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As interest in AI continues to surge, scientists and researchers face crucial questions when developing an AI strategy for R&D: What data will I use to train my models? Do I have enough data? Is it well-labeled and stored in the cloud? What AI strategy options are available to me? 🔎 Areas of focus may include: – Generative AI & LLMs for navigating R&D data – 2D & 3D Research Image data & AI algorithms that process them – Deep learning methodologies for predictive algorithms – AI that supports generation of computational life science models Join MetaCell and experts from leading research organizations, including Genmab, UCSD, and SUNY Downstate, as we share our experiences with AI and Machine Learning projects. The Q&A addresses key challenges, common pitfalls, actionable insights, and successful case studies. 🌐 Speakers: – Stephen Larson, CEO & Co-founder, MetaCell – Maryann Martone, Professor Emeritus, Department of Neuroscience, UCSD – Salvador Dura-Bernal, Assistant Professor of Computational Neuroscience, SUNY Downstate – Rama Shah, Senior Manager, Commercial Operations, Genmab 🎯 Key takeaways: In the current AI frenzy, navigating the landscape can feel like the wild west. At MetaCell, we've been charting this territory for a while and have valuable insights to share. The talk will be particularly beneficial for those looking to build cloud solutions for intelligent gathering and storage of biological data, and to set a strong foundation for effective AI strategies.