Our research objective to make continuous efforts in the field of Aritficial Intelligence to build machines that are capable of become artificial assistants to humans helping them to live a better and more intelligent life.

Research Problems

Learn from Observations

Machines are not observing the users and they are not learning from them, they do not get better with experience, they do not gain any experience, they stay the same until the manufacturer spend great amount of money to build new upgrades and release it to users.

Perceive the environment

Machines are usually made without any sense of their environment. They are made to work without any clue of what is happening and the specific usage is usually not monitored because of which they fail to provide an experience that is capable of self-enhancement for the better usage experience.

Optimize the performance

Machines are still not made to accommodate the environment that they are working in. They do not have any idea about the project that they are used in or the constraints that they are supposed to satisfy to be able to work at the peak efficiency. Without the perception of its environment machines are made to work in most general of the settings for them to be useful and are therefore made dumb by design.

Learn from Supervision

Machines are still not made to accommodate the environment that they are working in. They do not have any idea about the project that they are used in or the constraints that they are supposed to satisfy to be able to work at the peak efficiency. Without the perception of its environment machines are made to work in most general of the settings for them to be useful and are therefore made dumb by design.

Optimized Decision Making

Machines are not made to optimize the usage for the user according to its perception of the environment. They often fail to achieve the minimal change required of them with the change in the usage environment. There is practically no adaptability present in machines and they are made not as expert assistants but as dumb tools to get the job done.

Communication Skills

Machines are incapable of responding to the user queries because they are still incapable of having a conversation with the users. With this fault the user is left with no other choice but to look for solutions outside the machine environment.

Objectives

Taking a step back and reinitiating the research in Artificial Intelligence with a different approach where, through big data and advances in robotics, the behavior of humans is even deeply studied than before to make machines attain a level closer to human intelligence

To analyze the power of human brain futher in estimating and predicting the chances of various day to day events and build statistical learning techniques that can behave like humans and build better solutions to problems that are too tiresome for humans to solve

To utilize the ways of the Deep Learning techniques to build into machines the capabilities of utilizing the observation of different possible unrelated phenomenon to improve their current skills or to gain new skill

To create the Natural Language Processing techniques that can decipher the human communication where what they say is usually not what they mean

To measure those things that are deemed unmeasurable by mimicking how human creates their own process of judgement and coding their ways into mathematical models, and much more

Brain

Inspired by Game of Life, Path of Evolution, Neural Networks, Optimization, and Human Brain, Brain is to be an operating system which would be capable of operating any machine with tiny processing power to the one with quantum capabilities. The brain is to function based on examples, it should be able to observe, understand, react, and build from experiences. It is to understand a language that translates from that of humans.

Brain Simulation Neural Network Path of Evolution Transition Rules Optimization Evolutionary Algorithms Computation Efficency Function Approximation Multiplication Solution Space Fourier Transformation Addition Bayesion Network
Vision

The idea behind Vision depends on capability of human mind to do more with little. To know we can move forward we determine empty space by looking through our two eyes, experience, and inspection. Human vision is much more than image processing and it to be treated in this project as such.

Layer 1 Vision Empty Space Discovery Motion Through Empty Space Distance Prediction Modeling Object(3D) Dual Camera Analysis Sensor Feed Integration Trignometric Analysis Spacial Analysis Temporal Analysis Speed of Motion AI Trigers Expression Activity Recognition Object Brain
Communication

Communication is not meaningful if one is not translating the original language of humans to the one that computers understand. This serves as the foundation of the communication project. The goal is to make computer understand what is spoken to it in its own language. Computer is to hear, process, understand, decide, and react. Communication otherwise is not done.

Communication Vocabulary English Grammar Object Oriented Programming Classes Methods And Properties Phonetic Voice Objective Discovery Reasoning Bayesion Network Objective Sensor Neural Network Brain Translation