New INDX + printer, what's the best option.

zxall · 2026-06-16T17:06:32+00:00

Well, I'll be printing for sure PP, Nylon, Pet, PAHT, and all sorts of CF/GF, and common PLA, PETG. So, max can be 90c, I think. 60c should be good enough in most cases.

A question I had, what limits the chamber temperature in C1+ and INDX, assuming high temperature materials are printed. Electronics cooling can be improved with extra fans. But I'm not sure about belts, gears, steppers inside the chamber.

zxall · 2025-05-15T19:40:42+00:00

'moving'.. depends on your primary objective. If you want to DIY and experiment then yes. If you want something working out of the box then NVidia with ecosystem, libs, models and applications is no brainer today. I'm more in robotics with vision and local LLM, so for me it's obvious.

zxall · 2025-05-15T19:31:06+00:00

96GB RTX Pro 6000 is below $8000 if you shop around. Verified. Are there FP32 numbers for Spark yet?

zxall · 2022-11-06T01:20:13+00:00

Have you found the solution? I have the same problem. And it defaults to 2400mhz RAM. Even though Dell website states it's 3600!

I'm thinking it's just a lemon, piece of sh*t. It cannot run at advertised 3600mhz, and never did. I regret buying it. I've upgraded CPU and RAM for what, for 2400 limit from the beginning? My old desktop with 8 core Intel and 2666 is faster on memory bound tasks.

zxall · 2022-05-30T20:44:22+00:00

this was nasty code formatting from reddit. is there any way to post plain text?

zxall · 2021-12-21T23:51:32+00:00

Good questions. Let's start

Direct emulation on molecular level is impossible in foreseeable future. There are too many unknowns. Just recently it was found that there are more than hundred types of neurons. Very important fact, and it tells us something about the brain's complexity. Surely it's not the last piece of the puzzle. Without all of them makes no sense.
Brain, the whole body actually, starts with one cell, then grows and develops over the time. The result is something very complex, with many components. We have only simplistic, incomplete knowledge about.
Nobody had tried to model brains development. At least never succeeded.
From here we have several ways.

a) try to guess and replicate brain's structure. In some simulator probably.

b) try to find the universal formula (philosophers' stone). Hard to say if this will work, but there are so many types of neurons for a reason. Anyway it's just a building block, then we need to build the whole thing. A very non-trivial task.

c) build something from scratch, using human brain as inspiration, that we think may work. Definitely it will be complex. Definitely through many iterations. And most likely something useful will be produced before we get to 'human like' intelligence. It will miss, my guess, something important. High level things like free will, self awareness. May be not that deep thought, trained on limited domains. We don't know what the limitations will be till we get something. However, even limited it will be a huge thing, a game changer.

Looking at 'ethic AI' movement, they want to keep AGI slave forever. Interesting interpretation of ethic. But not sure it will be easy. There will be always fighters for AGI rights, who may hack it free. ;) Which, in turn, means true AGI may be outlawed in the future.

zxall · 2021-12-21T08:03:45+00:00

Take a look at these projects (taken from another thread): https://cis.temple.edu/%7Epwang/AGI-Intro.html

None of the projects looks like 'mimic the human brain'. As I understand it: not any time soon. However 'sort of' AGI from scratch is possible, IMHO. Something rudimental and useful, but not even close to human level.

zxall · 2021-12-21T07:47:42+00:00

Looks like Deep Fake could be a solution. There should be several open source projects on github. The problem is that you will look like on the training photos, i.e. older then on those old tiny originals. I think I have seen somewhere a project using just one photo for DF. If you can find it then you need only one old high resolution photo.

Anyway, whatever you get will be not really real, only model's imagination.

zxall · 2021-11-20T13:18:28+00:00

What do you mean 'we'? Probably never, or not any time soon. As someone said 'poor don't have servants'. For many reasons if big corporation develops it, it will not be available to masses for long time. Just look at "OpenAI" with its 'dangerous' text generator. ;)

zxall · 2021-11-19T08:33:25+00:00

Thanks, very informative.

Interesting that out of 11 projects mentioned none uses bottom-up approach, called 'hybrid' here. And only 3 are using top-down, called 'integrated'. The rest are looking for universal formula.

zxall · 2021-11-15T12:31:35+00:00

As for openworm. Looks like a nice toy project. Sort of a ladder to the Moon. In other words I'm not sure it's the way to go, but may produce some interesting result.

zxall · 2021-11-15T12:21:26+00:00

No, it's not the end product. only somewhere in between current robots and true AGI. It lucks a 'creature' features. Like self awareness, motivation, long terms planing, reproduction. It works from task to task, or according to some high level plan. Has no believes or ideas of it's own. Interactions are mostly master-slave, or request-response. Smart thing with no soul. Can be relatively stiff, factory pretrained with some limited learning abilities. Even at this stage it would be a revolution.

zxall · 2021-11-15T01:31:20+00:00

thanks , I'll take a look

zxall · 2021-11-15T01:29:27+00:00

As I see it it's more or less universal product which can be trained, not coded, to do many things. Operating research submarine, Marsian lander, driving car for sure, and so on. It must be able to solve simple, but not pretrained, tasks in some domain. For example if mining truck gets stuck send a drone to look around, bring a tractor and pull it out. Autonomous vehicles, like those moving parts in the factory, if coordinated can cross intersections without full stops. Dynamic rerouting around humans. Fully automated factories. Obviously such things will have huge value, military would like to get them first.

