Machine Learning and AI development laboratory

NGENICS

Create complex AI allied solutions based on machine learning,
computer vision, image recognition and expert systems integration

We develop any kind of solutions from desktop to high-performance, distributed processing

EXERCISED AI TECHNOLOGIES

Computer vision

Both pictures and video stream recognition systems including One-shot Image Recognition. Strong competence in creating computer vision apps and integrating image-recognition ai-solutions.

Natural language processing

Text generating systems, recommendation systems based on text recognition, classification and clusterization algorithms. Our work covers areas such as sentence understanding, syntactic parsing and tagging, sentiment analysis, and models of text and visual scenes.

Data analysis and prediction

Create prediction and classification models using both traditional and deep learning. Develop deep configuration architecture and unsupervised feature learning mechanism that can handle a large amount of data.

AI APPLICATIONS

Monitoring

AI can rapidly analyze large amounts of data and detect abnormalities, thus it is very well suited for monitoring applications, such as detecting credit-card fraud, cybersecurity intrusions, early warning signs of illnesses, or important changes in the environment.


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Discovering

AI can extract valuable insights from large datasets, often referred to as data mining. In particular, because AI uses dynamic models that learn and adapt from data, it is very effective at uncovering abstract patterns and revealing novel insights.


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Predicting

AI can forecast or model trends, thereby enabling systems to predict and personalize responses. These types of applications, such as Netflix’s recommendation algorithm, analyze users’ viewing histories and suggest new titles that they might like.


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Interpreting


Until recently, most data analytics was focused on structured data. Because AI can learn and identify patterns, it can interpret unstructured data, such as images and text.


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Interacting with the Physical Environment

AI allows autonomous systems to engage directly with the physical environment. It enables robotic systems that can navigate and manipulate the world around them.


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Interacting with People


AI can allow humans to interact more easily with computer systems. With AI computer systems can respond to speech, gestures, and even facial expressions.


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Interacting with Machines


AI can automatically coordinate compli- cated machine-to-machine interactions e.g. data center computing activity and environmental conditions control.


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Farming Autonomously

Autonomous indoor farming system can use networked sensors and machine learning to constantly monitor a farm’s environment and plants condition and adjust lighting, temperature, humidity, water, and soil nutrient levels or notify the farmer about the plant’s diseases e.g. mold, bacteria, or insect damage. The system learns from historical data and refines its predictions to maximize the farm’s productivity.

Predicting Where Earthquakes Do the Most Damage

A start-up called One Concern has developed a system that uses AI to model a town’s buildings, based on factors such as building age, density, and construction materials, and predict how they would react to seismic activity.70 If an earthquake hits, One Concern can plug in the new seismic data to estimate which areas are likely the most damaged.71 Using these predictions, first responders can prioritize disaster response efforts to target the hardest hit areas after an earthquake.

Avoiding Dangerous Solar Flares

Researchers at Stanford University have developed a machine-learning system that can predict M- and X-class solar flares, which produce dangerously high levels of radiation that could harm airline passengers, damage power grids, and disrupt communication satellites.80 The system analyzes data about the sun, such as the topology of its magnetic field and its atmosphere, and can identify regions of the sun likely to produce solar flares.81 More advanced warning of when and where a solar flare could occur will allow airlines, power grid operators, and others to take precautionary measures to avoid danger.

Predicting stock market

The ability to predict the stock market is, as any Wall Street trader will tell you, a license to print money. So stock analytical systems are of no small interest to anyone, who develops machine learning. System of this kind work by ingesting large quantities of financial news along with minute-by-minute stock price data, and then using the former to figure out how to predict the latter. The algorithm buys, or shorts, every stock it believes will move more than 1% of its current price in the next 20 minutes - and it never holds a stock for longer. The results are quite impressive: such an algorithm performs at least on parity with the 10 top rated funds (S&P top 500 rating).

Teaching a Robot to Recycle

Autonomous recycling system uses a robotic arm, an array of sensors, and AI to identify recyclable items in waste and separate them for recycling, removing the need for manual sorting. It analyzes trash on a conveyer belt using 3-D scanning, spectrometer analysis, and other methods to determine what a piece of trash is made of, and, if recyclable, a robotic arm will pick it up and move it to a separate container.

Automating Office Assistants

Virtual-assistant service can analyze employee calendars and emails to automatically schedule meetings and adjust calendar appointments. Users can copy the virtual assistant in emails when they want to set up meetings, and it will analyze email text to determine the topic and time of a meeting, determine if there are any conflicts, and automatically schedule calendar appointments. The app can also search for and add relevant phone numbers, reschedule meetings by conversing with users, and learn users’ preferences over time.

INTEGRATING AI INTO INDUSTRIES

agriculture

agriculture

consumer convenience

consumer convenience

healthcare

healthcare

education

education

telecommunication

telecommunication

public safety

public safety

transportation

transportation

industrial operations

industrial operations

business operations

business operations

energy

energy

Key Competence

We invent the next generation of computer infrastructure through innovations in software design, enabling new applications for mobile, cloud and data-intensive computing.


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Area of expertise

  • Image recognition mobile-apps
  • One Shot Recognition applications
  • Life video stream analysis, objects recognition and classification
  • Language processing and compilation based on NLP algorithms
  • Numeric data based recommendation and prediction systems
  • Recommendation systems, based on both language and image analysis

Our work ranges from basic research in AI algorithms to key applications in banking, retail, insurance and automotive industries. A distinguishing feature of the NGenics Group is our effective combination of sophisticated and deep modeling and data analysis with innovative probabilistic, machine learning, and deep learning approaches.


For more information & portfolio

INFO at NGENICS.AI

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Location

Ananievsky pereulok, 4/2,
107045, Moscow,
Russia.