mkaic

> People who enjoy a van Gogh - or any other work - primarily do so because it has particular qualities they appreciate (no, being human-made isn't an intrinsically appreciable quality; secondarily because many humans instinctively like to possess unique - or "shiny" - things)

Speak for yourself. You could show me the exact same artistic image, same exact pixels, but if I know it was made by a human, it will instantly be worth more to me and capture more of my interest. Conversely, having the knowledge that the pixels were created by a machine would make me instantly lose interest in the image.

I think "being human-made" very much is an intrinsically appreciable quality, but you have to include the production of the art as part of the art itself for that to be the case. And I and many other people explicitly do include the production of the art as part of the art itself. Not everyone shares this perspective, but many do.

I chose to use the first line of the video description as the submission rather than the actual YouTube video title, as I found the video title vague and uninformative.

I'm excited to see a new thing in the Zero-Order Optimization (ZOO) world. I see most ZOO methods not as a "replacement for backprop" the way they are often marketed, but as a technique that can potentially work well in regimes where backprop is fundamentally weak. One of my favorite papers [0] in recent memory, for instance, is about using central-difference random gradient estimation (CD-RGE) to train large RNNs without using backprop-through-time. They also show it works decently for hard-to-optimize differentiable-neural-computers. Since reading that paper, I've had a lot of fun trying to apply this technique to settings I would describe as "a traditional differentiable neural network being applied in a non-traditional environment where you can't just call loss.backward and hope for the best". I am excited to try Dust out on my personal project now :)

I got a popup in my Codex just now saying "Try out 6.1 Sol!" and so I clicked the button to try it, and intriguingly, it set my model selector to "GPT-6 Astra Light" which makes me think 6.1 Sol may be in some way just a lighter/distilled version of Astra? defo interesting, not sure if I should read too much into it though. I see no option for directly selecting 6.1 Sol in my Codex Desktop UI.

I investigated a gradient-descent-based concept adjacent to this back in like 2023 [0] inspired by the original 3DGS paper, I was pretty happy with the results I got with back-to-front alpha-blending and polar-coordinate gaussians for variable-curvature brush strokes. One of these days I should add another example gif to the repo besides just the Mona Lisa one that's currently there, but that's the only one I've got at the moment unfortunately.

[0] https://github.com/mkaic/painterbot

Just cancelled mine after reading this comment, I only really cared about the bigger file uploads and the HD screen-sharing anyways and I can live without those.

Now that I think of it, I bet I could host a decent instance of some open-source alternative in a public cloud for around the same cost as what I paid for Nitro ($100 a year)...

I suppose both of us watched the same Youtube video by Metta Beshay (i think that is his name?)

perhaps I shouldn't share my workaround, but I've found that Mullvad's Norway nodes consistently get past Reddit's IP-blocking :)

Heavy and chronic usage of cannabis is associated with some of these things. I think "plenty of evidence that marijuana can cause {effects}" is somewhat overstating the consensus on the topic.

Like many things in life, cannabis can be enjoyed responsibly or irresponsibly. Irresponsible use is inadvisable and can absolutely ruin your life and the lives of others around you. I see no issue with responsible use, though. All things in moderation. Alcohol, social media, and caffeine all come to mind as examples of other drugs that can be largely safe and enjoyable if used responsibly, but which become dangerous/harmful when moderation is abandoned.

Signed,

a responsible/occasional cannabis user :)

"It's... a regional dialect."

"What region?"

"Er, upstate New York."

"Really. Well, I'm from Utica and I've never heard anyone use the phrase '100M' to mean '100 thousand'"

"Oh, no, not in Utica. It's an Albany expression."

I think some of the coolest changes in this release are on the nodes side of things — they added Closures (kinda like lambdas!), Bundles (tuples/structs, I guess?), and Repeat (loops!) (already was in Geo Nodes, now it's in Shader Nodes too).

Blender nodes have come a long way over the past decade and it's incredibly satisfying to see the care with which they have been developed. Blender's node editor is my personal favorite node editor I've ever used in any software, and I often find myself wishing other software adopted some of their UI and UX conventions.

Been a happy user since, oh, v2.75? And looking forward to being a user for many more releases to come.

Donate to Blender! [0]

[0] https://fund.blender.org

IIIII HHHAAAAAVE THE POWERRRRR

Location: Boulder, Colorado

Remote: Open to Remote, Hybrid, or In-Person

Willing to relocate: Only for an exceptional offer.

