🌀I want AI to manage tasks for long-term parallel projects.

I want AI to manage tasks for long-term parallel projects.

I mean, maybe it's not for me. It's getting more and more messy.

Tasks are a complex network of interconnected units that must be divided into actionable units in order to complete a task.

The object of Neri Neri is more of a project objective

This is different from project task management.

The goal of the project is a distant goal

Now feasible tasks of the project are one meter way in front of you

What tasks are not feasible now?

Is it just a note that maybe there will be a road in that area and we will have to go that way?

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Discusses task management for long-term parallel projects with AI. He pointed out that a multi-head rooted system is not necessarily suitable for task management. He expressed the view that efficient handling of tasks does not necessarily lead to good results, and emphasized the importance of organizing the network of tasks and determining what really needs to be done. He also stated that project objectives and task management are different, and clarified the difference between them.

The Notebook and Nishio's fragment "The Intellectual Production of Engineers: A Full Hierarchical Table of Contents" share insights on how to manage tasks. The Notebook emphasizes the importance of organizing a network of tasks and determining what really needs to be done. Fragments, on the other hand, provides insights into how to manage and prioritize tasks and offers specific techniques for improving productivity.

deep thinking

Task management by AI requires not only efficient processing of tasks, but also the ability to organize a network of tasks and determine what really needs to be done. This suggests that AI will not merely perform human tasks on behalf of humans, but will also serve as a higher-level decision support entity.

AI task management: not just for efficiency, but for decision support as well."

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generated: 2023-09-15 07:11

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Discusses task management for long-term parallel projects using AI. He pointed out that a multi-header root system is not necessarily suitable for task management. He also discussed the pros and cons of handling tasks efficiently, emphasizing the importance of organizing the network and determining what really needs to be done. He stated that project objectives and task management are different, and explained the characteristics of each.

The fragments "multitasking confusion," "AI could manage tasks," and "task repartitioning" are relevant to the note. The note discusses task management difficulties and the potential of AI, and these fragments complement them in terms of task management problems, AI-based solutions, and task repartitioning, respectively.

deep thinking

Through notes and fragments, we will consider in depth the difficulties of task management and its solutions. Particular attention will be paid to the possibility of AI-based task management and the possibility of efficiency improvement through task re-fragmentation. However, we must not forget the realistic viewpoint that those methods do not necessarily solve all problems.

Possibilities and Limitations of Task Management with AI and Task Repartitioning is discussed. The title of the paper is "Possibilities and Limitations of Task Management with AI and Task Redivision.

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generated: 2023-09-16 07:13

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Discusses task management for long-term parallel projects using AI. He pointed out that a multi-head root system is not necessarily suitable for task management. Efficient handling of tasks is not necessarily good, and it is important to determine what really needs to be done. He also stated that project objectives and task management are different, likening objectives to a distant goal and tasks to the road in front of you.

The fragment "Letting AI Neutralize Unclear and Long-Term Tasks" (Diary 2023-09-12) is related to the content of the note. The note points out the problems of task management for long-term parallel projects using AI, and the fragment proposes letting AI twist obscure, long-term tasks as a solution.

deep thinking

AI-based task management has the potential to be a tool not only for simple efficiency, but also for identifying what really needs to be done. However, this requires AI's ability to understand task complexity and project objectives and make appropriate decisions.

Title: "Possibilities and Challenges of Task Management with AI"

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generated: 2023-09-18 07:09

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Discusses task management for long-term parallel projects using AI. He pointed out that a multi-head root system is not necessarily suitable for task management. He expressed his view that efficient processing of tasks does not necessarily lead to good results, and emphasized the importance of understanding the intrinsic value of tasks. Stated that the NeriNeri system is effective for project objectives, noting that project objectives and task management are different.

Fragment "pProject" points out problems in task management, which is related to the task management issues described in the note. In addition, the fragment "Future Past" explains the importance of recording and looking back on tasks, which is related to understanding the intrinsic value of the tasks described in the note.

Deep thoughts and questions

AI-based task management has the potential to provide a new perspective on understanding the intrinsic value of tasks and processing them efficiently. However, it is not yet clear how AI will understand the intrinsic value of tasks and how to leverage it. Further research is also needed on how AI manages tasks and how it can help humans find the details and context of tasks.

