Whenever I am in a new city I always feel astonished that more places haven’t adopted contactless payments for transit like TfL rather than prepaid cards. It’s so much more seamless and meaningfully reduces the barrier for tourists or those who don’t typically use transit.

still thinking about the skyline of San Jose, the tech capital of the world I was expecting futuristic utopia vibes and instead got, like, Plano Texas vibes

Using the recently added MACE multi-GPU support, Philipp Benner burned 1440 A100 hours to train a 16M param universal MACE on MPtrj that achieves a new SOTA on Matbench Discovery, reaching F1 score of 0.64 in crystal stability prediction! 🧵

The philosophy of Matbench Discovery was to try produce a discriminative benchmark that mirrors a real workflow in High-Throughput inorganic crystal discovery. We’re hoping to commodify the thermodynamic screening steps such that researchers can focus on properties and synthesis

If it seems like I’ve been talking about data centers a lot, here’s a good example why. Major climate goals are at risk. “Microsoft’s predicament is one of the first concrete examples of how the pursuit of AI is colliding with efforts to cut emissions.” bloomberg.com/news/articles/…

the bay area is one of the greatest failures of urban planning in human history - best weather on earth - waterfront property, islands, and hills for views - massive natural bay what we got: - mindless suburban sprawl - a “subway” used by <1% of the population

Orders of magnitude: coal vs. lithium.

In relation to the noble prize in physics I've seen several articles saying that Geoffrey Hinton worked on applying ML to improve solar cells, if anyone has the source material or references I would love to read them but haven't found them through search.

Is there any good literature on the use of deep set models as part of deep kernel learning GPs for bayesopt? Ryan-Rhys Griffiths Andrew Gordon Wilson

Today we release TorchSim, a next-generation PyTorch-native atomistic simulation engine for the MLIP era. Our hope is that this open-source package ignites a materials simulation revolution.

Try it for yourself here: github.com/Radical-AI/tor…

TorchSim v0.2 is out! github.com/Radical-AI/tor… I am especially happy to have 5 new contributors and 3 new model interfaces. Below, a sneak peek of a WIP figure describing TorchSim's approach to memory estimation.

Another step forward in ML-first materials. We’ve seen machine learning revolutionize industry after industry, and today, we release EGIP, showing our ML-first approach that out-performs traditional physics-based methodologies: radical-ai.com/news/EGIP

This chart is internet-famous since Steve Jobs allegedly looooooved it. It shows how much energy (measured in calories) is needed to move objects by weight. A human on a bicycle is outrageously energy efficient. Cycling is the king of transportation!

We are excited to announce a $55M Series Seed+ led by RTX Ventures, joined by NVentures (NVIDIA's VC arm), noa, Infinite Capital, eni, AlleyCorp and many others.

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