Verified65% confidenceFactExact time
DeepMind's GNoME project predicted approximately 2.2 million potentially stable crystal structures, about an order of magnitude more than the stable materials previously known to humans.
3
Sources
65%
Confidence
Long-term
Relevance
7/11/2026
First Seen
Sources
The Real Bottleneck in Materials Innovation: Why Scaling Up Is Harder Than Discovery
hackernewshackernews7/10/2026
Related Claims
UnverifiedThe GNoME project discovered 2.2 million new stable crystal structures in the field of materials science.77% similarUnverifiedGNoME基于图神经网络架构，将晶体结构表示为原子节点和化学键边的图，在Materials Project等数据库中约4.8万种已知稳定材料上训练65% similarUnverifiedGraph neural networks (GNN) treat crystal structures as graphs and aggregate neighbor information through message passing to predict properties such as formation energy, band gap and elastic modulus, with typical models including CGCNN, SchNet, MEGNet and ALIGNN.57% similarUnverified无进位乘法获得硬件支持后，批量数据加密、大规模GCM认证、区块链哈希运算等场景可借助GPU数千核心并发处理实现远超CPU的吞吐量56% similarUnverifiedNvidia's official data claims that Nemotron 3.5 Super VL can achieve up to 5 times higher agent throughput on a single GPU than open-source models of the same scale.55% similar
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