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Artificial Intelligence as a Futuristic Technology

Artificial Intelligence as a Futuristic Technology

CEO Hiroaki Kitano at Sony Computer Science Laboratories said in an interview that the firm plans to release a product or service derived from collaboration with Cogitai (California-based startup) as early as next year. “We are considering various options, including a robot,” he said.

The famous researcher Alan Turing said during a lecture in 1951,
“It seems probable that once the machine thinking method had started, it would not take long to outstrip our feeble powers.They would be able to converse with each other to sharpen their wits. At some stage therefore, we should have to expect the machines to take control.”


This affirmative picture of Artificial Intelligence certainly gives us a hope of seeing a hollywood Sci-Fi in reality. The progress can also be seen when various forms of AI like- specified and personalized search engine results, intelligent personal assistant software – Siri, Google Translate, vehicle navigation systems, chatbots, diverse robotics enhancements etc are used as something in ‘common’.

Not only this, but biggies like Google and Sony are also taking interest in its implementation and progress, for instance, there are latest updates about,

  1. Google making virtual reality and artificial intelligence, or “machine learning,” as the focal points,this spurred speculation that Google is getting ready to release a virtual-reality device to compete with Facebook’s new Oculus Rift headset, as well as the Samsung’s Gear VR and the Vive from HTC and Valve.
  2. Technology consulting company Accenture along with IPsoft forming a new business unit around the Amelia AI platform. It is designed to accelerate client adoption of artificial intelligence

All these initiations are the sign of progress in the field of AI. But for knowing where it is going, we need to understand, where it wants to go…

AI Aspirations

The ultimate goal of AI is to create an intelligent machine that can compete human brain. However, to make this possible a thorough study of complex behaviours like, reasoning, comprehension of intricate ideas, quick learning etc. is necessary. These are the building blocks for creating an artificially intelligent brain, therefore, we need to study them individually and in correlation:

Immediate Judgement

AI tries to reach this goal through combination of:

  • Autonomous embodied agents (3D body) that can interact with the surroundings
  • Sensorimotor skills, i.e, the ability to perceive environment and respond accordingly.
  • Neural Networks, like human brain that compute values from inputs and present the required results; machine learning; pattern recognition; adaptive nature.
  • Statistical Approaches (mathematical approaches to specific problem resolutions).

Future Planning

We think about the future before acting. We sharpen our skills to get good jobs, we save for tomorrow and preserve for the progeny. We always think of potential future before acting.

This has always helped our species to survive. Therefore, intelligent agents in any machine should be capable of doing predictive analysis, so that they can draw an action plan to follow… with a probable insight of results and perform in a manner which will maximize efficiency (value) of the process.

Machine learning

Machine learning is the construction and study of algorithms which allow AI systems to make predictions and decision based on data input and knowledge acquired through it.
It can be focused on:

  1. unsupervised pattern recognition in streams of input (for example, defining spam mail from non-spam mail in electronic mail systems);
  2. supervised (programmed) classification and relation formation in the input data (for example guiding spam and non-spam mail into different categories in the system).

Machine learning is used in various spheres of information technology such as spam filtering (mentioned as an example above), optical character recognition, search engines personalization, computer vision and data mining (predictive analysis).

Further enhancement of machine learning algorithms should attribute to the overall computational intelligence of machines.

Natural Language Processing

This is the most important and complex aspect of AI to develop. The Turing test is based on the ability to converse- the machine that will be able to speak and understand the context of the conversation and respond accordingly will be characterized as an intelligent entity (because it involves abstract properties – social intelligence, knowledge, perception, problem-solving, etc.).


Goals in robotics combine engineering with artificial intelligence studies and revolve around questions of:

  1. Object manipulation
  2. Navigation
  3. Localization
  4. Mapping
  5. Motion planning

Way to Fulfill them

There are numerous problems obstructing the success of AI. However, by implementing various methods/ tools these can be successfully addressed:

Search and Optimization Method

When we have a destination to reach and various paths to reach there (as a result of our search), what we do is analyze which will lead us optimized solution, i.e which path will lead us to the destination safely and in relatively less time. Similar is the case with AI, after searching for numerous plausible solutions we need to cut off those which are not giving us optimized results. Choosing an optimal pathway can be an intelligent solution.Reasoning, planning and robotics algorithms are created with the assistance of search techniques based on optimization.

Logical Method

Logic is used for solving problems regarding automated planning and machine learning, as well as those of logic programming. It is used for determining validity through true/false attribution, expressing facts about objects, their properties and relations which is essential for ontology in knowledge representation.

Also there are other methods to consider…like, probability algorithms for filtering and predictive analysis of streams of data, classifiers and statistical learning method, artificial neural networks, programming languages (differ according to specific needs of a sub-category of AI).

Successful Implementation of AI


IBM has achieved tumultuous success in the field of AI by setting examples like, Deep Blue chess-playing algorithm and the complex Watson system.

Deep Blue chess-playing algorithm efficiently processed enormous predictive analysis by clear formulation of goals. The best part is that the computer handled it autonomously, it was optimized in such a way that even a chess expert failed to win over.

The Watson rose as a most thriving achievement as it showed intelligence in natural language. This real- time question and answer algorithm managed to reason correct answers and generate them in natural language- it won the jeopardy while operating offline.

Currently, IBM is focused on cloud migration services implementing their algorithms in a cloud-based environment and creating databases for health-care, business and education.


Google has been using artificial intelligence features for personalization and specification of their search engines, developed Google Translate which is a sufficient natural language processing and generation tool (aside from its lacking in matters of context and sub-symbolic meanings) as well as implemented a neural network strategy in management of their immense databases. These neural strategies are designed to recognize patterns and make decisions upon them extremely fast. Also, the machine learning algorithms are included which means that systems learn through experience and as such perform more effectively.

Facebook Facebook is a universe of information (data): friends lists, pages liked, groups joined. In order to customize the user experience, Facebook implements artificial intelligence. It uses AI to understand the taste of particular user by recognizing behavioural pattern and offers him choices accordingly. They are also heading towards creating an intelligent agent, who will interact with the users and provide them them the most valuable information instantaneously.


Taking into consideration Moore’s theory, we can predict that the depiction of science fiction is the future, especially if we are taking the complexity of the objectives into consideration. Though it would not be a smooth road to travel, as there are many issues which need to be solved to explore the potential of AI, still the progress is happening which is certainly going to create unseen magic.

In business, it will enable strategies designed for individual users – increasing their satisfaction and profit generation for the enterprise. It will have even more far-reaching consequences in medicine, sustainable economies, poverty reduction and education. We should only hope that the progress will always serve its altruistic purposes.

You may also like to read: Prologue to Artificial Intelligence