks are models of teaching machines to recognize underlying patterns. The name refers to neurons in the human brain. It’s because the way this network operates looks pretty similar to them. This kind of structure enables neural networks to handle more complicated challenges than traditional programming.

Prompt Engineering

Prompt engineering is the process of creating specific instructions for LLMs to generate desired outputs. The instruction usually contains information on the way and form of outputting content. It’s a handy skill in the modern world because it allows users to interact with AI more efficiently.

What’s the Next Step After Learning Basic AI Terminology?

This little AI terminology cheat sheet should help you understand essential AI-related content. In order to explain the matter more deeply, we will continue expanding this AI terms glossary and explain how artificial intelligence is built and trained in our upcoming articles.

However, if you want to learn how exactly AI can benefit your business today, contact our experts to set up a free consultation.

For those of you who want to continue learning about artificial intelligence technologies, check out our older posts:

How to Hire an Offshore Outsourcing Software Development Company

Outsourcing software development offers a range of benefits to businesses of any size. The main advantage of this method is flexibility as outsourcing gives you access to a huge pool of talent. However, as much as it could help you, entrusting your product development to offshore specialists could also cause problems. The secret to success here is to hire a reliable outsourcing development company you can trust. This guide will help you with this by pointing out the most important factors to consider when choosing this service.

Benefits of outsourcing software development.

Advantages of Outsourcing Software Development

Before we get into the ‘how’, you need to understand whether outsourcing is the right choice for your business in general. An in-house team means you have more control of the workflow at every level. However, building your own team is guaranteed to be more expensive.

Meanwhile, outsourcing offers the following benefits:

  • Access to versatile tech talent
    When outsourcing software development you have access to all talent worldwide. Therefore, you can definitely find the exact combination of skills and tech expertise required to build your ideal product. For example, you can build an AI development team containing experts who specialize in AI training combined with expert developers who can build the system to their specifications.
  • Shorter time-to-market
    As you aren’t limited in tech expertise and don’t need to spend time recruiting and talent on your own, the product development journey will be shorter. Even if you need to recruit additional experts during the development process, the Devtorium IT recruiting service will do this for you. Therefore, you get to release your product faster and with minimal disruptions.
  • Easy scalability
    Having complete control of an in-house team also reduces its flexibility for scaling. However, when you are outsourcing software development, scaling won’t be an issue. Note that this is true both for up and downscaling. The size of your team will always correspond to your current needs and budget.
  • Quick team expansion
    Note that you don’t have to outsource the entire development project. In fact, you can often achieve better results by choosing IT outstaffing services. In this case, you will enhance your in-house team with additional tech expertise by recruiting offshore specialists. This is a great option for scalability and increasing your product functionality by hiring experts in highly specific areas.
Tips on how to find an offshore software development company.

How to Hire an Outsourcing Software Development Company: Step-by-Step

  1. Outline your requirements
    First of all, you need to have a clear idea of what you want to achieve with your product. In order to choose an outsourcing software development company you need to understand what sort of technical expertise you require. Note that you don’t have to create a complete plan of technical features for the product. However, it will be best to research your prospective competitors and make a list of features you want to have. This way, you will be able to narrow down the pool of outsourcing candidates. For example, you can look for someone with expertise in fintech development, or creating insurance platforms, etc.
  2. Research offshore outsourcing companies
    You can use reputable platforms, such as Clutch, to collect information about various offshore outsourcing companies. A reliable provider will have all the essential information on their website. There you can learn about the services they offer and take a look at the case studies portfolio to get some idea of the company’s expertise.
  3. Conduct an interview and get a proposal
    The next step is to contact the company and set up a meeting where you can discuss your project. You can arrange a free meeting with the Devtorium team anytime. During this meeting, we will collect your requirements and talk about details in order to understand how we can bring your ideas to life. Then, we will provide you with some estimates and a proposal. When ‘shopping’ for a 
  4. Start collaboration with the outsourcing software development company
    Once we settle on the proposal, we can start collaborating to meet your goals and deadlines. Devtorium Project Managers will establish the lines of communication and set up the workflow to ensure that the project stays within the budget and delivery times outlined in the contract.
Best countries for outsourcing software development.