Technologies: AI / Machine Learning, Docker, Python, PyTorch, Numpy, Pandas, Linux, TrueNAS, Pandas, SQL, Blender, Git / Github

Résumé/CV: https://docs.google.com/document/d/1io7PASX56d7eJTCXQnPxjqy3...

Email: matthew.kai.christensen (at) gmail.com

Hello, my name is Kai and I'm a machine learning researcher with an interest in computer vision and novel neural network architecture design. I have 4 years of experience working on computer vision models for medical imagery, including publishing an echocardiography-focused finetune of CLIP in Nature Medicine last year. I'm self taught and enjoy work where I can be creative and learn new skills. I would love to be a part of the team that invents the Transformer-killer. I'm also open to more data-sciencey jobs if the work is interesting.

I also have 3D modeling, filmmaking/editing, and music-making skills and experience if they're relevant. I've been making movies and doing VFX ever since I was little.

My favorite Spherical Minecraft-like gamedev project is PlanetSmith [0], which uses hexagonal voxels (and a few pentagonal voxels). The devlogs are very well produced and I highly recommend checking them out.

[0] https://youtube.com/@incandescentgames

My favorite way to generate random points on a n-dimensional sphere is to just sample n times from a Gaussian distribution to get a n-dimensional vector, and then normalizing that vector to the radius of the desired sphere.

Have you kept up with recent ML papers like MindEye, which have managed to reconstruct seen images using image generator models conditioned on fMRI signals?

Ever since that paper came out, I (someone who works in ML but have no neuroimaging expertise) have been really excited for the future of noninvasive BCU.

Would also be curious to know if you have any thoughts on the several start-ups working in parallel on optimally pumped magnetometers for portable MEG helmets.

I second this recommendation, I've been listening to the Wanderstop OST on shuffle for over a month now and find it delightful. The sister album "Wanderstop FM", which contains tracks that play diagetically on the in-game radio, is also excellent.

I feel a bit shaken after reading this comment, to be honest. I don't think I've ever heard someone so perfectly describe such a major component of my life experience. It's like you read my mind.

I was a "gifted kid", now I'm a lonely adult living by herself constantly cycling between complacency, failure, panic, and productivity. Diagnosed ADHD, choose to stay unmedicated, sometimes the best employee in my office, usually one of the laziest and most disappointing employees in my office. Constantly daydreaming about how better circumstances would change things for the better even while knowing deep down I'd cause the exact same set of problems for myself all over again even if I got my Dream Job.

Spent my whole life being told I was exceptional, and, to be fair, I lived up to it as a kid. These days I'm so terrified of regressing to being "normal" that I sabotage myself at every turn.

Thank you for leaving this comment. I may bring up the concept with my therapist and see what she thinks of it.

I think in casual speech at this point (at least in my experience) the two are used interchangeably. In professional or legal settings I'm sure the distinction matters more, but I feel like OP's usage here felt pretty natural to me even though it's not technically correct.

If they can manage to make good on their plans to open-source it, I'll breathe a tentative sigh of relief. I'm also rooting for them, but until they're open-source, I'm not willing to invest my own time into their ecosystem.

Here's an unpaywalled PDF I found of the same: https://labs.la.utexas.edu/gilden/files/2016/04/theketchupco...

I love the look and feel of Nim, but found it to be stuck in a weird chicken-and-egg situation where it didn't have enough of a following to have a Convenient Package For Everything, ultimately turning me off it. Of course I recognize that the only way a language gets a Convenient Package For Everything is if it gets popular, but still...

Damn, this is a strikingly simple modification. Basically, modern deep learning optimizers typically calculate the update to the weights each step using some kind of momentum and/or LR scaling based on the running variance of the gradients. This means that, in theory, the actual "instantaneous" gradients from a particular backward pass might point in a different direction than the actual update the optimizer applies. The change the authors propose is to simply ignore any parameter updates proposed by the optimizer that have the opposite sign of the current gradient from the most recent backwards pass. They're essentially saying "only apply the long-term stabilized update where it agrees with the current 'instantaneous' gradient." They show that this simple change significantly speeds up model training.

I'm pretty intrigued by this, but will, as usual, wait for independent replications to come out before I fully believe it. That said, because of how simple this is, I'd expect such replications to happen within 24 hours. Exciting work!

In a hilarious act of accidental satire, it seems that the AI-generated audio version of the post has a weird glitch/mispronunciation within the first three words — it struggles to say "GPT-4.5".

I don't think there is such a legal obligation, because videos like this one exist where devs do share the exact financials of their Steam releases: https://www.youtube.com/watch?v=mPMfcaUulYU

Not with that attitude it's not :P