How generative AI revolutionized chatbots
The chatbot has been a mainstay of the internet for many years, offering some degree of human-like interaction on countless websites without the need for full-time staff. Thanks to the recent generative AI revolution however, the humble chatbot has received a big upgrade, elevating it from a simple and oft ineffectual customer service tool to a powerful conversation partner that could revolutionize the way people interact with software and information.
Generative AI offers not just unparalleled natural language processing (NLP) abilities, but also the ability to act as a type of database, storing and retrieving vast quantities of data through training and prompting. When put together, generative AI can not only elevate existing chatbots but bring forth a new class of digital assistants or copilots that can support the use of complex software or the execution of challenging tasks in complex fields.
Smarter data access
In the modern era, no matter the topic there is almost guaranteed to be a vast wealth of information available about it. Everything from professional reports to amateur anecdotes and from carefully curated documentation to public forums, it is now often more of a problem to find relevant information among everything that’s available rather than wondering if the information exists at all. This is especially true for professional software with its high degree of complexity and exhaustive documentation which can make it difficult to learn and, crucially, slow to find specific information about.
Now though, a generative AI powered chatbot could serve as a smart database of relevant information that is deployed alongside a professional application or suite of tools. The chatbot would then provide conversational access to that information rather than needing to scour documentation or tutorials, the pertinent facts are presented immediately both saving time and making the users job easier.
Having knowledge accessible through a chatbot, instead of requiring the user needing to search for it themselves, could also help solve the problem of “you don’t know what you don’t know”. This problem arises when, for example, a user is looking up a particular method to do something when a better method they simply didn’t know about exists. When querying a chatbot instead of directly searching for the information, the AI could suggest alternative methods and best practices based on its trained knowledge, making sure users learn the best and most efficient methods first, even if they never knew about them before.
Automation and interaction
The potential of generative AI chatbots isn’t limited to information retrieval either since, with appropriate training, a chatbot could be used to directly interact with the tool its supporting as well. This would allow many functions to be interacted with using NLP, allowing intuitive interactions simply by describing the desired outcome and allowing the AI to decide the approach, tools, and methods required. This could also be extended to automation’s, simply instructing a chatbot to perform a series of tasks without needing to manually perform them.
Additionally, with a broader range of training a chatbot could provide assistance in supporting areas as well, such as assisting a designer in writing code for testing or a mechanical engineer in wiring best practices during a mechanical design step. When used in this way, chatbots could serve as not just an assistant in using a tool but as a repository of knowledge across an entire company, allowing every user to have access to a knowledgeable expert in any and every field they might have questions about.
Generative AI will change the way people consume information and interact with software, allowing the entire process to become more natural. Compared to the way humans speak, think and interact with their environment, computers have always forced a much more rigid and limiting structure but now, smarter chatbots with unmatched NLP abilities will be the first step in breaking down that barrier. In the years to come, people and software will move from a strictly user and tool relationship to one of collaboration improving not just efficiency but freedom of expression as well.
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