Best Destinations for IT Outsourcing Today

The first task that lies before you when looking for an outsourcing software development company is to choose a country. This shouldn’t be too difficult as there are reports that allow you to understand where exactly the IT outsourcing industry is the strongest. Moreover, you can find out average rates and see which destinations offer the best cost-to-value ratio for the client.

  • Ukraine
    Despite the war currently going on in the country, Ukraine remains the top IT outsourcing destination in Eastern Europe. The revenue generated by this industry has been steadily growing over the last decade and russia’s invasion didn’t impede this growth. According to Statista, the IT outsourcing industry is set to generate $1.7 billion in revenue in 2023 and double that within the next five years.
  • Poland
    Poland has the largest workforce of development professionals in Europe (about 500 000). About 40% of these professionals work in the IT outsourcing industry. Polish software development vendors provide highly skilled labor at a reasonable rate.
  • India
    India is one of the most popular software development outsourcing destinations due to the affordability and abundance of developers. The country has a huge pool of STEM graduates with about 2.5 million added every year.
  • Brazil
    Brazil is the top IT outsourcing destination in Latin America. It’s particularly appealing to US businesses because there are very few issues with time zones. The country heavily supports the IT outsourcing industry through favorable legislation and promotion of technical professions within its education system.

Hiring an outsourcing software development company can be a game-changer for your business. So, don’t hesitate, and take the first step right now!

How to Use Generative AI in Real-Life Business

Generative AI is the buzzword of today. Everyone must have tried using at least one of the available solutions by now. ChatGPT alone has over 100 million users, and Midjourney isn’t too far behind. However, if you are a business owner looking to boost your services or workflow with tech innovation, your main question should be, ‘how to use generative AI in my business?’

We are here to answer this question today. Devtorium offers a wide range of AI software development services, and our solution engineers have expertise with different types of AI frameworks. According to our experts, the only limitation when implementing AI into business is your creativity. Generative AI uses are indeed quite specific. However, using your imagination, you can make these instruments help with many everyday tasks.

How to use generative AI for business.

Step 1: Choose the Type of Generative AI Applications You Need

Generative AI is a technology that trains using specific datasets, and, based on that training, it learns to generate various types of other datasets. Simply put, developers input massive databases that the AI processes and learns. Then, it creates different types of content based on the information it consumed.

It’s also important to note that generative AI applications are today’s top tech trend. They’ve been on a steep rise since 2020 and, according to Gartner, reached the ‘Peak of Inflated Expectations’ in 2022. ChatGPT made this technology truly mainstream as it introduced AI to the mass market. Every person with a computer and internet access could use ChatGPT and get some answers from it. This showed people without connections to software development that AI technology is real and that generative AI uses are endless.

The quick popularization of other AI tools pushed this technology forward faster because, as mentioned before, it learns when it works with data. Therefore, AI improves with every task it completes.

When you consider how to use generative AI in your business, you need to start by researching the types of these tools. The most basic way to separate generative AI into types is by the kind of output content they produce. However, remember that some AI solutions are highly complex and can generate various content.

  • Text generation
  • Code generation
  • Video generation
  • Image generation
  • Sound generation
  • Research and explanation

The last type refers to generative AI uses in research where such tools can process, simplify, and summarize complex texts. For example, you can use Elicit or Enago Read for these purposes. Other popular generative AI apps are ChatGPT, DALL-E, Bard, DALL-E, and Midjourney, which create different content based on user-given prompts or dialogue.

Generative AI tools and their types.

Step 2: Generative AI Application in Real-Life Situations

Types of these tools seemingly make it obvious how to use generative AI. However, are you sure you’ve thought of all the ways this can be implemented in business?

