Frequently Asked Questions about FullpathGPT (and ChatGPT in general)
The groundbreaking AI-powered ChatGPT-4 that has taken the world by storm can now be easily integrated into your dealership website in seconds with FullpathGPT for automotive.
Where does FullpathGPT get its answers from?
What is the difference between a GPT-empowered chatbot and a “regular” chatbot?
A regular chatbot typically uses a set of pre-defined rules or decision trees to generate responses based on specific keywords or patterns detected in user input. While these chatbots can be useful for answering simple and straightforward queries, they are limited in their ability to understand the nuances of human language and generate complex or contextualized responses.
In contrast, a ChatGPT chatbot uses a large language model to analyze the context and meaning behind user input and generate responses that are more human-like and nuanced. These chatbots can understand and respond to a wider range of queries including those that are complex multi-part queries, or queries that require some level of creativity or problem-solving.
Overall, ChatGPT chatbots are designed to provide a more natural and engaging conversation experience for users and will often produce better answers.
A practical example would be a question about safety (“Does the new Blazer have a safety rating? And how does it compare to the Tahoe?”), or car seats (“How many car seats can I fit in the back?”) A typical chatbot is not capable of handling this.
What is the difference between a GPT-empowered chatbot and a “human-assisted” or “manned” chatbot?
A ChatGPT-powered bot uses a large language model to generate responses to user input automatically. These bots can handle a wide range of queries and conversations with minimal human intervention, making them useful for scaling customer support, handling routine queries, and providing 24/7 availability.
In contrast, a manned chat involves a human operator who is responsible for responding to user queries and providing support. These chatbots are challenged by the fact that the human doing the chatting is almost always located offsite and is not familiar with a dealership's inventory. This leads to a poor speed of response and insufficient answers. Even when the chatbot is maintained by the dealer BDC, the BDC members are often not available to handle the chats due to other obligations, leading to a fallback to a call center or a bot.
What is the GPT in Chat GPT?
GPT is a type of language model that uses deep-learning techniques to generate human-like text. The model is pre-trained on a large corpus of text data and can then be fine-tuned on specific tasks, such as language translation, text completion, or text classification. The GPT models are part of a family of transformer-based language models developed by OpenAI and are known for their impressive performance in a wide range of natural language processing tasks.
What is the LLM model that we are hearing about in the news?
These models are called "large" because they are trained on massive amounts of data, sometimes up to billions of words, or even entire internet contents. These large datasets enable the models to learn a wide range of linguistic patterns and nuances, and as a result, they are highly versatile. They can perform well across various natural language processing tasks, such as language translation, text summarization, sentiment analysis, and more.
Some examples of popular large language models include GPT-3, BERT, and RoBERTa, which have achieved impressive results on many language-related tasks and have received widespread attention and adoption in both academia and industry.
Can Fullpath ChatGPT Support Spanish language?
What is the difference between GPT and LLM?
GPT (Generative Pre-trained Transformer) is a specific type of Large Language Model (LLM) architecture. In other words, GPT is a type of LLM.
LLM is a general term that refers to any language model that is capable of processing and understanding natural language. These models are typically based on deep learning techniques and are trained on large amounts of text data to learn the patterns, structures, and relationships within the language.
GPT is a specific implementation of an LLM that uses a Transformer-based architecture. The GPT models are known for their impressive performance on a wide range of natural language processing tasks, such as language translation, text completion, text classification, and more.
Therefore, while LLM is a more general term that encompasses any language model designed to process natural language, GPT is a specific type of LLM architecture that has gained widespread attention and adoption due to its impressive performance on many language-related tasks.
Does the Fullpath ChatGPT send an ADF XML lead to the CRM?
Yes, FullpathGPT does this just like any chat conversion form.
Can I see the FullpathGPT transcripts?
Yes, FullpathGPT transcripts are sent with the ADF and are available on the visitor's Shopper page in your Fullpath Dashboard.
Regarding data and data policy and security, is data shared with OpenAI’s GPT4 API held on their servers?
From OpenAI's policy:
Starting on March 1, 2023, we are making two changes to our data usage and retention policies:
- OpenAI will not use data submitted by customers via our API to train or improve our models, unless you explicitly decide to share your data with us for this purpose. You can opt-in to share data.
- Any data sent through the API will be retained for abuse and misuse monitoring purposes for a maximum of 30 days, after which it will be deleted (unless otherwise required by law).
What does the implementation process look like?
Does FullpathGPT replace Website Engagement's chatbot?
For those who have purchased FullpathGPT, the ChatGPT interface will replace the native Website Engagement chatbot.
If I don’t use Website Engagement do I get all the Website Engagement features when I buy Fullpath ChatGPT?
Is FullpathGPT covered by Co-op?
It is not co-op eligible as of yet. We will provide updates as they become available!
Can I use FullpathGPT if it is not a certified vendor?
Does FullpathGPT require a new code snippet?
Can a FullpathGPT conversation be transferred over to a human chat representative?
What does reporting look like?
Reporting is the same as it is in Website Engagement.
Do other Website Engagement features continue to work?
Yes.
Do we provide customizations and support for FullpathGPT?
Does Fullpath GPT use ChatGPT 3 or 4?
Does FullpathGPT Hallucinate like other GPTs?
Why yes, it does. Let’s define what we’re talking about here. Hallucination in AI refers to the generation of outputs that may sound plausible but are either factually incorrect or unrelated to the given context. These outputs emerge from the Open AI model's inherent biases, lack of real-world understanding, or (and in our case, most probably) from training data limitations around vehicle shopping, selection, and buying processes and interactions. In other words, the AI system "hallucinates" information that it has not been explicitly trained on, leading to sometimes unreliable or misleading responses. This problem is NOT unique to FullpathGPT, rather it's a problem all LLMs struggle with when trying to interact with users in a question and answer format.
There’s no easy way to fix this. We can, however, allow the system to learn and improve over time. Additionally, we can provide bumpers and guides for how the FullpathGPT can navigate specific scenarios or responses (see above regarding Custom Instructions).
A disclaimer to this effect is always present at the beginning of the chat interaction.
What if FullpathGPT provides inappropriate responses?
Lastly, our product and development teams are working on incremental changes weekly. We are using a method called prompt hardening which is assisting us in ensuring FPGPT is more reliable and controlled in the outputs. The goal of prompt hardening is to mitigate potential risks associated with AI models by reducing their sensitivity to certain types of input or by constraining their behavior. Prompt hardening is an ongoing process that requires continuous monitoring and refinement to address emerging issues and concerns.