I'm a visible minority who went from the GTA to Boston, everything is fine. People with this attitude are mostly fear mongering. No one I know has been harassed by ICE. Not saying they aren't doing terrible stuff, but the average tech worker is just fine in the US.

Would be similar to the typical simulations of humanoids. If you need to model the deformations of the human body, or get a proper model of tendons that make up humans, it'll be more difficult, but possible.

Proper simulators for those exist, you essentially need an engine with a compliant contact model. MuJoCo is the goto here, see:

https://mujoco.readthedocs.io/en/stable/modeling.html#muscle... https://mujoco.readthedocs.io/en/stable/computation/fluid.ht...

These explicitly model biological muscles. IIRC it was originally created to model human hands (I could be misremembering though).

Really depends on the fidelity you want.

Edit: I also work in rigid body simulation for robotics.

Indeed, it entirely depends on which axis you want to focus on. A loose trade-off chart would be speed, stability and accuracy. You can only have two of these in a simulator.

Robotics folks probably want speed and accuracy. I'm from the video game industry so I generally look for speed and stability.

Note: This is a loose analogy and recent techniques are already blurring the lines between these axis.

It's incredibly hard to do good, novel work in 2 years for engineering. You'll likely not learn much either.

No? This is only true if you assume that Newton’s only notable achievement was the creation of calculus. Newton did far more for physics and classical mechanics than Leibniz. Did Leibniz also discover the universal law of gravitation? Did he match Newton’s prism experiments in some way? In what sense can Newton be replaced by Leibniz?

I'm not in academia, so I might be fully ignorant about how things operate, but if professors don't reaed the actual paper, can do they know if it's BS or not?

Here's how it works in our group. The professor gives papers to the PhD students or PostDocs, who read the paper completely. I regularly 'sub-review', as it is called, meticulously looking for issues. I have heard that there are professors who review entire papers in 2-3 hours, since they have a lot (10+) of papers per conference to review without any compensation while they have their own research, teaching, and funding to juggle.

It's not a pretty system sometimes.

Edited to add: Conference's also require declaring that there was someone who sub-reviewed the paper. The professor / PI mentions the PhD student's name in the review form of the paper. Of course, the professor also double-checks all the sub-reviews

The sub-review process, when it works well, is arguably a reasonable one. To give the example of how this works from the perspective of the program committee of a conference I'm involved in:

The PC chairs assign papers to members of the PC. Those reviewers are ultimately responsible for the review quality and, a more frequent problem for the conference, ensuring the reviews are in on time. In principle, they can ask anyone to sub-review, but in practice, it usually goes to grad students, postdocs, or graduate alumni (and since we have a relatively light review load per member, we have many people who do all reviews themselves). The reviewers arguably know more about the expertise of their grad students and postdocs than the chairs doing the assignments do. Also unlike a journal, where editors might ask anyone with particular expertise, we both only assign reviews to PC members, and do assign them: PC members only get to state their preferences on what they would like to review. The sub-review process ideally lets reviewers ask people to do reviews who they know would be suited to a particular paper, but who might not be experienced enough to reasonably be on the PC itself with those responsibilities, and the chairs might not know much about. It then lets those reviewers look over the sub-reviewer's work directly, which might include mentoring them. While we do anonymous reviews, identities are visible to chairs, and one thing I've noticed when a chair, for example, is that grad student sub-reviewers often do excellent, thorough reviews, but also often lack the confidence to be sufficiently critical when writing about problems and weaknesses they identify, something that the reviewer can help with.

The review system (we use easychair) directly handles sub-reviewers, and our proceedings list all sub-reviewers (at least, those who actually submitted reviews). Good sub-reviewers can sometimes be reasonable candidates to ask to be on the PC the next year, and give a gentler, safer onramp: we're able to have a wider mix of junior and senior members when there are new postdocs (and I think in one case a grad student) who we already know do reliably good reviews and know our review process.

A few other commenters have talked about the paper review process.

I wasn't thinking of this at all. Important to understand: the peer review process takes up only a minor part of a professor's mindshare. It's considered a chore. Much more important is to read lots of new papers (including pre-prints) for continual education, to know what's going on in your field and adjacent fields.

They're getting better, and are starting to be used in robotics: https://scenesmith.github.io/

Curious, when you do this, do you understand the math/reasoning of the paper and just have claude as do the coding? Not saying that matters if you just care about the end result, but I'm curious how much using an agent affects your understanding of what the papers are proving.

I went in with limited understanding, gained some more as the agent worked through it. What can appear complex in the paper often turns out to be far more simple and elegant once you see the code written.

Never tried with that low of a timestep, wonder if that could start causing floating point issues which will lead to more instability.

Yeah I did have to refactor slightly to minimize precision related impacts.

Awesome work, what always prevents me from implementing more solvers is the amount of math required. While the implementation always seems simple, understanding the different optimization strategies for each solver gets confusing.

It's really impressive that the author was able to implement rendering papers and physics sim papers with such regularity. It really is a feat. Makes me curious to see what their background is.

Can you elaborate on what you mean? It could be a matter of perspective, For a stack of blocks, each 1 meters high, the stack can get quite high and your expectations on how it should look like IRL might not be correct, due to never experience a large tower of blocks being knocked over at that vantage point. Especially if the mass of the objects are strange (super light for their size or super heavy).

I know in older games, the recommendation was to keep gravity low (~6 m/s^2 iirc) to help with simulation stability and make things look better, that might contribute to your idea of things being floaty.

I don't find the examples in the git repo to be especially floaty, but I work with a lot of simulators so I might just be used to it.