Can You Talk to AI Like a Real Person?

And yes, you can talk with AI like it was a real person and better natural language processing (NLP) technology is helping to make this experience as seamless as possible. The effort to train AI systems of this kind demands an exorbitant amount of data — weights for OpenAI’s GPT-2 model, which powers the company’s language model (chatbot) commonly produce in a range far beyond hundreds or even thousands and can run up into billions as is the case with Google. The vast amount of data is what allows the AI to understand language patterns, context and intentionality — so that responses it generates can seem more human-like. OpenAI’s GPT-4 model has been trained on a dataset size such that the resultant responses are both coherent and contextually accurate across multiple languages mimicking conversational flow (e. g. appropriate question – answer pairs etc.).

The ability of AI to carry on conversations, for instance in customer service industries, is a prime example. Evidently, the field holds a deep dependence on AI over conventional communication methods owing to conjecture that 85% of customer interactions will be handled sans human agents by 2030 as per Gartner. Amazon, IBM and other big corps deploy virtual assistants that handle thousands of customer queries in minutes helping them save around 60% on operation costs while answering your customers timely. These scores largely reflect increased customer satisfaction levels that companies provide by customizing the experience through AI which learns in real time from user behavior.

These conversational AIs are developed using industry terminologies. Intent recognition and sentiment analysis (how the AI understands why something is being said, plus matching inflection) are just as important if you want to make your bot seem human. For example, if a user says “I need help with my account” the AI recognizes an actual “intent” in this request (help) and takes action based on two important words of users’actually asking for. For example, it has built-in sentiment analysis which measures the positive or negative tones in user inputs as responses; a machine can then model its feedback to be more empathetic—a factor that humanizes AI\x80, and is crucial for UX.

The reason many believe that it may be feasible for conversational AI to eventually provide an exchange with which people can hold their own, was first pontificated on by Alan Turing where he asked the iconic question “Can machines think?” That inquiry, the basis for his Turing Test, asks if there was a response from an artificial mind that could not be distinguished from a human one. It took a while for us to catch up with this but that 1950 question Turing asked, conversational AIs are the closest they have ever been today at passing it. Still, AI can replicate some patterns of conversation only but still it has no core understanding and feelings as a human does.

AIs are not only improving communication but also shaping how AIs can handle problems that may have formerly been out of reach. People from scheduling appointments to solving technical issues, are found chitting chatting with ai for help. It also uses AI and responds as fast, sometimes even in milliseconds (real-time maybe more real than you would want it to be?), which makes it feel human-like. The likes of Microsoft, for instance, has drastically slashed waiting times among millions of users thanks to its AI-powered chatbot in the Azure support service — 70% more than human agents could have done.

There will come a time when we are talking to an AI model likely be as natural and similar (in execution, at least) compared to communicating with another human. But of course, many practical limits remain to be overcome. AI is powerful at simulating human responses to a certain extent but its language and awareness are based on data patterns, rather than an actual form of consciousness or empathy. So the question of whether we can ever talk to ai in the way that we do with another person is both techno-moral victory and philosophical curiosity — one whose contours are still emerging during this new era of intelligent devices.

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