Rhys Goodall

stuff @RadicalAI Born 362 ppm.

[Rhys Goodall @RhysGoodall]

https://t.co/7JBqVkfMpS

[Rhys Goodall @RhysGoodall]

The future is electric

[Rhys Goodall @RhysGoodall]

@farazamiruddin How in the San Jose is putting all the commercial areas in one block on the edge going to create anything other than a city where everyone needs a car 5 days a week?

[Rhys Goodall @RhysGoodall]

@mmoderwell I am not hugely a fan of generative models but i think something like https://t.co/GmuqdxwNtK could be good in this sort of funnel. Multi-step relaxation is good. Maybe just relaxing the unit cell parameters first could have prevented what I saw. Fixsym I don’t think would help.

[Rhys Goodall @RhysGoodall]

@mmoderwell I tried an enumerated campaign with SMACT -> anom prototype outer product -> Wren -> MLIP (sevennet-0) a few years back but saw lots of explosions from the MLIP. Wren cut ~10^9 to 25 * 10^6. The random symmetrical structures from pyxtal were often ill-conditioned to relax nicely

[Rhys Goodall @RhysGoodall]

@notimenoway @ajassy If power shuts off the chips will stop producing heat and they’ll just cool slowly from the maximum safe temperature they were at under steady load with the cooling system?

There’s not a meltdown risk, these are gpus

[Rhys Goodall @RhysGoodall]

@JacobAShell A biking trip would certainly have been a better plan. Local bus routes were not just bad but entirely absent. Maybe in a fairly near term future self driving taxis could have been the solution to my trailhead woes.

[Rhys Goodall @RhysGoodall]

- R2SCAN datasets for training foundation models like MatPES/MP-ALOE as MLIPs get more leverage approximating higher fidelity simulations at fixed inference cost. This also helps with unifying molecules and materials as R2SCAN + dispersion good for mols/mofs/mats

[Rhys Goodall @RhysGoodall]

I have prematurely said that MBD was saturated more times than I should admit. Perhaps there is still more juice to squeeze but if I was still doing day to day research in this space I think there's more ripe fruit to pick elsewhere. I would like to see the following:

[Simon Batzner @simonbatzner]

Yet another NequIP in the top 10 with EquFlash, this time with some very clever accelerations! Bringing the total to ….? I’ll leave it to you how to count :)

One question this raises is what a lot of folks have told me recently both on here and in private: they find it “disheartening” (to quote @SamMBlau) that we’ve had the same sota architecture since January 2021 now.

My answer is always the same: we’re not building these models for the sake of building models. We’re building them because there are fundamental challenges that require the discovery of novel materials. These algorithms accelerate that. If the FF architecture isn’t the bottleneck, you should stop optimizing it and focus on more interesting problems (data, data, data, evals, scalability, and above all, actually finding and making materials).

I can think of at least one other field that flourished when they stopped playing the architecture game.

Take my words with a grain of salt though. I was told at APS 2019 by a very “senior” person in the field that the fitting problem of MLIPs was “solved”. That turned out it be horribly wrong. I’m rooting for every grad student to make a meaningful dent in this problem. And who knows, maybe there is more juice to be squeezed beyond a 1mev/atom MAE difference.

(also if you’re building molecular FFs, different story, this is a materials benchmark)

[Rhys Goodall @RhysGoodall]

@natolambert @tdietterich In the way Chemrxiv and Biorxiv exist, Airxiv would be welcome contribution to the landscape

[Rhys Goodall @RhysGoodall]

@natolambert @tdietterich I have high trust in most physics and materials science papers in my domain on arxiv. The platform was adopted and dominated by the CS field but it remains important to other communities .

[Rhys Goodall @RhysGoodall]

@rmcentush Wind is rotating power so it’s AC? The biggest mistake the US made on its grid was being early and going too low on the voltage.

[Rhys Goodall @RhysGoodall]

@marvinvonhagen @letsbuildmore @TimSweeneyEpic @dhh Bad example google pays a huge amount to apple to access their distribution.

[Rhys Goodall @RhysGoodall]

@ruben_laplaza @curtischong5 Glad you're finding it helpful. Could you make an issue documenting what the issues are? I would guess loading from a ASE DB returns a list of Atoms and then we have IO functions to join those into a batched SimState. We want to remain decoupled from ASE but also be interoperable

[Grant♟️ @granawkins]

> be me
> exponential curve supervisor
> get to work
> check-in on the curve
> it’s sigmoid

[Radical AI @RadicalAI]

We are excited to announce a $55M Series Seed+ led by RTX Ventures, joined by NVentures (@nvidia's VC arm), @noavctech, @infinitexyz, @eni, @alley_corp and many others.

[Rhys Goodall @RhysGoodall]

@marwinsegler @andrewwhite01 It does think that a lot of chemicals used in battery electrolytes are Chemical Weapons. LiPF6 and LiTFSI both led to refusals.