Will we one day have robots that actually talk to us like in the movies?

Creating robots that talk to humans naturally, like in science fiction movies, requires strong artificial intelligence and natural language processing. Current technology allows computers to give ready-made answers based on data, but creating robots that actually think is still a challenge.

 

Many science fiction movies, from Star Wars to Transformers, have featured robots. In reality, many robots have been developed to make our lives easier by helping us clean or performing more sophisticated surgeries. However, the robots we see in movies are very different from the ones we see in real life. In the movie Transformers, there are many scenes where the main character and the robot have a conversation. In every robot movie, there is a conversation between the robot and the protagonist. To have a conversation, you basically need to understand what the other person is saying and respond accordingly.

‘A’ : “Have you eaten?”
‘B’: “I’m going to school now.”

In the above example, ‘A’ and ‘B’ are speaking to each other, but they’re not having a conversation. Conversations are very different from simple speech. It’s not just about sending and receiving messages, it’s about conveying your thoughts to the other person. The fact that we see so many scenes like this in movies reflects our dream of talking to robots. Artificial intelligence is the discipline needed to create thinking machines that can communicate with humans.
There’s probably no one who hasn’t heard the term artificial intelligence. However, few people know exactly what it is. Artificial intelligence refers to intelligence created by humans or other intelligent beings, or artificial intelligence. There are two main types of AI: strong AI and weak AI. Both are based on computers and create artificial intelligence, but the former can actually think and solve problems, while the latter cannot. In this article, we’re talking about strong artificial intelligence, which is what we need to create robots that can talk to us.
Some philosophers have debated the philosophical underpinnings of artificial intelligence, which is the feasibility of implementing human intelligence or consciousness in a non-bodily machine. The Turing Test is the most famous experiment that supports the idea that AI is possible, and the Chinese Room is a counter-example.
The Turing Test was conducted to answer the question, “Can machines think?” and argued that “if a response from a computer is indistinguishable from a human response, then the computer can think.” The idea is that if a human observer cannot distinguish between a machine’s and a human’s responses, that is, if the machine succeeds in making itself look like a real human, then it should be considered intelligent.
On the other hand, the “Chinese Room” experiment shows that just because a computer responds, it doesn’t necessarily mean it’s thinking. In a nutshell, the experiment involves putting a non-Chinese speaker in a room with a writing utensil and a list of pre-made Chinese questions and answers. The person inside the room writes the questions in Chinese, and the person outside the room writes the answers in Chinese (and draws them out verbatim) according to the prepared response sheet. If you look at this from the perspective of the person outside, you can see that you have communicated with the person inside because you have received an answer to your question. However, in reality, the person inside did not think about it, but simply drew a picture according to the given table. From this, it follows that even if a question is answered perfectly, it cannot be assumed that the person inside has derived the answer to the question through his or her own thinking. In other words, even if there is a machine that can answer questions, the Turing test cannot determine whether it has intelligence. As you can see, the question of whether machines can think has been hotly debated for a long time.
In order to answer the question of whether a machine can think, it needs to be able to understand the sentence. The technology needed to do this is machine learning. Machine learning is exactly what it sounds like: the ability of a computer to learn, that is, to execute behaviors that are not defined by code. Because humans can learn, we have the ability to continually expand our knowledge, understand new things, and adapt to change. Machine learning attempts to equip computers with these human learning capabilities, which means that in order to teach a computer to understand a sentence, it first needs a lot of data. Big data is used to store and manage large amounts of data in databases that contain information about how to answer certain questions, and data mining techniques are used to systematically and automatically find statistical rules or patterns in large amounts of data. In this way, it is possible to answer a given question.
In this way, computers and humans can talk to each other using data that is already available. However, if you ask if a computer can “think,” it probably can’t, depending on how you define it. It’s hard to process data that doesn’t exist. Babies sometimes use the word “is” to combine the words “is” and “is not”. But computers can’t do the same thing. Of course, with today’s technology, you can beat a world champion in chess, and you can win a quiz show. However, in chess, we have a database of all possible moves up to 10 moves ahead, and we use them to play, and in the case of a quiz show, we hear a question, analyze the sentence in the same way as above, and then search the database for something related to it to find the correct answer. With current technology, it is not possible to say that a machine “thinks” like a person, as it simply analyzes a large amount of data to achieve these results. However, just as we have gone from using a flip phone to using a smartphone in a few years, I hope that one day we will be able to talk to robots.