Here’s a list of some ideas for you to consider:

  • Text content creation can be used to make marketing materials, blog posts, advertisements, and even work emails for some situations. For example, if you don’t have a talent for creative writing, generative AI tools like ChatGPT can help you write proposals, congratulatory emails, and even feedback.
  • You can use generative AI to edit texts as well. The tool can help you improve grammar and style or make some translations. However, it’s admittedly not perfect in translations, so be careful with how you use that output.
  • When you need to make guides or other helpful documentation for your customers, you can use AI generators to simplify technical texts. So, you’ll create posts and papers that are easy even for non-professionals to understand.
  • Image and video generators can also be used in marketing. You can create everything from a brand logo to a complete set of marketing materials used in ads, banners, blog posts, and even website designs.
  • In other generative AI uses, 3D models can be implemented in manufacturing and used to aid business planning.
  • Architects can use generative AI applications to create and analyze existing designs.
  • If needed, you can use Midjourney and similar tools to create illustrations for your content.
  • Sound generation can be applied to create tunes for social media or for your personal artwork, as well as advertisements and presentations.
  • Text generators, like GPT-4, are part of responsive chatbots and other automated reply solutions. For example, you can program these tools to send automatic email replies.
  • Sound generation solutions can work with speech in different ways. One of them is speech-to-text, which will allow you to create records of lectures or important meetings.
AI applications in customer service.

AI Uses for Onboarding and Customer Service

Currently, the main areas of generative AI applications are employee onboarding and customer service. That’s because a chatbot is the most popular AI instrument used in business today. However, generative AI uses allow you to expand on those implementations, further boosting their efficiency.

Some ideas on how to use generative AI in onboarding and customer service include:

  • Creating educational courses using video and speech generation technologies.
  • Personalizing customer journey experiences.
  • Creating a support service for navigating the company or website.
  • Creating a service to collect and process complaints, using AI capabilities to allow the tool to resolve some common issues.
  • Developing a content recommendation system for customers to help boost sales.
How to use generative AI to boost your business.

Bottom Line: Who Needs Generative AI Apps Today?

This is only a short list of the most basic AI uses one can come up with today. If you are serious about improving your business’ productivity with this technology, you should book a free consultation and discuss your case with our AI solution developers.

AI applications are so versatile that they can benefit any business today. All you need is a bit of creativity and a lot of technical expertise. We have both and can help you achieve the best results with custom AI solution development services. These can be tailored to your budget and needs. Most importantly, they can grow with your business, offering continuous improvement and optimization.

What Are Devtorium AI Software Development Services?

Innovation is our everything, and AI software development services offered by Devtorium reflect that. We aim to ensure that our clients have access to cutting-edge technology. Together with you, we can create tech solutions that will give your business a competitive advantage even in this age of hi-tech races. Our software engineers, who specialize in artificial intelligence solution development, can use a variety of AI tools to ensure your business stays ahead.

In this post we’ll explain exactly what kind of AI solution development services Devtorium offers. Moreover, we’ll give you concrete examples of how these technologies can be implemented to give any business a boost.

Devtorium AI Software Development Services: Technologies We Use

Artificial Intelligence technologies used today can be roughly divided into three groups:

  • AI/Deep Learning/Machine Learning
  • Reinforcement Learning
  • Generative Networks

It’s vital to understand that when creating AI software solutions, developers usually have to use all these technologies. The solution architect working on your project will analyze the requirements and suggest a combination of technologies to fit your needs best. AI software is highly complex and usually takes both software developers and data scientists to create.

Data Science services are an integral part of any AI software development. Artificial intelligence literally runs on data. Therefore, working with different types of databases and optimizing these processes, for example, through vector embeddings, is crucial for producing solutions that can learn and improve as they evolve. Devtorium AI software development services create self-educating systems that will grow with your business and adapt to its changing needs.

How AI software development services can be implemented in real life.

AI Software Development Technologies: Areas of Implementation

Computer vision

  • Object Detection
  • Segmentation
  • OCR (Optical Character Recognition)
  • Human Pose Detection
  • Face Detection

Computer vision is one of the AI software development services we encounter daily. It’s combined with other types of AI tech to produce solutions that surround us everywhere, for example:

  • Auto-pilots for vehicles
  • Security systems (FaceID, fingertip scanners, building security footage analysis, etc.)
  • AR applications used for eCommerce and gaming
  • Scanning and transcribing text via a photo (try this feature in GoogleTranslate)
  • Advanced search through images, videos, and large documents

Large Language Models (LLM)

  • Text generation
  • Searching
  • Analytics
  • Summarising

The most well-known example of an LLM is ChatGPT. Pretty much everyone who is even a little tech-savvy today used this platform at least once. Its most popular features are text generative and writing code. However, it can do much more than that. For example, an LLM can create text summaries, descriptions of images, and different versions of the same content. It can ‘give advice’. However, the system is pretty straightforward in the sense that its advice is content generated based on your inquiry.