AI and Task Management: New Perspectives and Challenges."

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generated: 2023-09-19 07:09

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Discusses task management for long-term parallel projects using AI. He pointed out that a multi-head rooted system is not necessarily suitable for task management. It is important to act on a complex network of connected tasks by separating them into executable units. However, the multi-root system tends to connect tasks together. It is not always good to handle tasks efficiently, and it is necessary to determine what really needs to be done. The object of Neri-Neri is the purpose of the project, which is different from task management.

The fragments "Circulating Task Lists," "Task Shoot Time Techniques," "Forcing Task Organization," "Multitasking Experiments 2015," and "Scheduler" are relevant to the content of the note. They contain discussions of task management and efficiency, and are related to the problems and improvements in AI-based task management described in the Note.

deep thinking

The combination of notes and fragments provides a new perspective on the efficiency and effectiveness of AI-based task management. In particular, considerations regarding task clarification, prioritization, and task switching are important elements for improving AI's task management capabilities.

Clarification of tasks, prioritization, and task switching are important elements for task management using AI. Appropriate implementation of these factors will improve AI's task management capabilities.

Title: "Elements for Efficient Task Management with AI."

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generated: 2023-09-20 07:10

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Discusses task management for long-term parallel projects using AI. He pointed out that a multi-head rooter system is not necessarily suitable for task management. He expressed the view that efficient handling of tasks does not necessarily lead to good results, and stressed the importance of determining what really needs to be done. He stated that the object of NeriNeri is the goal of the project, which is different from task management.

Fragment "nishio/🔁Let AI manage tasks for long-term parallel projects" is directly related to the note and discusses the same topic. The fragment "nishio/🔁Let AI manage unclear and long-term tasks" also discusses task management using AI and is related to the note.

deep thinking

The discussion of AI-based task management reveals a gap between AI's capabilities and the way humans manage tasks; the perspective that AI's efficient handling of tasks does not necessarily lead to better results deepens our understanding of AI's scope and limitations.

Efficient task management by AI does not always produce good results. The key is to determine what really needs to be done.

Title: "Limitations and Importance of AI Task Management."

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code:fragments

I want 🔁AI to manage tasks for long-term parallel projects.

I want AI to manage tasks for long-term parallel projects.

I mean, maybe it's not for me. It's getting more and more messy.

Tasks are a complex network of interconnected units that must be divided into actionable units in order to complete a task.

The object of Neri Neri is more of a project objective

This is different from project task management.

The goal of the project is a distant goal

Now feasible tasks of the project are one meter way in front of you

What tasks are not feasible now?

Is it just a note that maybe there will be a road in that area and we will have to go that way?

Letting AI twist and turn unclear, long-term tasks

Letting AI twist and turn unclear, long-term tasks

Let AI 🔁twist unclear, long-term tasks

First, "what needs to be done" must be verbalized.

Maybe the current algorithm doesn't have enough next-action decision support, but I'll try anyway.

I tried.

Link later

relevance

Microformatting of objectives is useful for humans and AI to share objectives; Nishio's fragments "AI should manage tasks" and "Collaboration with AI" suggest that humans need to find the details and context of tasks and put them into words. In addition, "Collaboration with AI" indicates that AI can provide a broader perspective and that it is important for humans and AI to "collaborate" to share experiences.

Considerations can be seen from "write-in" and "non-write-in" methods of communicating information. In order to make the system easily usable for information, implementation of a writing API and automatic generation and deletion of information should be considered.

In "Constraints with N around 10~20," the variation of computational complexity with the value of N is shown. This is helpful when considering the processing load due to the amount and complexity of tasks.

The "Technology and Problem Solving Diagram" shows the relationship between technology and problem solving. This influences technology selection and problem-solving approaches.

The "The Engineer's Art of Intellectual Production: A Full Hierarchical Table of Contents" provides insight into how to manage and prioritize tasks. It provides specific techniques for improving productivity.

Since we usually manage computers that do not have feelings, we tend to fall into the wrong way of thinking about people who do have feelings, such as "Let's make them do tasks in parallel because the waiting time is inefficient.

It's hard to know how much time to spend on each corrective task without first understanding the big picture.

