What do you want to know?

QUANTUM JAVA SCRIPT

Get intelligent answers from QJ


Get intelligent answers from QJ. Featuring frontier capabilities in conversation, coding, reasoning, and voice.




Talk with QJS

Engage in seamless conversations with QJS Voice, experiencing natural, fluid dialogue like never before.

Never Miss a Point Again

Our AI captures every key idea, decision, and task automatically — so you can stay focused on the discussion, not the typing.

Voice Assitant

Speaker

Transcript

4:20

4:20

Anwar Raza

I’ve been reviewing the AI note summary logic, and I think it’s too focused on individual sentences rather than themes. For example, when someone discusses three points under the same topic, it still breaks them into separate highlights. It looks fragmented in the recap. I’d rather have it group related ideas together — maybe through semantic clustering

4:20

Anwar Raza

I’ve been reviewing the AI note summary logic, and I think it’s too focused on individual sentences rather than themes. For example, when someone discusses three points under the same topic, it still breaks them into separate highlights. It looks fragmented in the recap. I’d rather have it group related ideas together — maybe through semantic clustering

1:05

Sarah

Yeah, I see what you mean. Right now, the summarizer is built to trigger whenever it detects a transition phrase, like “next,” “also,” or “another thing.” It’s good for structure but bad for flow. We can change that by using context windows — say, two minutes of dialogue — and summarize based on meaning overlap rather than sentence boundaries. That way, it understands we’re still under the same topic.

1:05

Sarah

Yeah, I see what you mean. Right now, the summarizer is built to trigger whenever it detects a transition phrase, like “next,” “also,” or “another thing.” It’s good for structure but bad for flow. We can change that by using context windows — say, two minutes of dialogue — and summarize based on meaning overlap rather than sentence boundaries. That way, it understands we’re still under the same topic.

Talk with QJS

Engage in seamless conversations with QJS Voice, experiencing natural, fluid dialogue like never before.

Never Miss a Point Again

Our AI captures every key idea, decision, and task automatically — so you can stay focused on the discussion, not the typing.

Voice Assitant

Speaker

Transcript

4:20

4:20

Anwar Raza

I’ve been reviewing the AI note summary logic, and I think it’s too focused on individual sentences rather than themes. For example, when someone discusses three points under the same topic, it still breaks them into separate highlights. It looks fragmented in the recap. I’d rather have it group related ideas together — maybe through semantic clustering

4:20

Anwar Raza

I’ve been reviewing the AI note summary logic, and I think it’s too focused on individual sentences rather than themes. For example, when someone discusses three points under the same topic, it still breaks them into separate highlights. It looks fragmented in the recap. I’d rather have it group related ideas together — maybe through semantic clustering

1:05

Sarah

Yeah, I see what you mean. Right now, the summarizer is built to trigger whenever it detects a transition phrase, like “next,” “also,” or “another thing.” It’s good for structure but bad for flow. We can change that by using context windows — say, two minutes of dialogue — and summarize based on meaning overlap rather than sentence boundaries. That way, it understands we’re still under the same topic.

1:05

Sarah

Yeah, I see what you mean. Right now, the summarizer is built to trigger whenever it detects a transition phrase, like “next,” “also,” or “another thing.” It’s good for structure but bad for flow. We can change that by using context windows — say, two minutes of dialogue — and summarize based on meaning overlap rather than sentence boundaries. That way, it understands we’re still under the same topic.

Talk with QJS

Engage in seamless conversations with QJS Voice, experiencing natural, fluid dialogue like never before.

Never Miss a Point Again

Our AI captures every key idea, decision, and task automatically — so you can stay focused on the discussion, not the typing.

Voice Assitant

Speaker

Transcript

4:20

4:20

Anwar Raza

I’ve been reviewing the AI note summary logic, and I think it’s too focused on individual sentences rather than themes. For example, when someone discusses three points under the same topic, it still breaks them into separate highlights. It looks fragmented in the recap. I’d rather have it group related ideas together — maybe through semantic clustering

4:20

Anwar Raza

I’ve been reviewing the AI note summary logic, and I think it’s too focused on individual sentences rather than themes. For example, when someone discusses three points under the same topic, it still breaks them into separate highlights. It looks fragmented in the recap. I’d rather have it group related ideas together — maybe through semantic clustering

1:05

Sarah

Yeah, I see what you mean. Right now, the summarizer is built to trigger whenever it detects a transition phrase, like “next,” “also,” or “another thing.” It’s good for structure but bad for flow. We can change that by using context windows — say, two minutes of dialogue — and summarize based on meaning overlap rather than sentence boundaries. That way, it understands we’re still under the same topic.