Note that these AI solutions can process literary texts, code, and any other kind of textual data. A part of Devtorium AI software development services is creating and ‘training’ LLMs to automatically deliver the type of service you need.

Role of data science in AI software development services.

Big Data

  • Statistic/Data Analytics
  • Data Transformation

Our world is data, and AI-powered data science solutions can make it work for you in every way possible. Devtorium’s team of data scientists is experienced in creating solutions that can extract and process data from various sources. Some of their projects included:

  • Deriving relevant information from digital reports and massive databases. Then, processing this data and visualizing multiple reports for eCommerce businesses to help the client make educated decisions.
  • Processing data from multiple sources and creating a predictive analytics model to forecast trends and market changes.
  • Transform data from one format to another for future processing and analysis. For example, one of our projects included collating handwritten notes from medical specialists, adding medical records data, prescriptions, and medical test results. The data was transformed, processed, and analyzed to provide necessary insights for an AI-powered healthcare solution.
  • Another project Devtorium completed entailed collecting data from fitness trackers, medical records, prescriptions, notes, and trainer comments as a part of an interactive athletes’ training tracking app.

Robotics & Automation Engineering

Implementation of robotics technologies at manufacturing lines is nothing new today. However, recent advancements in artificial intelligence solutions take this type of service to the next level. As a part of Devtorium AI software development services, our engineers can do much more than simply program the machines to do specific actions automatically.

We are now able to ‘teach’ robots the basics of behavior and program them to learn. As a result, you get automation that improves with every iteration. So, instead of a mindless drone, you get a helper that can increase overall business productivity and significantly reduce the risk of errors.

Bottom Line: Should You Invest in AI Software Development Services?

Answering the question of whether your business needs an AI-powered solution is easy. Just decide for yourself if you want your business to stay competitive on the market. Today implementing AI in various business processes is not about getting head through groundbreaking innovation. Already this technology is becoming so popular and widespread that not using it is sure to put you hopelessly behind.

If you want to not only retain a competitive edge but actually move forward, taking over a bigger portion of the market, contact us today. Devtorium’s team of AI software engineers will work with you to develop a strategy that can help your company succeed.

Core UI Design Principles Every Client Should Know

As a client ordering any UX and UI design services, you need to understand that while personal views on aesthetics matter, designers must not rely on them alone. Professionals adhere to the core UI design principles to create a final product that’s both usable and attractive. Simply put, those principles exist to ensure that users love any solution or website you launch.

Keep reading to learn what those core principles are and some special secrets of the trade shared by Devtorium’s UX/UI design team.

Core UI Design Principles Explained

Focus on the User

The user must be the center point of all UX and UI design. It means that every step of the way designer’s first thought must be, ‘what will be most convenient for the user?’

A good interface doesn’t confuse or distract from the goal of the product. Essentially, all UI design principles focus on making the interface easy and pleasant for people to interact with. A person who opens the app for the first time must be able to find exactly what they need without any guides or additional training. Using it must feel natural, so having the user as a focus of the design is an absolute must.

Another critical factor is that the user must feel in control when using the app. Therefore, UX and UI design must be created in a way that’s easy to master fast. The user should feel confident in their ability to find and do what they need, so the interface must be intuitive.

Moreover, user-focused UI design must allow for mistakes. For example, it means that all actions must be reversible. In addition, any important steps must literally come with a warning.

Main UI design principles that make apps beautiful and functional.

Clarity

Clarity is one of the essential UI design principles today. Never forget that any interface’s purpose is to enable the user to interact with an app. Therefore, they must be able to clearly see what they need to do in order to achieve their goals.

Simply put, clarity of the interface determines whether people using your app are able to do this at all. Poorly designed UI makes it impossible for people to understand what your application does.

