TAKO and the Evolution of AI Chatbots: What Lies Ahead for Technology?

AI chatbots have changed the game of businesses. Modern chatbots can have a human conversation. The AI chatbots are equipped with deep learning and natural language processing. The new technology can now communicate just like humans and solve business problems. The evolving and present businesses must explore the world of AI chatbots to understand the potential development that lies ahead. Recently, AI chatbots, such as ChatGPT, BARD, etc., have become popular. However, a new chatbot is ready to take over the AI world. TikTok is now testing its own AI chatbot, known as ‘TAKO.’ In this blog post, we will explore more about TAKO and the evolution of AI chatbots, their capabilities, and their exciting possibilities for the future.

What is an AI Chatbot?

An AI chatbot is software that stimulates human communication. Such software is frequently used for customer services and sales. However, recently, the concept of an AI chatbot has changed altogether. Now, you can have a human conversation with an AI Chatbot about anything. The responses are prompt and accurate, and it feels natural and personal. The e-commerce sites also use bots to provide product descriptions to customers. AI chatbots are more like ‘do it all’ software, whether it is about the B2B sales process or learning how to code.

What is TAKO?

TAKO is a newly built AI software exclusively built by TikTok. Currently, TAKO is in a testing phase in selected markets. TAKO is like other AI chatbots that allow you to ask questions. However, this bot is for the Tiktok application only.

According to the sources, TAKO is a built-in feature of Tiktok and will appear on either side of the interface. It is more of a convenient feature that will allow the user to ask questions about the video and discover new videos per the user’s recommendation.

Suppose a user is watching a video of Meghan Markle’s wedding; TAKO might suggest that users ask, “What is the status of Meghan in the royal family?” or maybe users can ask TAKO to recommend videos on a particular topic-like, how to make your room smell fresh. The TAKO would respond with a list of links to videos per the topic. The user can click on the link that will lead to the content.

How does an AI Chatbot work?

AI chatbots are artificial intelligence software that offers human-like conversations. AI chatbots have revolutionized how businesses work; managing customer services and after-sales queries is much easier. Here is a general breakdown of how an AI chatbot works.

Data Collection:

The first step is to gather the information and train the chatbot as per the collected data. The data depends on the integration of the software. Typically, the data includes conversations, queries, descriptions, and responses.

The collected data is broken down and processed as per the standard format, and it is transformed into a suitable format that performs well with the AI chatbot. Moreover, the data responses are also as per the queries.

Training:

The collected data is refined and used to train the chatbot. Different methods exist to train the chatbots, such as machine learning algorithms, transformer models (GPT), and recurrent neural networks (RNNs).

Deep learning models like GPT 4 (Generative Pre-trained Transformer) are trained to understand the core context of a conversation and the input it receives.

Natural Language Understanding (NLU):

NLU is a part of chatbot training. It helps the chatbot to understand the input of the user. Sometimes, the user describes the issue in bits and pieces; NLU understands the text and reforms it for the bot to understand.

The NLU technique inspects the text input, understands the keywords and user intentions, and maps the input for the chatbot for accurate response.

Context management:

Coherent responses demand the context and history of the conversation. Chatbots work on accurate responses and the ability to give human-like responses. However, there is a whole system behind an AI chatbot that helps in establishing context.

The software has techniques like memory networks and hidden states that update information from past interactions. Hence, the chatbot gives responses based on conversational history.

Response generation:

Once the context is maintained, the chatbot generates an appropriate response. Usually, the input is broken down into pieces, creating a barrier to getting an accurate response.

NLG techniques use predefined templates and help the chatbot to generate responses based on the training data and the conversational history.

Deployment:

Once the chatbot is done with the training, it is deployed on a server that allows it to interact with the users in real time.

The integration is done on various platforms, such as websites, applications, and software, providing a seamless conversational experience.

Updates:

Chatbots require continuous learning based on user interactions, feedback, and updates. AI has changed the game for businesses; new software is launched every other day.

To give an appropriate response, the chatbots need to be updated with information now and then. This process helps refine the chatbot’s performance and increases the efficiency of responses.

The Evolution of AI Chatbots:

Over the years, the AI chatbots have evolved and gained popularity. With the advancements in machine learning and NLP technologies, businesses can witness a variety of AI chatbots that are more advanced and real. Let’s explore more about the evolution of AI chatbots.

Rule-based chatbots:

The early stage of chatbots is followed by a predefined set of rules. The rule-based chatbots had limited capacity to take commands. This type of chatbot was used for basic customer support interactions.

Rule-based chatbots recognize certain keywords and phrases and respond accordingly with predefined instructions. The ability of such chatbots is limited, and they cannot handle complex queries.

Pattern Matching:

A more advanced technique is used by chatbots to understand the specific set of phrases and keywords to generate accurate responses.

For example, integrated into a chatbot, pattern matching would give accurate responses about product inquiries, descriptions, cancellation requests, etc. However, the chatbot cannot expand the ability to give responses like a human in this approach.

Machine learning:

This is the most common approach, and integration of NLP and machine languages allows the chatbot to understand the context of the conversation and give output as per the input.

Machine learning and NLP simulates real-time conversations and allows the chatbot to handle complex queries.

Generative pre-trained transformer (GPT):

GPT models are taking over the world, transforming the game of AI Chatbots. The GPT models are based on pre-trained architectures that allow the chatbot to learn the statistical patterns and structures of languages.

The GPT models are more accurate and can generate coherent and contextually appropriate responses.

Multi-modal capabilities:

The world of AI chatbots is revolving rapidly. The chatbots are integrated with multi-modal capabilities, and now they can generate responses in various formats, such as images and voice.

The multi-modal chatbot allows the user to engage through different channels and platforms, which enhances the overall user experience.

As technologies advance, users can expect further updates and developments in AI chatbots. Improved languages, context awareness, and seamless integration are taking over businesses’ human efficiency.

Looking into the future

The world of AI is updating every single day. Innovations in chatbots enhance the efficiency of the responses. TikTok will also release their built-in app chatbot ‘TAKO,’ currently in the testing phase. The platform is already integrated with an algorithm smart enough to suggest preferred videos to users. TikTok app combined with a chatbot, the suggestions will become more precise and accurate. TikTok is a widely used app, and individuals spend hours browsing videos on TikTok; having a chatbot in the app can make it the main search engine for internet users.

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