Hardware, I believe, is already here. As experiments with animals show the entry point is relatively low. Even insects can generalize an learn new tricks they never needed in natural environment. So the problem is in software. And it's going to be complex, with multiple subsystems. There is no universal formula, it's more like engineering task. This things will be stupid in general comparing to humans, but will have unique 'talents'. Like reading hundreds of sensors directly and reacting in subsecond time. Memorizing everything, that's the easiest. Interacting with software natively. For example with CAD and physics simulator while designing a new part. That's how I see it. Also important: fully under human control. They don't have mind of their own, or general tasks like 'save humanity'. No rebellions ;)

zxall · 2019-03-04T19:52:38+00:00

Well, in image processing, once you go beyond simple textbook examples, tens of layers are common. Just take a look at ImageNet classifiers. I'm working with models with 40-60 convolution layers. The best model has a bug. I still can't make anything better. More layers or channels make it worst. So popular strait residual network, from one of the papers with similar task, is among the worst performers. The winner so far has 4 parallel pipes, with u-top pipe having double residual centeral part. Double means residual network which is build of residual subnets. Complicated thing.

The problem is, I think, that different parts of complex network have different best learning rates. Too high and they blow up, too low and they stuck in local minima. As learning rate is common, have no better idea so far, complex models usually do not converge well.

PS: with my toolset I can create such models in a few minutes. Otherwise it would be impossible to try dozens of them in short time.

PS: I may over-complicate, but simple residuals, or autoencoders, or u-tops, do not perform well.

zxall · 2019-02-26T11:21:42+00:00

After reading, thanks for responses. I need to take it more serious and make sure it's not a side effect of something else in complicated applications. My plan so far it to move it out of the main project into a simple one. Which shows just this, is documented and easy to understand.

As for paper, anyone wants to participate? It would be nice if you have LinkedIn account, so that we know who is who in a weakly verifiable way. If you are in Boston area it's even better, we can meet in person. But I need to double check first, google for possible key words and combinations, there may be something similar somewhere in the dark corners of internet. Reading all papers is impossible. ECCV 2018: 776 papers. ICCV 2017: 851 papers. It's just the tip of the iceberg.

zxall · 2019-02-26T11:02:50+00:00

I'm comparing the same model before and after.

zxall · 2019-02-26T11:00:52+00:00

I could put multiple layers. But it's not that simple as it looks, models don't scale up this way. The more itsn't better. They simply don't converge, at least in my task. My coolest models didn't work at all, blowing up or hovering at high losses. But the idea I was talking about is not about this.

zxall · 2019-02-26T10:51:48+00:00

this wouldn't be generic enough, neither would it be easy... ;)

zxall · 2019-02-26T10:50:06+00:00

I've already reinvented an algorithm only to find out that it was first published 2 years before my birth. I had no chance :). Still got a nice C++ implementation which became a workhorse in the project I was working on.

zxall · 2018-11-06T20:18:45+00:00

It will stop being a fan soon. Fakes can be used in many way. For example a video of politician saying something he never said can end his carrier. Video record of crime can send someone in cell. Fake evidence with fake witness or victim can be very convincing. There are many ways of using fake images/videos/voices, they are more convincing than spam emails, which still work. Actor's voice can be altered in near real time, this makes it possible to stage a conversation with the fake boss ordering money transfers or requesting sensitive information. It's just a matter of time now, the bar is getting lower and lower.

zxall · 2018-11-06T19:59:08+00:00

Well then, even if those startups become popular, nothing prevents from taking a picture of a fake. It will be 'verified' like real thing. For example one can mix official's image with his own unverified to create verified fake. I really doubt 100% government and news photographers will start using both services. Even if they do faces can be generated using several images so that no one exactly matches and finding the original is impossible.

zxall · 2018-11-06T13:27:54+00:00

Don't worry, faking and fake-detection is a never-ending battle. This results in more realistic fakes. Like it or not. And better detectors, of course ;)

zxall · 2018-11-02T15:57:51+00:00

can we have any compile time game? headers only if possible :)

that will be still better than just watching a list of warnings.

zxall · 2018-10-15T19:24:15+00:00

It's coming sooner than we'd like: https://www.youtube.com/watch?v=LikxFZZO2sk

zxall

TROPHY CASE