LLM Communication Summaries for Interrupt-Free Focus Work

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Solution Overview

Problem

Workers face difficulty in staying focused on tasks due to frequent interruptions from communications, which are costly and detrimental to task completion.

Innovation Solution

A system that collects user digital activity data, tokenizes it into vectorized embeddings, and uses a large language model to generate natural language responses to intercepted communications during focused work periods, summarizing them upon completion.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If communications are presented to the user during work periods, then the user can respond to communications promptly, but the user's focus on the task is interrupted

Engineering Contradiction:

Improvecommunication response reliabilityVSAvoidtask completion efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system performs preliminary actions by collecting digital activity data and tokenizing it into vectorized embeddings before the focus period begins. This pre-processing enables rapid response generation during communications without interrupting the user's focus, as the foundational data structure is already in place.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces an intermediary AI assistant that mediates between incoming communications and the user. The AI generates draft responses based on collected digital activity data, allowing the user to maintain focus while still addressing communications through review and approval of pre-generated responses.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Speed

If the user processes communications in real-time, then communication responsiveness is improved, but time spent on non-task activities increases

Engineering Contradiction:

Improvecommunication response speedVSAvoidtime lost from focused work

Core Design Contradiction:

SpeedVSLoss of time

Solution Approach 1:

The system performs preliminary data collection and tokenization during idle periods or before focus sessions, so that when communications arrive, the AI can generate responses rapidly using pre-processed data without consuming the user's focused work time.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The AI assistant serves itself by autonomously generating communication responses based on the user's digital activity patterns and collected data, reducing the need for user intervention and minimizing time loss from focused work.

Inventive Principle:

Principle #25Self-service

3Measurement precision

If the system collects and processes extensive digital activity data, then summarization accuracy is improved, but system complexity increases

Engineering Contradiction:

Improvesummarization accuracyVSAvoiddata processing system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system replaces complex manual data processing and analysis with an AI-based natural language generation model. The AI consumes tokenized digital activity data and automatically generates accurate summaries and communication responses, simplifying the overall system architecture while maintaining high precision.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system transforms raw digital activity data into tokenized vectorized embeddings, changing the parameter representation of the data. This transformation enables more efficient processing and storage while maintaining the information needed for accurate summarization and response generation.

Inventive Principle:

Principle #35Parameter changes

4Loss of information

If the user reviews all intercepted communications, then communication understanding is improved, but focus concentration is reduced

Engineering Contradiction:

Improvecommunication context retentionVSAvoidfocused work output

Core Design Contradiction:

Loss of informationVSProductivity

Solution Approach 1:

The AI assistant acts as an intermediary that reviews and summarizes communications for the user. It provides concise summaries and draft responses based on the full communication context, allowing the user to maintain focus while still understanding essential communication points through the AI's synthesized information.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

Instead of requiring the user to review all communication details, the system provides partial information - concise summaries and key points - that are sufficient for maintaining context without the excessive action of reviewing every communication in detail, thus preserving focus concentration.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12380283B2Summarization for attention management and recall

Publication Date: 2025.08.05 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

In an approach for assisting a user to remain focused on a task, a processor collects a plurality of information regarding one or more digital activities of a user. A processor tokenizes the plurality of information into one or more vectorized embeddings. Responsive to determining that the user has engaged a focus mode, a processor intercepts one or more communications. A processor synthesizes, utilizing a large language model and the one or more vectorized embeddings, one or more natural language responses to the one or more communications. A processor transmits the one or more natural language responses to one or more originating users of the one or more communications. Responsive to determining that the user has ended the focus mode, a processor displays a summary of the one or more communications and the one or more natural language responses transmitted while the user was in the focus mode.