Even if you're working on a job that isn't tight on deadlines, running with no end in sight can undermine your motivation.

The default is to "look through the whole thing first and list all the areas that need to be corrected"

You want to fix it right away because you're not keeping track.

What is the granularity of the record?

As I will find out tomorrow.

Sense of adequate detail is acquired gradually through training.

If you don't do it, you won't learn it.

If you have a record that shows who you are tomorrow, you can do "the rest tomorrow" at any point in time.

https://gyazo.com/fc6a8b16c96626f7f3024b3d38e25966

Human multitasking stuation

Concurrency control story

When a long task collides with a short task, the longer task loses probabilistically, so

Only short tasks are done and long tasks are not executed for a long time.

The stuation that "I'm not going to be able to do it," happens,

That is to say,

In human task management, when I had small tasks and large tasks, I did only small tasks.

I thought it looked a lot like the problem of large tasks being left untouched.

The latter is not bumped and reverted.

The distortion of task selection timing to avoid large tasks rather than uniform randomness is the cause of the distortion.

So, I thought that if I could reverse the bias, I could solve the stavation problem.

The wording is ambiguous and contains multiple issues that need to be separated out.

I'm not going to talk about frequent interruptions (CS terminology) that require real-time reactions in this case.

When there is a mix of large long-term tasks and small tasks, the problem is that the small tasks take up so much time that the large tasks do not get done.

The theory that there is a problem with the mechanism for determining which tasks to perform.

How to multitask

Me: "I think the size of the implicitly assumed single task may be different."

Wife: "In the end, humans can only do one thing at a time, so let go of the illusion of multitasking."

I said, "What do you do when you have multiple projects that can only be done one at a time and will take several months to complete?"

Wife: "There are countless smaller tasks in a long term project. One task that can be done."

I said, "For example, about this 'writing a paper' project."

Wife: "First of all, it's not good that it's not clearly stated what the paper is going to be about, and it's like, 'I'm going to be big! Like that."

You're not seeing the whole picture.

How about writing it out first?

I'm not sure I have an estimate of how long it would take to do any of these things.

I don't like to do this, but I think that by drawing a Gantt chart, I can notice if it's too dense or not.

You may not be able to subdivide your tasks.

Time should be malloc for task segmentation.

Apart from that, what is the reason for the tasks that are not progressing at all?

This is also self-expression. They are thwarted when they realize that the prototype they have built will not work as well as originally planned.

Then, they repeatedly start up other projects that seem to work, resulting in more work-in-progress tasks that are not progressing, eating up the brain's working space and causing thrashing.

I admit that I do not have enough memory to run those projects in parallel, I have to write them to external memory and stop some of the processes.

So which process do you stop? If you're only doing short-term tasks, you're not going to make any progress on long-term tasks, bound again.

You have to admit that you are incompetent to proceed with tasks based on a long-term perspective. Because you don't admit that, you fall into the bind of trying to do both.

We need to be stupid, work on short-term tasks, get them done, and reduce the number of them.

generated: 2023-09-22 07:10

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Digest 1

A discussion of task management for long-term parallel projects using AI. Multi-head rooted systems may not be suitable for task management. Tasks exist as complex networks, and it is important to divide them into executable units. However, efficient task processing does not always yield good results. The NeriNeri system is effective with respect to the project objective, which is a distant goal. Currently executable tasks are the road in front of us, while non-executable tasks exist as future possibilities.

Consider the relevance of the fragment "🔁I want AI to manage tasks for long-term parallel projects": task management by AI requires the ability to understand complex networks of tasks and divide them into executable units. However, the "🌀pOmni" fragment suggests that AI needs to verbalize "what needs to be done," and that current algorithms may lack next-action decision support. The "human task scheduler load test" fragment highlights problems in human task management, and AI may be able to solve these problems.

THOUGHTS

Task management by AI requires the ability to understand complex networks of tasks and divide them into executable units. However, efficient task processing does not necessarily yield good results; AI needs to verbalize "what needs to be done," and current algorithms may lack next-action decision support. In addition, problems in human task management are highlighted, and AI may be able to solve these problems.

"Task Management by AI: Understanding Complex Networks and Breaking Them Down into Workable Units."

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generated: 2023-10-25 07:11

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