AI and the particular subset of machine Learning is the process of building a scientific model after discovering knowledge from a data set. It is the complex computation process of automatic pattern recognition and intelligent decision making based on training sample data. With this, AI techniques can replicate specific elements of intellectual ability and computers, as they’ve already been shown to do, will be able to solve problems in various realms.
The basic idea of AI is simple but its execution is complex. First, the AI algorithm gathers facts about a situation through sensors or human input. Then, the computer compares this information to stored data and decides what the information signifies. The computer runs through various possible action steps and predicts which action will be most successful based on the collected information. IT giants like Google, Microsoft, and Facebook have all been using AI methods in various projects which demonstrate the uncanny ability of AI to deliver sophisticated outputs. Some companies are taking this flow, meshing it with deep learning traits and predictive analysis, then manufacturing it into commercial IoT products that can learn and adapt to consumer behavior. Examples include data mining, text mining, predictive analytics and business analytics—and increasingly fully managed in the cloud.
Chatbots keep coming in 2017
One of the more popular AI-driven technologies we have seen this year, and will continue to see in 2017, are chatbots. Complicated is the interaction between human and machine via voice, yet, based on the advancements made by Microsoft, Amazon, Google, and others, we all will become more familiar with these conversational computerised agents designed to simulate an intelligent conversation with human users via auditory methods. These chatbots will continue to be driven by artificial intelligence algorithms which can recognise commands more effectively at times than a traditional search query-response from Apple’s Siri, Amazon’s Echo, or Microsoft’s Cortana.
A recent chatbot offering is from Facebook. Their Facebook Messenger app will allow retailers and news information sites to integrate bots capable of responding to user queries in the hope that any required responses will be faster than waiting to speak to a real-life support person. People can conduct a conversation on making purchases, or catch up on the latest headlines, all without interacting with a human being or needing to type. Messaging platforms are the dominant apps for the moment.
Chatbots and the job market
The economic impact of chatbots will be significant, as is the way of most massively adopted technologies. The day of businesses outsourcing projects to chatbots is just around the corner. We will see large warehouses on the edge of major cities packed with servers running chatbots carrying out responses, customer feedback and interacting in a fashion akin to call centres now. It should not be overlooked that machines do not go on strike, do not turn up late for work, and do not take sick days. As long as they have the power supply and the skilled people to maintain them, chatbots should only improve.
They may also eliminate the need for many third party apps. They also streamline our interactions with multiple parties. In a situational sense, they would allow us to find out the weather, hail a cab, shop online, all while reading a popular news feed on Facebook. Chatbots make it easier and more natural to engage with brands without a “direct marketing” feel. In summary, chatbots enable us to have deeper experiences through our Internet connected devices and allow us to experience a more satisfying ‘human’ interaction – delivered by AI.