NOVA: Emission Split Update for Data Generation Fund

METANOVA LABS@metanova_labs

NOVA: Emission Split Update for Data Generation Fund Owner 26% / Miners 33% / Validators 41% With the launch of eTAO, subnet owners can now adjust how emissions are distributed. NOVA will be updating its split to allocate more resources toward what we believe is the highest-impact investment we can make in the subnet's future: experimental data generation. Wet lab data is the best investment we can make both to prove out what the subnet produces and to increase the value of what gets built on top of it. Data is the bottleneck AI-driven drug discovery faces a fundamental constraint: the quality of our predictions is ultimately limited by the experimental data available to train and validate them. Much of today's publicly available drug discovery data is fragmented across studies, generated using different experimental protocols, and inconsistent in quality and coverage. Generating high-quality experimental data allows us to address that limitation directly. It gives miners better ground truth for model development, provides independent validation of their predictions, and helps us identify which approaches actually translate into experimental success. The industry is making the same bet. Some of the largest investments in AI-driven biology are now directed toward generating the experimental data necessary to train and validate better models. Biohub committed $400M of a $500M, five-year initiative to data generation, infrastructure and measurement technology, and later expanded into a $1.8B effort backed by Meta, Google DeepMind and Isomorphic Labs, who collectively committed $300M. The OpenAI Foundation gave $15M to OpenADMET to generate public ADME datasets, which will be used in prospective blind challenges against newly measured experimental data. Octant continues the high-throughput data generation behind it. Leash Bio used a $9.3M seed round to scale data collection for a foundational medicinal chemistry model, producing a dataset that screened 133…

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