However, it’s also important to remember that no specific clarity standard exists. Actually, it will differ significantly depending on the purpose of the app. For example, if you are designing an eCommerce app for a large marketplace, you’ll have to include complicated catalogs with multiple categories and sub-categories. Meanwhile, a basic note-taking app will be much simpler and ‘clearer’. Therefore, as a client, you’ll need to work closely with the UI/UX design services team to create a clear and understandable interface for your target audience.

Consistency

Keep everything consistent! It’s not only one of the main UI design principles but the golden rule of design as a whole. Consistency makes your app more aesthetically pleasing and easier to use and understand. Also, it’s necessary for effective branding throughout all your channels.

In addition, you need to remember that not only your design must be consistent with the brand’s style. You also need to make it consistent with symbols and terms used in various real-life situations. For example, as an eCommerce business, you might want to stand out and make your shopping cart appear in some unique way, discarding the traditional cart or basket design and even renaming the feature.

If you are expecting the result to be that your clients will appreciate how unique your brand is, you will be bitterly disappointed. There might be a few who will genuinely appreciate it. However, most shoppers will simply leave your website fast because they couldn’t find the cart within a few seconds.

So, always remember to be clear and consistent in all your messages!

Ease opf navigation is one of core UI design principles.

Simplicity and Minimalism

Simplicity and minimalism go hand in hand with clarity as leading UI design principles today. Classics are there for a reason, and that reason is that they are recognizable, understandable, and work exceptionally well. So, use that power to create UX/UI design that truly appeals to your audience.

In our world of information overload, minimalism has become equivalent to clarity. So, whether you like the style personally or not, it’s imperative to use it for any app interface design. Otherwise, your product’s chances of success are slim.

Feedback

UX and UI design must be interactive in a way that it must provide feedback to the user. Your UI copy will be responsible for that. So, design extends beyond graphics. The quality of the UI/UX copywriter’s work is no less important for making your app easy to use and understand.

A good user interface will provide prompts and feedback for every action to help users make decisions and master the app.

Accessibility

We are building an inclusive world, so accessibility is one of the core UI design principles today. However, not everyone is the same, and it’s the designer’s job to account for all types of user differences. It’s hard work to research and create an interface that will be equally comfortable for different people.

Adaptable and flexible interfaces that the user can adjust to their preferences are the main future trend. Also, remember that accessibility requirements will differ depending on the type of user interface.

Bottom Line: Always Prioritize UI Design Principles

It’s true that design is a matter of personal taste and preference. However, if you want your software product to be successful, you must consider the main UX and UI design principles. This way, you can ensure that the app is easy to use.

Keep these principles in mind when choosing a UI design company. In fact, the designers you consider hiring must know and adhere to these principles in their work. So, be sure to discuss this during the interview.

Using AI for Sustainability: Technology for a Better Future

Everyone today should understand that our planet isn’t doing too well health-wise. Reports of natural disasters or some other nasty side-effects of environmental changes come almost daily. With the rise of artificial intelligence, we are wondering how using AI for sustainability could help improve this situation. It turns out that AI tech can become a true life-saver for our planet, but only if it’s used wisely.

Artificial intelligence software development technology is developing rapidly. Some of its trends are already focused on using AI for sustainability, but that’s hardly enough. To truly benefit from this tech, people have to invest in the solutions that can make the most difference. However, governments also need to contribute. It’s not only a matter of money but also regulation. It’s because abusing AI tech could lead to tragedies, especially in countries that aren’t liberal democracies.

Keep reading to learn what AI can do to help heal our planet and why we must keep it under control.

Benefits of using AI for sustainability

Using AI for Sustainability and the UN SDG Program

A giant blob of seaweed moving to the shores of Florida right now is only one of the many natural disasters in action. All of them are red flags waving at the planet’s populace, stating that we need to do something to improve the health of the planet. One of the main initiatives currently working on those objectives is the SDG Program. 

SDG stands for Sustainable Development Goals defined by the UN. Those are the goals humanity is working towards to ensure the long-term survival and well-being of our world as a whole. They go far beyond managing climate change, including dramatically important matters like conquering world hunger, inequality, and increasing education quality.

Using AI for sustainability can help achieve over a hundred of those top goals faster and more efficiently. Applying this technology is currently most beneficial in matters concerning climate change and the overall health of our environment.

