Core Functionality - SDV is an open-source framework leveraging ML to learn patterns from real data [1] - Generates tabular synthetic data at scale [1] Key Features - Supports built-in anonymization [1] - Includes validation capabilities [1] Data Handling - Enables training AI models on data that does not exist, implying synthetic data generation [1]

We’re at MLSys in Santa Clara, California from May 12–15, and we’d love to talk to you.Register to connect with us here: https://t.co/3W7AO36iCwAt Isomorphic Labs, we’re scaling, which means building both a world-class research team and a world-class engineering team to support the rapid growth of our best-in-class AI models.We’re currently looking for:➡️ MLOps engineers to build and scale our training and inference infrastructure➡️ SREs to ensure the reliability of our training runs➡️ Engineers passionate ...

“We’re building generalisable AI models capable of learning from the entire universe of protein and chemical interactions. This fundamentally breaks from the target-specific, siloed approach of conventional drug development.”Tune in to hear our Chief Technology Officer, @SergeiIakhnin, and Chief AI Officer, @maxjaderberg on the NVIDIA AI Podcast, where they discuss how Isomorphic Labs is applying cutting-edge AI to reimagine drug discovery, and what it means for the future of precision medicine.Listen to th ...