Many people are unfamiliar with the term “artificial Intelligence” and it is a source of mystery for many.
The term “artificial Intelligence” has a long history and is not new. This term first appeared in the 50s and 60s. There is a lot of fiction that is dedicated to it. Why is this term so popular? There is one reason, I believe. Computer science saw a new approach in 2012 AlexNet is the first convolutional neural networks.
AlexNet was able find patterns in images. Nvidia’s CUDA technology made it possible. It allows us to simultaneously process large volumes of primitive data. It’s fast enough to train neural networks. AlexNet was used by engineers to create similar architectures that could be used for fast training neural networks. It was a combination of scientific ideas and hardware technology that enabled a neural network to be trained. This led to a revival in artificial intelligence.
It is not possible to call it artificial intelligence, but this term can be used as a conditional term. The human can’t explain the task. It is impossible for people to explain how they classify a car in an image. Artificial intelligence is almost the same. Artificial intelligence isn’t magic or a mystery. It needs input. A neural network analyzes low-level and higher-level features in a photograph, and it needs data to train it. Its accuracy is higher than that of a human today.
What are the components of an AI system?
Artificial intelligence, a branch in computer science, is concerned with developing smart machines that can perform tasks that normally require human intelligence. These tasks can be performed by a variety of ready-to use solutions. You may already be familiar with pre-built apps and tools like IBM Watson.
We can see the components of an AI system as a comparison to websites with different levels of complexity. There are five levels to complexity in AI:
If you are able to understand the principles of machine learning, semi-automatic tools such as Amazon SageMaker and Azure AI can be used.
Third-party libraries such as Google Cloud Vision (OCR), or Google Speech-to Text.
Ready-to-use models like VGG, BodyPix, Keypoint R-CNN, StyleGAN. You can train them to recognize primitives and improve their recognition accuracy.
Create custom models from scratch. We need to have a lot of data (millions) in order to get the right result. For solving unique business problems, custom AI models are highly valuable.
What do you consider the advantages of an AI-powered system compared to a non AI one?
AI can solve complex problems or provide solutions that aren’t possible before. It simplifies the process. AI can be used to analyse data and automate business decision-making. AI-powered systems are generally more efficient.
High demand is being shown for AI-powered systems. If you have a lot of data, video or images, then AI-powered systems are worth considering for your business. It’s applicable to all industries. GPT-3 and other AI-solutions are driving up demand.
What overlap could there be between AI systems used in different business contexts and how much might they be similar?
This question can be answered with a double-edged sword.
AI-powered solutions may be compatible, particularly when they are related. Let’s take an example. A social business encourages social transport. While riding on the bus, the user takes a photograph. An AI-powered system then determines if the photo was actually taken on the bus. The object recognition part of the process can be used in other areas.
AI-powered solutions can be completely different and built from scratch for NLP, computer vision, speech, and optical recognition. Everything depends on the client’s business.
What’s the AI apps concept and how can it benefit business leaders?
If business leaders know what they are trying to accomplish, AI apps can be a valuable asset. After conducting a business analysis, this is possible to determine. It’s possible to reach your goals if you have clear objectives. AI solutions can be useful, for example, if you want to predict sales and find the most efficient employees. We have an approximate vision so that we can create a model, test it, and then deploy it. This process requires a lot of data. We will review the business metrics and business values provided by clients at the initial stage or create them with the help of the customer.
Sometimes business leaders need AI magic but don’t have a clear vision. We help business leaders understand what data they can get, where to move it, and what the benefits of AI solutions implementation. Let’s take, for example, the case of the automotive industry. Our client could benefit from AI tools to help them with sales forecasts. Our team used sentiment analysis (interpretation of emotion within text data) as well as image classification (CV). These tools are useful when analysing social media responses and gathering information about brand attitudes.
It is difficult to describe the benefits that AI brings to all businesses. It is necessary to select a company and analyze it.
Could you explain the involvement of your customers in developing services?
MobiDev’s first goal for clients is to find the right solution. All clients see the service in a different way. As a service provider, our company tries to include the customer in the process, without overwhelming them. Clients enjoy this interaction with the team.
It all depends on the client’s needs, preferences, and requirements. If the customer is innovative, a high level of involvement will be desirable. It is also mandatory when there are many permanent changes to be made or when business leaders still need to define the product they wish to receive. We agree with such clients to set milestones and sprints in which they participate. We also plan a schedule for meetings.
We understand that clients are the most important thing to us. MobiDev’s team takes care of the routine work so clients can focus on their business. They also offer transparency and an easy way for them to make decisions.
Digital technology is constantly changing. How should you approach R&D?
In our company, we use the term “research”. It’s the process of mastering new technologies that our company doesn’t use. These technologies can be useful for clients and solve problems. They could be up and running in no time.
MobiDev’s R&D experience is around 30% of our work. Research is a key component of developing high-tech tech such as artificial intelligence. We give enough attention to it.
How do you approach building and developing a team?
The team for us is something that is cohesive and includes the customer. Our success is dependent on the client as much as our engineers. Building relationships with clients and employees is a win-win strategy. MobiDev’s light-hearted atmosphere, transparency, and understanding of the process are all benefits. We believe that a team is comprised of people who work together on the same task, and we are committed to communicating.
We are keen to see the growth of MobiDev’s employees. Our approach to building and developing the team has been adjusted to the current pandemic. We insist on co-operative work, in which the client is involved.
Are they concerned that the technology is not mature enough or are the steps unclear to them?
Our approach is explained clearly and in the most simple way possible. Even clients with no technical background should understand our presentation. Because the process is clear, customers feel more at ease. We explain things illustratively using appropriate examples. This allows us to speak frankly about the risks and convey the idea that they can be managed.
The whole process is broken down into smaller iterations called “proofs of concepts”. Sometimes, the number of proofs is five or more. We are able to manage risks and can develop the AI solutions needed to make the business feel at ease.
What are the issues a company should consider when considering an AI-powered system for their business?
A company must first be able to conduct research and develop solutions. Leaders in business must know their problems and be able to gather data. They also need to be able to calculate success. AI-powered systems will require continued support, which should be considered.
Do you see untapped potential in certain business sectors for AI?
Leaders in AI adoption are investing more in the future. High tech and communications, finance, energy and resource, high tech, and automotive and assembly are all areas where AI solutions are highly sought after. However, AI’s potential remains untapped in certain sectors, which will change quickly. These industries include travel and tourism, professional service, building materials, and construction. We will also see an increase in costs associated with the implementation of AI solutions for healthcare, retail, and education.
Is AI-powered technology only for large businesses with large budgets?
AI-powered solutions don’t have to be expensive. We have worked with many companies, including startups with limited funding. This means that AI is not a necessity to reap the rewards. It is determined by the client’s capabilities. It can either be pre-built or made from scratch.
In a few years, where will AI be?
In AI, there are three levels of decision-making: predictive, descriptive and prescriptive. The descriptive approach describes what’s happening right now in the system. The second level is the predictive approach. It describes what might happen, semi-automates decision-making, and draws your attention to particular points. Prescriptive is fully automated and provides a ready-to use decision.
The two highest levels are usually used. One example of this is the system for evaluating credit issuing. A person who comes to a bank to apply for a loan is asked to provide their credit history and other important data. The evaluation of these parameters is already automated for microcredits. This is done by using the prescriptive approach, which determines if the borrower will repay his loan. The prescriptive approach is not effective when we are talking about large amounts. Because of the high risk. In 5-10 years, AI will enable us to make more critical decisions. Let’s prepare for the next tech revolution!