Simulate human conversations with AI

Conversational AI essentially simplifies demand

The advent of technology has resulted in the development of several products that have automated manual tasks, making them easier to use, helping to build profitable businesses, and making services accessible to everyone. One of these products is the use of artificial intelligence to simulate human conversations. Also known as conversational AI, this is a subfield of artificial intelligence that deploys machine learning to initiate a conversation, which is like a conversation between humans because it is natural and personalized. The product gained worldwide attention in its early days due to its engagement capabilities and impressive pace of interaction. Conversational AI simplifies demand in its essentials to identify people, actions, and objects.

How it works

There is two-way interaction between a computer and a human due to Natural Language Processing (NLP), which leads to automated conversation through messaging apps, voice assistants, and chatbots. Nowadays, conversational AI is adopted by industries across industries and integrated into their platforms to provide 24/7 support to users without human agents. The origin of conversational AI can be traced back to option menus for users such as “cancel my order”. But today we have conversational AI that answers everything from messages to calls.

The far-reaching tool enables people to rethink the way we integrate information, analyze data and use the resulting information to improve decision-making. AI systems can learn and adapt as they make decisions. For example, ConveGenius Edu, a social edtech company adopted the chatbot-based learning model by integrating WhatsApp APIs into their solution. This technology has made the teaching and learning process so easy by eliminating the reliance on concrete infrastructure. Conversational AI built into the platform helps push every student towards personalized learning paths. The AI-driven algorithm is designed to connect students with the most relevant content. Additionally, teachers have their own version of chatbots that gives them access to student data. This allows them to map and shape the learning trajectories of their students while assessing their individual learning outcomes.

In the automotive sector, semi-autonomous vehicles have tools to inform drivers and vehicles of upcoming traffic jams, potholes, highway construction or other possible traffic obstacles. Cars can benefit from the experience of other vehicles on the road without human intervention, and all of their “experience” gained is immediately and fully transferable to other similarly configured vehicles.

Another striking example is that of the stock exchanges, where high frequency machine trading has replaced much of human decision making. People submit buy and sell orders, and computers match them in the blink of an eye without human intervention. Machines can spot trading inefficiencies or market deviations on a microscopic scale and execute trades that make money as directed by investors.

Advantages and disadvantages

Since every positive side has a darker version, simulating human conversation via AI also has some drawbacks such as high cost of creation, unemployment, emotionless interaction, and original thinking. However, AI interaction tools are trained with a set of data. The larger the dataset, the better the services. So if you can train your device to express emotions, it can simulate the same ones. But it is also a challenge to provide machines with quality and well-labeled data to identify them quickly. Another challenge is to explain the capacity. When we are given the rationale for the decision, it is easier for us to assess how well we can trust the model. Likewise, AI-based interactions are biased as they make decisions based only on available data. It’s also difficult to pinpoint where something went wrong after an AI system made a mistake.

Future prospects

AI systems will further improve the delivery of chatbots, virtual agents, digital assistants, etc. in the future with more advancements. According to Evaluate reports, the global conversational AI market will reach $ 32.62 billion by 2030 at a compound annual growth rate (CAGR) of 20% between 2021 and 2030. The increasing demand for human interactions based on AI is driving the growth trend. Conversational AI reduces the scope of human error. Some of its many benefits include risk taking, 24/7 availability, help with repetitive tasks, digital support, faster decision making, and more.

In summary

Nevertheless, at present, artificial intelligence is one of the most promising new technologies shaping the future. AI is disrupting business today, and it’s the AI ​​that has the most impact. It improves communications with customers, thereby reducing costs. It also helps build brand loyalty as well as personalization. AI is everywhere. AI is here to stay.

Author

Jairaj Bhattacharya, co-founder and managing director of ConveGenius

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Analytics Insight is an influential platform dedicated to insights, trends and opinions from the world of data-driven technologies. It monitors the developments, recognition and achievements of artificial intelligence, big data and analytics companies around the world.

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