What is Generative AI?

I asked ChatGPT, the chatbot from OpenAI, what Generative AI is and this was the answer: Generative artificial intelligence (AI) refers to algorithms and models that are able to create new and original content. These AI systems are trained to analyze data and independently generate new texts, images, music or other creative output. They are based on deep machine learning and neural network architecture. Generative AI has applications in various fields such as art, design, music, game development and text generation. Although they are fascinating and powerful, they also pose challenges in terms of ethics, copyright and data protection.

I like the fact that ChatGPT not only highlights the advantages, but also draws attention to the challenges of the new technology. The following blog post is not about Generative AI in general, but only about how Generative AI can be used for chatbots.

What are chatbots with Generative AI?

Chatbots with generative AI or generative AI are AI systems that specialize in conducting human-like dialogues with users. Instead of retrieving predefined answers from a database, they use generative models to generate contextual and coherent answers. These chatbots analyze the user’s input text, learn from existing conversations and then generate a response based on the learned patterns and context. By using generative AI, chatbots can have more natural and flexible conversations and respond to a variety of user requests. Chatbots with Generative AI can usually answer many more questions than conventional intent-based chatbots. In addition, chatbots with Generative AI understand context and the conversations sound much more natural.

What are the advantages of chatbots with Generative AI?

Chatbots with Generative AI offer various advantages for companies and also for end users:

1. Flexibility: Generative AI chatbots are able to respond to a variety of user requests as they are not limited to predefined answers. They can generate context-related and individual answers based on their machine learning and modeling capabilities.
2. Naturalness: Generative AI enables chatbots to generate human-like responses. You can use a language that is more natural and less predictable, resulting in an improved user experience.
3. Adaptability: Generative AI chatbots can continuously learn from new data and conversations, which improves their ability to adapt to changing user needs and requirements. They can improve and optimize their answers over time.
4. Versatility: Since Generative AI chatbots are text-based, they can be used in various channels, such as messaging apps, customer support platforms, social media and more.
5. Scalability: Generative AI makes it possible to automatically scale chatbots to a large number of users and requests without the need for human intervention. This enables companies to communicate more efficiently with their customers and provide support.

What are the disadvantages of chatbots with Generative AI?

In addition to all the advantages that chatbots with Generative AI bring, they also have a few disadvantages. The following factors should be taken into account:

1. Quality problems: Generative AI models can occasionally generate inaccurate or nonsensical answers. This can lead to frustration among users, especially if the answers do not meet their expectations or needs.
2. Lack of control: Generative chatbots can in some cases provide answers that are inappropriate, offensive or undesirable. This is because they generate their responses based on the context they have learned, which may contain inappropriate content.
3. Data protection and security: Chatbots with generative AI work on the basis of data provided by users. This can lead to privacy and security concerns, especially if sensitive or personal information is included in the dialogs.
4. Lack of empathy and emotional intelligence: Generative chatbots have difficulty understanding human emotions and subtle nuances in conversation. They may therefore have difficulty responding appropriately to emotionally charged requests or offering empathetic support.

Examples of chatbots with Generative AI

Jumbo.ch ‘s latest chatbot uses generative AI to help customers find the right product.

Helvetia Insurance ‘s chatbot also uses Generative AI to answer the most frequently asked questions from customers and website visitors.

My chatbot also uses Generative AI to answer your questions about me or chatbots and ChatGPT.

How are chatbots implemented with Generative AI?

Chatbots with Generative AI can either be implemented independently by companies or with the support of chatbot platform providers. The example of Helvetia Insurance shows how companies have independently combined OpenAI’s ChatGPT API with their own chatbot.

However, there are now also the first chatbot providers that use the ChatGPT API from OpenAI and thus offer companies an easy way to implement chatbots with Generative AI.

The following is an example of how chatbot provider Dialogbits supports companies in implementing chatbots with Generative AI.

Chatbots with Generative AI from DialogBits

DialogBits is a chatbot provider from Münster, Germany, which has distinguished itself from other chatbot providers in recent years primarily through its flexible chatbot bit system and the possibilities of on-premise installations. The bit system leads to a very simple combination between chatbot and any number of (individual) interfaces. The ability to host the chat or voicebot on premise has led to Dialogbits being used primarily by companies and industries with high data protection requirements.

How do chatbots work with Generative AI from DialogBits?

Until now, companies that used dialog bits had to use intents manually. Enter dialog flows, training sets and even placeholders in the system. The chatbot could only successfully answer the users’ questions if the system had sufficient intents, training sets and answer flows. Thanks to the new Generative AI function, companies can now simply load any data sources such as websites, PDFs, Word documents and other content databases into the tool and the chatbot can first “understand” the user request with the help of Generative AI and then generate a natural-sounding answer with the help of the stored documents.

What is special about chatbots with Generative AI from DialogBits?

DialogBits is not the only provider to offer chatbots with Generative AI. But the tool offers some special features that not all providers have:

1. In Dialogbits, rule-based or intent-based dialog flows can be combined with the new functionalities of Generative AI. Companies can therefore also use classic intents and dialog trees and enrich them with Generative AI.
2. Companies can provide the chatbot with their own content, which is then available for the Generative AI function. However, it is also possible to have a reply answered directly by ChatGPT. The chatbot then uses the entire, broad knowledge of ChatGPT.
3. Companies can also specify websites as content sources. The chatbot can be set to regularly “fetch” the latest data from the website. This ensures that the chatbot’s answers are always up to date.
4. Since costs are incurred when using the ChatGPT API, only those requests should be sent to OpenAI that are really necessary. Companies can create rules for this in Dialogbits.
5. Many people immediately think of ChatGPT from OpenAI when they think of Generative AI. This is mainly due to the fact that, as of June 2023, OpenAI’s API is particularly suitable for chatbots. However, this can change quickly. This makes it all the more important that the Dialogbits Generative AI function is not limited to one language model, but that companies can also use other or even their own language models.
6. If desired, the chatbot with Generative AI from DialogBits always shows the source of the content. In this way, misunderstandings can be avoided.

What do chatbots with Generative AI from DialogBits need to consider?

The use of generative AI for chatbots makes a lot of sense in principle. The use of Generative AI in the DialogBits chatbot is particularly recommended if chatbots are to conduct dialogs as naturally as possible and draw on a broad knowledge base. Furthermore, companies should not always rely exclusively on the advantages of Generative AI, but should critically question when the use of Generative AI really makes sense. There are still use cases where classic rule- or intent-based flows make sense. This is particularly the case with flows and dialogs that are very process-driven.

How do you start a chatbot with Generative AI?

Every chatbot project starts with the creation of a good concept. I would be happy to help you with this.

I offer general chatbot and ChatGPT consultations and I also give specific workshops on the use of ChatGPT.

Feel free to send me a WhatsApp message or an email and we can find out together where you stand and what you need.