Digital Engagement : The Right Information in Context

Need for Artificial Intelligence

• To create expert systems which exhibit intelligent behavior with the capability to learn, demonstrate, explain and advice its users.
• Helping machines find solutions to complex problems like humans do and applying them as algorithms in a computer-friendly manner.

To understand the structure of Intelligent Agents, we should be familiar with Architecture and Agent Program. Architecture is the machinery that the agent executes on. It is a device with sensors and actuators, for example : a robotic car, a camera, a PC. Agent program is an implementation of an agent function. An agent function is a map from the percept sequence(history of all that an agent has perceived till date) to an action.

Agent = Architecture + Agent Program.

Types of Agents

• Simple Reflex Agents
• Model-Based Reflex Agents
• Goal-Based Agents
• Utility-Based Agents

Few Business Applications Using AI

Over the past few years, from healthcare to banking and finance, each sector has gone through a wave of change to bring ease to work by bringing in Artificial Intelligence. Here’s a sample applications list :

Financial organizations are building AI-driven investment advisors. Chat bots provide everything from customer service to sales assistance. Although AI is receiving a lot of visibility, the fact that these technologies all require some element of knowledge engineering, information architecture, and high-quality data sources is not well known. Many vendors sidestep this question or claim that their algorithms operate on unstructured information sources, "understand" those sources, interpret the user query, and present the result without predefined architectures or human intervention. That very well might be true in certain circumstances, but most applications require a significant amount of hard work on the part of humans before neural nets, machine learning, and natural language processors can work their magic.

AI BRAIN TO BUILD INTELLIGENT SYSTEMS FOR AUTOMATED DECISION MAKING

Today's data driven world moves faster than ever. From consumers, products, businesses, operations to revenue, all depends on the intelligent systems that are capable of learning the activities and building insights for better strategy, experience and delivery.BigSun Technologies is built on life-science focused technologies that not only understands insights but also is able to take decisions as 'like humans' on behalf of businesses for better real time personalized consumer experience, automated decision making, improving performance and efficiency with increasing in conversion and revenue. The businesses are able to know more, and faster in real time. It's more beyond Artificial Intelligence and Data Analytics - It's true 'AI Brain'.

BigSun focuses on product innovation and new area researches with help of its technology and research firms. It helps companies to build intelligent systems and process with boosting their results.

Human : Change the way People and Machine Interact : The emerging technologies such as AI will help in improving the way people live and interact around either as individual or in society.People will be able to focus on more creative and interactive work than doing clerical work, focusing on the 20 % of non routine tasks that drive 80% of value creation.

Process : Reimagine intelligent systems : The emerging technologies such as AI will reinvent end to end businesses processes and the way businesses interact with its customers or products or services or vice versa.This will remove limitations such as time and distance for businesses and humans do. The automated decision making focused “AI Brain “ will empower processes to improve themselves.

Data : Unlocking the hidden insights out of the data : Data is the new commodity in the business domain. The learning will become more transactional and adaptive in coming future to deliver and identify new insights.

Other Emerging Technologies : Analytics and Insights , Contextual Intelligence,Digital Experiences , Actions and Decisions , Genomics Science , Deep Personalization , NeuroScience , Machine Learning , NLP and Machine Learning , etc.

Organizations are in a never ending cycle of improving their digital means of engaging with customers. Initiatives include improving personalization of the user experience by presenting relevant content ,tuning search results what the user is interested in and improving the effectiveness of offers and promotions. In each customer case , the means of engagement is providing a relevant piece of data or content (in the form of sales , next best actions ,products for cross sell and upsell,answers to questions and so on ) at exactly the right time and in the context that is most meaningful and valuable to the user. This is done by interpreting the various signals that users provide through their current and past interactions with the organizations.These signals include prior purchases , real time click stream data , support center interactions , consumed content , preferences , buying characteristics , demographics , firmographics , social media information that is captured by marketing automation and integration technologies. Here ,for example the search signal is a recommendation engine . The signal is the search phrase and the recommendation is the result set.

AI will help leaders drive innovations to unlock trapped value — in the core businesses and beyond. The future of AI promises a new era of disruption and productivity, where human ingenuity is enhanced by speed and precision.

Research in AI has focussed chiefly on the following components of intelligence: learning, reasoning, problem-solving, perception, and language-understanding.

Features of AI :

Machine Learning : ML give machines the ability of reasoning, problem solving and perception. They can learn on their own from past experience and improve over time. Machine Learning has found its applications in healthcare, e-commerce, spam detection and many more.

Deep Learning : DL is a subset of Machine Learning. Deep Learning is based on the making artificial neural networks that simulate the human brain. This neural network enables machines to analyze, understand and take decisions on their own.

Advantages of AI

Efficiency: Artificial Intelligence machines have a high level of efficiency. As we all know that machines are built with algorithms that enables AI machines to become less prone to error.

Repetitive jobs: Artificial Intelligence machines can replace humans from monotonous jobs that humans find boring. This is because machines are emotionless and do not get bored.

No breaks: Artificial Intelligence Machines takes less or no breaks as compared to human counterpart.

External Factors: These machines can perform in any environment or place where humans cannot reach. For example inside petroleum pipes to check leakage.They can work at any temperate range as high as 1290 degrees to as low as - 47-degree Celsius.

Adaptability: Artificial intelligent machines have the ability to adapt to any environment. Artificial Intelligence can be classified into two types. Narrow AI and Broad AI. Broad AI can perform a vast variety of task on the basis of an environment.AI is helping in making smarter machines , smart TV , smart homes ,etc.

Artificial Intelligence is helping human race and doing great things and achieving bigger targets. Nowadays, AI has become an integral part of everyday lives. It has become a boon to many industries like healthcare, finance, marketing etc. So, it becomes necessary for various industries to keep pace with the latest trends in Artificial Intelligence to maximize benefits from it.

Few Business Applications Using AI

• Machine Learning
• Robotics
• Image and Speech Recognition
• Natural Language Generation.

AI permeates many of the apps and services we use on a daily basis fulfilling roles from image classification to algorithmic trading strategy to predictive maintenance. Using AI in your company makes it easy to focus on specific aspects of your operations where intelligent features may quickly yield a tangible benefit. In many cases,it only takes one or two smart apps to save real time , streamlining existing processes and enabling data driven decision making on a faster time lines.

10 Steps to adopting Artificial Intelligence to your Business :

• Get Familiar with AI
• Identify the problem you want AI to solve.
• Prioritise Concrete Value
• Acknowledge the Internal Capability Gap
• Bring In Experts and Set up a Pilot Project.
• Form a task force to integrate data
• Start Small.
• Include Storage as part of your AI plan.
• Incorporate AI as part of your daily tasks.
• Build with Balance

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