Knowledge Graph
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Entities25 of 207,987
- large language modeltechnology1,043 mentions
- robotic manipulationmarket824 mentions
- artificial intelligencetechnology739 mentions
- reinforcement learningtechnology491 mentions
- density-functional theorytechnology386 mentions
- Transformertechnology371 mentions
- agentic AItechnology353 mentions
- vision-language-action modeltechnology350 mentions
- U.S. Food and Drug Administrationorganization320 mentions
- Vision-Language Modeltechnology318 mentions
- Microsoftorganization291 mentions
- Googleorganization276 mentions
- NVIDIAorganization264 mentions
- Model Context Protocoltechnology232 mentions
- machine learningtechnology204 mentions
- MarketsandMarketsorganization199 mentions
- Claudeproduct192 mentions
- AI agenttechnology188 mentions
- ChatGPTproduct178 mentions
- Anthropicorganization177 mentions
- integrated sensing and communicationtechnology175 mentions
- Amazon Web Services, Inc.organization174 mentions
- OpenAIorganization172 mentions
- diffusion modeltechnology169 mentions
- IBMorganization163 mentions
Entity
MACE
technology11 mentionslast seen Nov 11, 2026
A graph-neural-network machine-learning interatomic potential benchmarked for dynamical stability in inorganic semiconductor nanocrystals.
Relationships 17
- MolCryst-MLIPsdepends onMACE92% confidence1 source
- DFTB+MACEcomposed ofMACE90% confidence1 source
- MACEdepends ondensity-functional theory90% confidence1 source
- Orchestr.AIdepends onMACE90% confidence1 source
- MACEdepends onmachine learning interatomic potential90% confidence1 source
- MACEdepends onfoundational atomistic model90% confidence1 source
- MACEapplies toargyrodite Li6PS5Cl88% confidence1 source
- MACEimplementsmachine learning interatomic potential88% confidence1 source
- MACE-FNOdepends onMACE88% confidence1 source
- MACEimplementsmachine-learned interatomic potential88% confidence1 source
- molecular dynamicsimplementsMACE85% confidence1 source
- MACEapplies toEarth's core materials simulation85% confidence1 source
- MACEdepends onmachine-learned interatomic potential85% confidence1 source
- MACEdepends ongraph neural network85% confidence1 source
- MACEimplementsmolecular dynamics85% confidence1 source
- MACEapplies tohigh-throughput materials screening80% confidence1 source
- MACEapplies tointeratomic potential modeling75% confidence1 source
Sources
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