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KV Cache Transform Coding for Compact Storage in LLM Inference

https://arxiv.org/abs/2511.01815
1•walterbell•4m ago•0 comments

A quantitative, multimodal wearable bioelectronic device for stress assessment

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Wellness Hotels Discovery Application

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2•paulpauper•33m ago•0 comments

Ask HN: Are we at the point where software can improve itself?

1•ManuelKiessling•33m ago•2 comments

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1•marius-ciclistu•36m ago•0 comments
Open in hackernews

Ask HN: Anyone interested in improving scheduling?

4•mradek•7mo ago
I'm working on improving scheduling.

Specifically, any scenario where you have complex rules governing limited resources. Think large-scale, multi-year waterfall projects with $XX million budgets and hundreds to thousands of resources (people, machines, etc.).

Here are couple examples:

- Construction and engineering projects with thousands of interdependent tasks, crews and equipment

- Job-shop and flow-shop manufacturing where parts must move through machines under sequence and capacity constraints

If any of this sounds familiar, interesting, or you have direct experience dealing with these problems (as a PM, etc.), let's connect.

Shoot me an email at *** hello at mradek dot com *** or reply in this thread!

Comments

nickpsecurity•7mo ago
That's a very, well-explored domain. It's usually called planning. Some parts are called constraint, satisfaction problems. You should look at top, commercial products and survey papers in each to assess the stage of the art.

Also, before improving it, you might want to lay out what's wrong with it. What specific problems in the real world did you try to solve, what solutions did you try, and with what results?

If you're not doing the work, you probably won't have the experience to meaningfully improve it. It's better to work on solutions to problems in industries you're familiar with.

If you did the work and hit limitations, your interim goal should be to improve planning for those problems. Such narrower, specific goals might help you both succeed and get talented help. That should be in your problem statement or on your landing page.

That's all the help I can give since I have no time for developing stuff these days.

mradek•7mo ago
I should have been clearer about the specific problems I'm tackling. I’ll try addressing your points.

> On domain expertise

I've been in the trenches for over a decade since falling in love with Gantt charts, getting my CAPM certificate, and graduating college. First as a project manager on multi-year, $XX–XXX M projects, then as a self-taught SWE building PM software (we IPO'd a few years back). My domain knowledge is in oil & gas, construction, supply chain optimization, and manufacturing to a lesser degree. The scheduling tools I know best are MSP and Primavera P6.

> On the existing landscape

I agree that this is a well-established field of study. I'm using Google or-tools and evaluated a few other constraint solvers. However, I believe the focus has been more theoretical because actual software and tooling that people use day-to-day lacks any collaborative execution and management automation. In my opinion, this is where and why projects always break down.

* This leads me to the specific problem which I should have shared earlier! *

Every non-software rollout I was part of ran late and over budget. There's a stat that 90%+ of projects miss their targets. By contrast, agile software teams shipping sprint-sized features almost never slipped. The difference? Real-time collaboration and adaptability. (And yes, I'm aware the scopes are radically different!)

The moment we move from "just" the world of bits to the world of steel, gas pipelines, trains, and dealing with hundreds or thousands of people, equipment, 3rd parties... even the best plans crumble.

> Real world experience

I could go into minute detail on each one, but I'll spare you the reading and myself the PTSD by condensing a few pain points:

- No shared, real-time view. Data lived “somewhere,” but never with field teams or execs.

- Black-box auto-levelers (like Primavera P6) only delay tasks they don’t split or reallocate crews without the PM doing a ton of work. Small hiccups can easily compound into slips that last days or even months. Licenses are expensive and access is gated so only “the scheduling team” sees the live plan. I’d argue it’s not a solved problem otherwise we would not have needed to also bring on dedicated scheduling consultants.

- Process workshops and Excel jockeying can’t keep pace with real-world churn. Any good plan evaporates once work actually starts. We did these things on every project but I don’t think it really made a difference because while people are a variable, bad tooling is exponential.

> My approach

Rather than building another optimization engine, I’m creating a collaborative platform where scheduling is a core feature. Most tools focus on the initial optimization but ignore the continuous re-planning that real projects require. Not everyone _needs_ the schedule obviously, but the schedule _definitely_ drives the project. I want to enable realtime ADAPTATION as conditions/constraints change in the field.

I’m particularly interested in connecting with others who’ve hit similar walls, or who have insights on bringing real-time collaboration to complex, distributed projects so I really appreciate your response.

stncls•7mo ago
A good chunk of the day-to-day work of "operations research" consulting shops is scheduling.

There is also dedicated software like Timefold, formerly RedHat OptaPlanner [0].

[0] https://timefold.ai/blog/optaplanner-fork

ge0ffrey•7mo ago
For Job Shop Scheduling like this, Timefold has two implementations:

- Basic: an open source Food Packaging quickstart on solver.timefold.ai

- Advanced: a Job Scheduling REST API on app.timefold.ai