In turn, this can benefit businesses and economies because we live in a highly interconnected world. For example, according to PwC research commissioned by Microsoft, using AI for various environmental purposes can contribute about $5.2 trillion to the global economy by 2030. That’s not even counting the long-term benefits the entire planet’s population will experience from having a healthier environment.

Using AI for sustainability worldwide could help reduce greenhouse gas emissions by 4%  in 2030, which equals the annual emissions of Australia, Japan, and Canada combined! 

Companies Using AI for Sustainability

Many top companies already use AI for energy management and other practices to reduce their carbon footprint. Top examples of this include:

  • IBM
    IBM is applying AI in many of its processes to boost overall business productivity. Regarding increasing sustainability, one of the most valuable contributions comes from using AI for weather forecasting. Artificial intelligence allows for raising the accuracy of predictions by about 30%. As a result, IBM can help renewable energy companies increase their efficiency, especially in resource management and energy production.
  • Google
    It’s no secret that Google takes sustainability projects very seriously. Running power-hungry data centers, the company must do its best to boost energy efficiency. AI helps Google reduce cooling costs by 40%, and that’s only one of its applications.
  • Carbon Tracker
    Carbon Tracker is a think-tank focused on finding ways to improve the climate situation on the planet. One of its projects is using AI for tracking emissions. They can track CO2 based on satellite imagery and use this data to identify coal plants with the lowest footprint. Then, they use the data to help attract investment to these specific plants.
  • Xcel Energy
    It might be surprising to hear that a company that burns coal and has a high emissions level uses AI for sustainability. However, even businesses that are considered non-eco-friendly work on minimizing their impact. Xcel Energy is using AI to increase its efficiency by about 20%.

However, you don’t have to be a huge enterprise that racks up millions in revenue to start using AI for sustainability. You can use this technology to improve your business practices and processes in many ways. Consider the following ways to implement AI:

  • Precision agriculture
  • Energy management within office buildings
  • Analytics for better resource planning
  • Minimizing energy and water waste
  • Environmental monitoring
  • Sustainable supply chains

Dangers of using AI for sustainability.

Why Using AI Might Hamper Sustainability and Cause Global Problems

Using AI for sustainability can help accomplish great things. Some of the most prominent among them are:

  • Clean power
  • Sustainable production and consumption
  • Clean transport
  • Smart homes and cities
  • Early warning about possible disasters
  • Resilient infrastructure
  • Pollution prevention
  • Clean oceans
  • Disease control
  • Clean water supply
  • Resource management
  • Sustainable resource use

These and many other things can be possible if people work together and wisely manage their resources. AI can be a great help by taking out biases and calculating the best strategies for increasing sustainability and equality.

That said, this power can be used for evil as easily as it can be used for good. Therefore, it’s imperative to develop specialized regulatory bodies and strategies to monitor the applications of AI.

One of the most concerning matters is the use of this technology by authoritarian and totalitarian political regimes. Some non-democratic governments are already using AI for tracking purposes. There is a huge risk that they will abuse this technology further in order to maintain power and control of their territories and promote their corruption schemes.

A lack of transparency and competent regulation when it comes to using AI for sustainability or any other purpose can result in tragedies. It will definitely lead to multiple safety risks, including some with possible global consequences. It will also make it impossible to maintain clear ethical standards.

Therefore, any large-scale use of AI should be preceded by the development of proper regulation. Currently, technology is growing and spreading much faster than appropriate political and regulatory protocols. This should be concerning for all of us.

Statistics of using AI for sustainability

Bottom Line: The Future of AI and Its Impact on the World

Even the most basic AI chatbot can do incredible things today. Therefore, the future of AI technology is certainly bright. It will continue developing and growing fast because it’s the top investment opportunity right now.

However, that growth can lead to unimaginable consequences without proper regulation. So, the question isn’t how we can use AI for sustainability but how to ensure that sustainability is all it’s used for.

We shoule use AI for sustainability with better regulation.

Is Bubble the Best No-Code Development Platform?

No-code development can’t replace professional developers yet. However, it’s certainly getting better at creating software. Some of the best no-code development platforms can already create efficient and reasonably complex apps. Bubble.io stands out among these services due to its reliability and versatility. We know this because one of the Devtorium teams is using Bubble to develop an ERP solution for our company.

