Google Patent Signals Interest in Small Chatbots Amid Language Model Craze

Google wants to make chatbot development easier with its latest patent.

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Photo via U.S. Patent and Trademark Office

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Google wants to make training a chatbot as easy as small talk. 

The company is seeking to patent a system for chatbot development using “structured description-based” techniques. Google’s tech basically allows a user to create a fine-tuned chatbot for specific tasks using just natural language inputs. 

Google’s system starts off with an AI model “utilized in conducting generalized conversations,” and relies on user inputs to fine-tune it. It may map certain inputs as different dialog states, such as questions, responses, or transitions, and a user can instruct the chatbot to respond to those accordingly. 

For example, if a user were building a chatbot that could answer questions related to a business for their website, the user could instruct it to do things like provide store locations and hours, answer questions about inventory, or confirm order statuses by only using simple explanations. 

Google noted that, in some examples, these chatbots can be fine-tuned or generated in an “on the fly” manner in response to “unstructured free-form natural language input.” Meaning, if the developer notices a mistake or unwanted output, it can be easily amended with natural language instruction. 

“As a result, the chatbot can be generated and deployed in a quick and efficient manner and for conducting the corresponding conversations on behalf of the user or an entity associated with the user,” Google said in the filing. 

Google noted that this system can also be used to train voice-based conversational AI used over “phone calls or locally at the client device.” 

Big Tech firms are constantly looking at ways to make their AI models bigger and better. And as it stands, large language models are the subject of this effort, with Google, Microsoft, Meta, and OpenAI all feeding their own ever-growing chatbots as they strive for artificial general intelligence.

While these language models have incredible capabilities, they also face significant challenges — one of which is the sheer cost. DeepMind CEO Demis Hassabis warned earlier this year that the Google subsidiary may spend more than $100 billion developing AI. Meta and Microsoft, meanwhile, warned investors of rising expenses related to this development in their recent earnings reports. 

Additionally, these models present data security issues and suck up tons of power. And despite the tech industry’s fascination with large language models, the average enterprise doesn’t need a hundred billion parameters to achieve a functional chatbot. 

Patents like these, however, may hint that tech firms are looking at ways that the average business or enterprise may get use out of AI without having to hire a software development team, quickly training a conversational AI agent on any topic or domain with simple, natural language instruction. Google’s tech could offer a no-code solution to AI development that’s far less resource-intensive or expensive than building on top of a massive large language model. 

Plus, Google isn’t the only company that seems to have this idea: JPMorgan Chase and Oracle have also sought similar no- and low-code AI patents, signaling a broader interest in getting AI into the hands of more than just developers.