Artificial Intelligence Programming

Artificial intelligence is a branch of computer science focused on computer simulation of intelligent behavior.

Typical issues for artificial intelligence methods:

We offer next pattern recognition services:

• Optical character recognition
• Handwriting recognition
• Face recognition and face detection
• Motion detection and recognition

Our image processing offers:

• Image retrieval
• Object recognition
• Measurement of pattern
• Image sharpening and restoration

Data mining is primarily used today by financial, communication, retail and marketing companies. We provide data mining services that enable these organizations to determine relationships among «internal» factors such as price, staff skills or product positioning, and «external» factors such as economic indicators, competition, and customer demographics. Our solutions enable companies to determine the impact on customer satisfaction, sales, and corporate profits.

Following are the aspects in which Simmakers data mining services can contribute for your business:

	Financial Data Data warehouse design & construction, based on benefits of financial data mining Trading strategy development and trading rule discovery using genetic algorithms Market and credit risks calculation Visualization tools for financial data analysis
	Telecommunication Industry Data warehouse design & construction, based on benefits of telecommunication data mining Multidimensional analysis of telecommunication data Telecommunication data processing for marketing purposes Telecommunication fraud detection Telecommunication network fault isolation and prediction Visualization tools for telecommunication data analysis
	Retail Industry Data warehouse design & construction, based on benefits of retail data mining Analysis of effectiveness of sales campaigns Multidimensional analysis of customers, products, sales, region, time, etc Product recommendation and items cross-referencing Visualization tools for retail data analysis

With Simmakers, you get a competent solution created by highly qualified specialists in  data mining, artificial inteligence, software engineering and applied mathematics.

We have several advantages that allow us to solve problems successfully:

• Partnership with NVIDIA. Being partners with NVIDIA , the world’s largest producer of graphics cards and GPUs, we apply the corporation’s latest achievements in the development of IT-solutions in computer graphics, data visualization and parallelization of computations.

• Extensive experience. Cooperating with customers from North America, Western Europe, Russia for more than a decade, our specialists have completed more than 30 complex projects on data visualization and computer simulation of physical and technological processes for various industries, including construction engineering, oil and gas extraction, metallurgy, film industry, healthcare, arts, etc.

• Profound technological expertise. Simmakers specialists have won high recognition and international awards in various fields and are professionals in applied mathematics, IT and software development. We actively collaborate with the leading international research and development centers, such as the Massachusetts Institute of Technology (MIT), the University of California (UCLA) and the Skolkovo Institute of Science and Technology.

• Custom-tailored service. In the development of IT solutions, we make the demands and needs of each customer as our highest priority. This approach allows us to develop trusting and mutually beneficial relations with customers resulting in beneficial effect on the efficiency of project implementation.

• More questions? – Contact Us.

Listed below are some of our featured projects.

Deformable Registration	Thermosim
Ecoview	Elementary Car Emulator
Emotion recognizer

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We apply various techniques:

	Artificial neural networks Perceptrons Multi-layer perceptrons Radial basis networks Cognitron, neocognitron Hopfield networks
	ANN training algorithms Inverse propagation by gradient descent Levenberg–Marquardt algorithm The resilient propagation (RPROP) Broyden-Fletcher-Goldfarb-Shanno method МConjugate Gradient (CG)
	Genetic algorithms Genetic programming Evolutionary programming Evolution strategy
	Fuzzy logic Propositional Predicate Highest-order
	Expert systems, hybrid intelligence systems Hybridization algorithms Hybrid expert systems Hybrid neurons and neural networks Hybrid ANN training algorithms

Q: What is Artificial Intelligence?

A: Artificial intelligence (AI) is the intelligence exhibited by machines or software. Also it is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.

Q: How does Artificial Intelligence work?

A: There are many different approaches to Artificial Intelligence, none of which are either completely right or wrong. Some are obviously more suited than others in some cases, but any working alternative can be defended. Over the years, trends have emerged based on the state of mind of influencial researchers, funding opportunities as well as available computer hardware.

Over the past five decades, AI research has mostly been focusing on solving specific problems. Numerous solutions have been devised and improved to do so efficiently and reliably. This explains why the field of Artificial Intelligence is split into many branches, ranging from Pattern Recognition to Artificial Life, including Evolutionary Computation and Planning.

Q: What are the applications of AI?

A: Here are some examples.

expert systems

A «knowledge engineer» interviews experts in a certain domain and tries to embody their knowledge in a computer program for carrying out some task. How well this works depends on whether the intellectual mechanisms required for the task are within the present state of AI. When this turned out not to be so, there were many disappointing results. One of the first expert systems was MYCIN in 1974, which diagnosed bacterial infections of the blood and suggested treatments. It did better than medical students or practicing doctors, provided its limitations were observed. Namely, its ontology included bacteria, symptoms, and treatments and did not include patients, doctors, hospitals, death, recovery, and events occurring in time. Its interactions depended on a single patient being considered. Since the experts consulted by the knowledge engineers knew about patients, doctors, death, recovery, etc., it is clear that the knowledge engineers forced what the experts told them into a predetermined framework. In the present state of AI, this has to be true. The usefulness of current expert systems depends on their users having common sense.

heuristic classification

One of the most feasible kinds of expert system given the present knowledge of AI is to put some information in one of a fixed set of categories using several sources of information. An example is advising whether to accept a proposed credit card purchase. Information is available about the owner of the credit card, his record of payment and also about the item he is buying and about the establishment from which he is buying it (e.g., about whether there have been previous credit card frauds at this establishment).

speech recognition

In the 1990s, computer speech recognition reached a practical level for limited purposes. Thus United Airlines has replaced its keyboard tree for flight information by a system using speech recognition of flight numbers and city names. It is quite convenient. On the the other hand, while it is possible to instruct some computers using speech, most users have gone back to the keyboard and the mouse as still more convenient.

understanding natural language

Just getting a sequence of words into a computer is not enough. Parsing sentences is not enough either. The computer has to be provided with an understanding of the domain the text is about, and this is presently possible only for very limited domains.

computer vision

The world is composed of three-dimensional objects, but the inputs to the human eye and computers’ TV cameras are two dimensional. Some useful programs can work solely in two dimensions, but full computer vision requires partial three-dimensional information that is not just a set of two-dimensional views. At present there are only limited ways of representing three-dimensional information directly, and they are not as good as what humans evidently use.

game playing

You can buy machines that can play master level chess for a few hundred dollars. There is some AI in them, but they play well against people mainly through brute force computation—looking at hundreds of thousands of positions. To beat a world champion by brute force and known reliable heuristics requires being able to look at 200 million positions per second.