1:05

Sarah

Yeah, I see what you mean. Right now, the summarizer is built to trigger whenever it detects a transition phrase, like “next,” “also,” or “another thing.” It’s good for structure but bad for flow. We can change that by using context windows — say, two minutes of dialogue — and summarize based on meaning overlap rather than sentence boundaries. That way, it understands we’re still under the same topic.

Summary

Sarah and Mark discussed improving the AI meeting assistant’s summarization system. Sarah noted that the current model breaks related ideas into separate highlights, making recaps feel fragmented. Mark explained the summarizer’s current logic and suggested using larger context windows to group related topics. They agreed to implement semantic clustering and link summaries to specific time ranges for better interactivity. Mark also proposed adding topic-based color segments on the transcript timeline.

Summary

Sarah and Mark discussed improving the AI meeting assistant’s summarization system. Sarah noted that the current model breaks related ideas into separate highlights, making recaps feel fragmented. Mark explained the summarizer’s current logic and suggested using larger context windows to group related topics. They agreed to implement semantic clustering and link summaries to specific time ranges for better interactivity. Mark also proposed adding topic-based color segments on the transcript timeline.

Find meaning with QJS Think

The most powerful version of Qjs. Now available with a QJS4 Heavy subscription on all platforms.

Never Miss a Point Again

Our AI captures every key idea, decision, and task automatically — so you can stay focused on the discussion, not the typing.

Summary

Sarah and Mark discussed improving the AI meeting assistant’s summarization system. Sarah noted that the current model breaks related ideas into separate highlights, making recaps feel fragmented. Mark explained the summarizer’s current logic and suggested using larger context windows to group related topics. They agreed to implement semantic clustering and link summaries to specific time ranges for better interactivity. Mark also proposed adding topic-based color segments on the transcript timeline.

Summary

Sarah and Mark discussed improving the AI meeting assistant’s summarization system. Sarah noted that the current model breaks related ideas into separate highlights, making recaps feel fragmented. Mark explained the summarizer’s current logic and suggested using larger context windows to group related topics. They agreed to implement semantic clustering and link summaries to specific time ranges for better interactivity. Mark also proposed adding topic-based color segments on the transcript timeline.

Summary

Sarah and Mark discussed improving the AI meeting assistant’s summarization system. Sarah noted that the current model breaks related ideas into separate highlights, making recaps feel fragmented. Mark explained the summarizer’s current logic and suggested using larger context windows to group related topics. They agreed to implement semantic clustering and link summaries to specific time ranges for better interactivity. Mark also proposed adding topic-based color segments on the transcript timeline.

Public beta

We're running a public beta program until the end of 2025. To kick things off, we make an early version of a next-gen model available under the name High Potentials-beta. The model offers function calling, a 128k context length, and system prompt support.

Transform text into visual realities

Super Quantum Javascript

Flerto Process

Do more with QJS.
Unlock a Qjs subscription on quantumjavascript.com.

We've just launched SuperQJS Heavy, providing access to Qjs Heavy and much higher rate limits.

Super Quantum Javascript

Flerto Process

Do more with QJS.
Unlock a Qjs subscription on quantumjavascript.com.

We've just launched SuperQJS Heavy, providing access to Qjs Heavy and much higher rate limits.

Super Quantum Javascript

Flerto Process

Do more with QJS.
Unlock a Qjs subscription on quantumjavascript.com.

We've just launched SuperQJS Heavy, providing access to Qjs Heavy and much higher rate limits.

High Potentials

Quantum Java Script

Lorem Ipsum

Copyright © 2024 – All Right Reserved

High Potentials

Quantum Java Script

Lorem Ipsum

Copyright © 2024 – All Right Reserved

High Potentials

High Potentials

Quantum Java Script

Lorem Ipsum

Copyright © 2024 – All Right Reserved

High Potentials