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\n AQCat for materials discovery will be available first, followed by AQPotency for drug discovery<\/p>\n
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\n AQCat for materials discovery will be available first, followed by AQPotency for drug discovery<\/p>\n
SandboxAQ<\/a> announced it will make its Large Quantitative Models (LQMs) accessible through Google Cloud\u2019s Marketplace. Through this marketplace listing, users will be able to tap rigorous, physics-grounded scientific models directly from the conversational AI tools they already use, with no specialized code or infrastructure required.<\/p>\n LQMs are AI models built on real-world lab data and scientific equations, engineered for the more than $50 trillion global quantitative economy including sectors such as biopharma, energy, advanced materials, and financial services. By offering LQMs within GCP Marketplace, SandboxAQ extends the reach of its LQMs across more channels and more large language models, while Google Cloud strengthens its capabilities in healthcare and drug discovery.<\/p>\n Also Read:\u00a0AiThority Interview with Matej Bukovinski, Chief Technology Officer at Nutrient<\/a><\/p>\n Brian Goldstein, Vice President Strategic AI and ISV, Google Cloud, said \u201cBringing SandboxAQ\u2019s Large Quantitative Models to GCP Marketplace is one of the ways we are empowering healthcare researchers to accelerate drug discovery and solve one of the most critical gaps in healthcare today.\u201d<\/p>\n \u201cBringing our LQMs to Google Cloud\u2019s Marketplace will put the rigor of first-principles science directly into the hands of every researcher, in the tools they already use,\u201d said Jack D. Hidary, CEO of SandboxAQ. \u201cPairing the reasoning of a frontier model such as Gemini with the quantitative precision of our LQMs is a powerful combination.\u201d<\/p>\n The collaboration builds on SandboxAQ\u2019s broader strategy of connecting its LQMs to leading large language models, following its recent integration with Anthropic\u2019s Claude.<\/p>\n Also Read:\u00a0\u200b\u200b<\/a>AI systems \u2013 Interoperable AI systems: Connecting models across platforms<\/a><\/p>\n