Understanding conversational AI: How does it work?

In a world where artificial intelligence (AI) is playing an increasingly important role, it is essential to understand how it works and its applications. Conversational AIs, such as ChatGPT, Google Gemini, Claude, or Mistral, are often perceived as mysterious and powerful tools. But how do they really work? In this article, we break down their operating mode, capabilities, and limitations, as well as the best way to interact with them.

How Does a Conversational AI Work?

Conversational AIs are based on deep learning models using artificial neural networks called Transformers. They are designed to understand and generate natural language based on countless text examples from the Internet. Their operation can be divided into several key steps:

1. Model Training

   A conversational AI is trained in several phases:

   • Pre-training: It ingests enormous volumes of text from books, articles, forums, and other public sources to learn the structure of language and how words are linked together.

   • Supervised Fine-tuning: Human annotators provide examples of correct conversations to guide the model.

   • Reinforcement Learning from Human Feedback (RLHF): The model generates several responses, and humans rank these responses based on their quality. Then, a reinforcement algorithm helps the model prioritize the best responses.

2. Understanding and Generating Text

   When a user asks a question, the AI performs the following actions:

   • Tokenization: The text is first divided into "tokens" (small segments of words or characters) to be processed numerically.

   • Contextual Analysis: It uses its Transformer architecture to analyze the context, identify intentions, and predict the most probable words to follow.

   • Response Generation: It produces a response by choosing the words with the highest probability based on the conversation context.

   • Filtering and Adjustment: Predefined rules help avoid offensive, inaccurate, or non-compliant responses.

3. Learning and Updates

   Although these models cannot learn directly from individual conversations, they are improved through user feedback and regular updates from their developers. This allows for the correction of biases, improved relevance, and the addition of new capabilities.

   
   

How to Interact Effectively with a Conversational AI

To obtain precise and useful responses, here are some tips:

• Be Clear and Precise: The more detailed your question, the more relevant the response will be.

• Use Examples: Providing context helps refine the response.

• Ask Open-ended Questions: They allow for more in-depth information.

• Request Reformulations: If a response is unsatisfactory, ask for a reformulation or more details.

  
  

Comparison of Major Conversational AIs

There are several conversational AIs on the market, each with its own specificities:

• ChatGPT (OpenAI): An advanced and versatile model used for various tasks such as writing, analysis, and coding. Its operation relies on regular updates and improvements based on user feedback.

• Google Gemini (formerly Bard): Developed by Google, this model is connected to Google's search services, allowing it to access real-time information.

• Claude (Anthropic): Focuses on safety and alignment with human values to reduce biases and unwanted behaviors.

• Mistral AI: A European alternative distinguished by its open-source approach, allowing businesses and developers to adapt it to their specific needs. It emphasizes models optimized for efficiency and transparency.

These differences influence how these models are used and their relevance based on specific needs.

The Impact and Future of Conversational AIs

Conversational AI is already transforming many fields, including marketing, communication, and customer service. As technology advances, these tools will become even more intuitive and personalized. However, it is crucial to adopt responsible use and complement AI analyses with human reflection.

Conclusion

Conversational AIs are powerful tools but remain assistants. They excel in text analysis and idea generation, but their optimal use relies on well-constructed interactions and critical thinking. By understanding their strengths and limitations, you can make the most of them for your professional and personal needs.