More than $4B of deals between biopharma companies and AI specialists were announced last year. Similar to the massive quality leap from GPT-2 to GPT-4 and the record-breaking consumer adoption rates of AI tools, that same exponential progress and uptake is coming to biotech AI. 2024 may bring the first one-trillion-parameter protein language model. Companies are already using AI to program, as opposed to discover, antibodies. This level of opportunity and change brings with it urgency—— companies need to rethink from the ground up how their R&D should work to compete in a new era defined by the intersection of biology, data, and AI. In this webinar, learn how companies are updating their approach to R&D, with a focus on: AI-Ready Data: Improving generation of high-quality biomedical data to support AI model building and model tuning AI-Enabled Scientists: Integrating the right models directly into scientists’ workflows for everyday use Scalability: Making performance, speed, privacy, and cost tradeoffs for deployment of AI, and connecting the wet and dry labs