Qualcomm incorporated (20240126987). DECISION MAKING AS LANGUAGE GENERATION simplified abstract
Contents
- 1 DECISION MAKING AS LANGUAGE GENERATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DECISION MAKING AS LANGUAGE GENERATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
DECISION MAKING AS LANGUAGE GENERATION
Organization Name
Inventor(s)
Roland Memisevic of Toronto (CA)
Mingu Lee of San Diego CA (US)
Sunny Praful Kumar Panchal of Toronto (CA)
DECISION MAKING AS LANGUAGE GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240126987 titled 'DECISION MAKING AS LANGUAGE GENERATION
Simplified Explanation
The abstract describes a method involving a pre-trained language model to generate an output language stream based on a previous language stream input. It then detects well-formed actions in the output stream, performs operations in response to these actions, appends the results back to the output stream, and repeats this process until a termination condition is met.
- Explanation of the patent/innovation:
- Utilizes a pre-trained language model to generate an output language stream. - Detects well-formed actions in the output stream. - Performs operations based on these actions. - Appends the results back to the output stream. - Iterates the process until a termination condition is satisfied.
Potential Applications
This technology could be applied in: - Natural language processing systems - Chatbots and virtual assistants - Automated content generation
Problems Solved
- Streamlining language processing tasks - Enhancing automation in various applications - Improving efficiency in generating and responding to language inputs
Benefits
- Increased accuracy in detecting and responding to actions - Automation of language-based operations - Enhanced productivity in language processing tasks
Potential Commercial Applications
Optimizing language-based customer service interactions
Possible Prior Art
- Existing language processing systems - Previous methods of automated content generation
Unanswered Questions
How does this method handle complex language structures and nuances in the input and output streams?
The method's ability to handle complex language structures and nuances is not explicitly addressed in the abstract. Further details on the model's capabilities in processing intricate language patterns would provide a clearer understanding of its effectiveness in real-world applications.
What are the potential limitations or challenges faced when implementing this method in different environments or industries?
The abstract does not mention any potential limitations or challenges that may arise when implementing this method in various environments or industries. Exploring the scalability, adaptability, and compatibility of the technology in different settings would shed light on its practicality and feasibility beyond the initial concept.
Original Abstract Submitted
a processor-implemented method includes receiving an input comprising a previous language stream, and generating an output language stream by a pre-trained language model, based on the input. the method further includes detecting a well-formed action based on patterns in the output language stream, and performing an operation, by an environment, in response to detecting the well-formed action. the operation returns a result. the method also includes appending the result to the output language stream to obtain an updated output language stream. the method includes repeating the generating, with the updated output language stream as the input, the detecting, the performing, and the appending until a termination condition is satisfied.
