The use of artificial intelligence for commercial purposes is not a distant perspective now. Earlier, machines were unable to compete with human brain. But with the introduction of artificial intelligence, computers have learned to replicate the cognitive functions of humans. Artificial neurons are structured in the form that human neurons are, they can constantly teach themselves by receiving new information, analyzing it and improving the result step by step.
With a market projected to reach $70 billion by 2020, AI is poised to have a transformative effect on consumer, enterprise, and government markets around the world.
We are focusing our efforts on neural network development in four areas:
- Neural networks for healthcare
- Neural networks for other industries
- Optical character recognition (OCR)
- Natural language processing (NLP)
In order to create neural networks in the most optimal and efficient way, we are using the top-level equipment in both Moscow and Yekaterinburg offices. The partnership with Nvidia allows us to use their best products for computation on a daily basis.
It is worth mentioning that simultaneous work of specific neural networks is able to create an additional symbiotic effect and create spaces for more possible applications.
Neural network development for healthcare
We offer neural network development for institutions interested in creating their own AI, which will serve as an assistance tool for medical specialists. This area is separated from the others, since application of AI in healthcare is our main goal.
Introduction of artificial intelligence into diagnostics will help to avoid the factors that might affect the decision-making process for the doctors:
- Narrow view of the problem
- Lack of specific experience, knowledge and skills
- Lack of time to study the anamnesis of the patient
- The possibility of making erroneous and illogical decisions in specific cases under the influence of certain factors (fatigue, irritation, subjectivity)
AI in this case acts as a non-subject to the foregoing factors, which somehow can affect the accuracy of the diagnosis. It is important to note that the speed of decision-making by a neural network is significantly less than the speed of decision making by a doctor. In terms of business, each case review and diagnosis procedure will take much less time and will save many working hours annually.
Our approach is based on computer vision, which is supposed to automate tasks that human vision does. This includes not only the image recognition to define the type of image and its segmentation, but also an analysis of diseases.
We are able to provide you with the best solutions based on the data amount, medical image type and financial capabilities you have. The neural network will be thoroughly customized and adjusted up for your needs.
Artificial neural networks can be trained by using various types of medical data:
- Computed tomography and magnetic resonance imaging (CT and MRI)
- Positron emission tomography (PET)
- Ocular fundus imaging
- Histopathological imaging and others
Our expertise, significant computational powers and tools allow us to bring the neural network to life as a quick, comfortable and intuitive software in a timely manner and with a high accuracy of detection.
Neural network development for enterprises
In addition to healthcare, we are looking for opportunities to operate in other industries. We are confident that our expertise will allow us to create neural networks in other areas as well. As Skychain mainly builds neural network on computer vision, we can define the areas, where we can apply our expertise to create new solutions:
Industrial quality control
Producers increasingly rely on artificial intelligence, because it can significantly assist them in increasing throughput, reducing errors and risks in the production chain, complying with regulations and achieving high quality of end product.
In some areas, such as automotive or life sciences, defects of products might result in heavy fines or even lead to deaths. Neural networks will check the product line, simultaneously inspect the quality of several samples and report to the system in real time.
AI in logistics will harness all the data from the supply chain, analyze it, identify patterns and provide insight to every link of the supply chain. The high volume of data that supply chains generate on a daily basis. It is very underused and AI will help to make it more structured and exploitable.
Neural networks can also predict the estimated transit time. By analyzing different parameters of internal data, the machine learning model will be able to predict if the average daily transit time for a given lane is expected to rise or fall up to a week in advance.
Artificial intelligence can save a lot of time for the human resources specialists. It can scan, read, and evaluate applicants and quickly eliminate 75% of them from the recruiting process, saving the specialist from doing the monotonous and stressful work. Another application for AI is onboarding assistance. Specially trained neural networks determine customized onboarding procedures for every single position. By analyzing key performance indicators and behavior, neural networks assess the performance and can dramatically improve productivity of the company.
Optical character recognition (OCR)
Skychain plans to create an optical character recognition neural network. We feel that development of our own OCR will benefit for us in both project and commercial use.
Optical character recognition allows to operate with big amounts of text data and convert the images of typed, handwritten or printed text into machine-encoded text. The process of document management within a big company usually requires OCR assistance on a daily basis. Neural network reprocesses the image and analyzes the structure of document. Later, it reviews the distinct elements, separates them into particular characters and then compares them to a set of pattern images. Then it creates numerous propositions of what character it might be, processes them and comes up with the decision, presenting you the fully recognized text.At the latter stage of Skychain project, we assume that our own OCR will help to make another step towards increasing the accuracy of diagnostics.
Natural language processing (NLP)
Our team plans to work on natural language processing neural networks and expand in this direction as well. NLP itself is related to the area of human-computer interactions. This field of AI development has a lot of potential for the researchers. Today, researchers refine and make use of such tools in real-world applications, creating dialogue systems, speech-to-speech translation engines, scanning social media for relevant information, and identifying consumers’ sentiment and emotion toward products and services.
NLP neural network can be used as:
an enhancement tool for grammar checking or writing platform
a human-computer interface that is able to convert a natural language into a computer language and vice versa. It can make a visually impaired person able to use a natural language system (with speech recognition) to interact with computers.
an add-on for language translation program that could translate from one human language to another. This would cut down the time needed for translating documents.
software, which is able to understand and process human language, convert the information from electronic books and websites into structured data and further stock into a huge database.
The introduction of chatbots is a very common implementation of NLP into customer service. Chatbots are a form of the ‘intelligent assistant’ technology. They can “step in” for routine tasks such as answering straightforward questions from an organization’s knowledge base, or taking payment details. 40% of large businesses have implemented this technology in some form, or will have done so by the end of 2019. Organizations are clearly becoming more comfortable with the idea of integrating chatbots and intelligent assistants into their processes, and confident that it will lead to improvements in efficiency and customer satisfaction.