According to forecasts, the global no-code/low-code development platform market will reach $187 billion by 2030. If things continue as they are now, Bubble will be among the top platforms there. So, if you are wondering whether to choose it for your own MVP development, keep reading. Our team compiled a list of the platform’s pros and cons based on their experiences.

Benefits of Using No-Code Development Platforms for Small & Medium Business

No-code and low-code development platforms have been around for a while. Initially, they were very limited and mostly served as aids for developers. In essence, even today, no-code development is often used to cut down the software engineer’s work hours and involvement in a project. However, this tech can’t replace the professional entirely. That’s because an expert must manage it.

That said, no-code development offers small and medium businesses a great opportunity. These platforms enable SMBs to create affordable customized software to boost their business’ productivity and speed up inner processes.

Moreover, using a no-code development platform is a fantastic way to build your MVP. If you have an idea, this type of solution will allow you to make it presentable to attract investors.

However, in order to make the most out of your no-code development project, you must understand the capabilities and limitations of the platform you choose. In this article, we’ll analyze Bubble, one of the leaders among the best no-code development platforms today. 

Is Bubble the best platform for no-code development?

Bubble No-Code Development Platform: Pros & Cons

Advantages of Using Bubble

Every Devtorium developer who used or even researched Bubble says its main advantage is that the platform allows you to write your own logic. Quite often, it’s a massive issue with no-code platforms because they only let you develop solutions based on built-in plans.

However, Bubble allows developers the maximum level of flexibility. So, you can use this platform to create almost any type of solution. For example, this includes marketplaces, SaaS, dashboards, or even your very own social network.

Our devs believe Bubble is an excellent platform to test your ideas. You can use it for developing an app fast and evaluating how all the features you want to include fit together. You can also use it to have a focus group test the app. This way, you’ll be able to assess and improve your app development plans. In addition, you can see the audience’s response to it.

Aside from the flexibility, Bubble offers a wide range of functionalities you can integrate into your app. This no-code development platform is extremely versatile and has a vast plugin marketplace. Therefore, there is hardly a feature you can’t find. Therefore you should be able to create precisely the type of software you want.

Moreover, there is a thriving Bubble community, and the platform’s support service works exceptionally well. So you’ll be able to find advice or discuss any questions you have. 

Bubble No-Code Platform Limitations

Even the best no-code development platforms aren’t perfect. So you need to consider their limitations before settling on a no-code platform for your project. In fact, your long-term plans are the foremost thing to consider when using Bubble. For example, if the platform doesn’t have the capability for features you want to add in the future, reconsider using it at all.

Of course, no-code development platforms evolve and release new features and functionalities regularly. However, betting the future of your own project on this chance is probably a mistake.

That said, you must remember that the features you might like at the idea stage aren’t what your target audience needs and wants. So from this point of view, creating a high-quality MVP with Bubble might pay off because you’ll be able to collect relevant feedback. But bear in mind that you might need to move to a different platform or even build your native app from scratch again using different technology.

In addition, we discovered that Bubble is flexible for functional design but not for UI/UX design. It’s a fundamental fact to keep in mind when you try to bring your idea to life using Bubble. You’ll be disappointed if you believe you can create a functional app and upgrade the design later, you’ll be disappointed.

Bubble no-code development platform is somewhat limiting in UI/UX design adjustments. It means you have room to create an attractive UI design as you start developing, but you can’t change it much after creating the app. So the solution is to have your design on hand when you start working with this no-code development platform.

Pros and cons of using Bubble for no-code development.

Bottom Line: How to Choose the Best No-Code Development Platform

If you think about no-code development, Bubble is definitely one of the best options today. Our developers tested it extensively and were very impressed. However, you need to remember that all these platforms have limitations. The most important among them is processing power.

Simply put, no-code is suitable for small and medium projects. However, enterprise-level businesses won’t be satisfied with the results.

You need to consider your specific needs and plans to choose the best among no-code platforms. Research what each option can deliver and pick the one that meets your needs best. Don’t forget to consider the price because these solutions won’t be free if you want to have a decent amount of processing power.

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