H-Optimus-0 shipped fully open. H-Optimus-1 is free for research and licensed for commercial use. M-Optimus is commercial-only, for now. This post explains the thinking behind those choices: why openness is strategy rather than charity, why we learn more from a model we give away, where it costs us, and why our most capable models arrive in stages.
H-Optimus-0 shipped fully open. H-Optimus-1 is free for research and licensed for commercial use. M-Optimus is commercial-only, for now. This post explains the thinking behind those choices: why openness is strategy rather than charity, why we learn more from a model we give away, where it costs us, and why our most capable models arrive in stages.
H-Optimus-0 shipped fully open. H-Optimus-1 is free for research and licensed for commercial use. M-Optimus is commercial-only, for now. This post explains the thinking behind those choices: why openness is strategy rather than charity, why we learn more from a model we give away, where it costs us, and why our most capable models arrive in stages.
Explore the key technical hurdles and approaches involved in evaluating Biological Foundation Models (Bio FMs) for biopharma, from raw model performance to the necessity of biological interpretability, data integrity, and needs clinical contexts.
Explore the key technical hurdles and approaches involved in evaluating Biological Foundation Models (Bio FMs) for biopharma, from raw model performance to the necessity of biological interpretability, data integrity, and needs clinical contexts.
Explore the key technical hurdles and approaches involved in evaluating Biological Foundation Models (Bio FMs) for biopharma, from raw model performance to the necessity of biological interpretability, data integrity, and needs clinical contexts.
Biopharma needs its own class of AI because Biology Foundation Models, unlike text-trained LLMs, learn directly from the native, multi-scale experimental data of life—enabling biologically faithful insights that can meaningfully improve biomarker discovery, patient stratification, and drug development outcomes.
Biopharma needs its own class of AI because Biology Foundation Models, unlike text-trained LLMs, learn directly from the native, multi-scale experimental data of life—enabling biologically faithful insights that can meaningfully improve biomarker discovery, patient stratification, and drug development outcomes.
Biopharma needs its own class of AI because Biology Foundation Models, unlike text-trained LLMs, learn directly from the native, multi-scale experimental data of life—enabling biologically faithful insights that can meaningfully improve biomarker discovery, patient stratification, and drug development outcomes.
We have recently released H-Optimus-1, a new foundation model (FM) for pathology.
We have recently released H-Optimus-1, a new foundation model (FM) for pathology.
We have recently released H-Optimus-1, a new foundation model (FM) for pathology.
We are proud to launch Bioptimus. Our company mission? To create and build the first universal AI foundational model for biology.
We are proud to launch Bioptimus. Our company mission? To create and build the first universal AI foundational model for biology.
We are proud to launch Bioptimus. Our company mission? To create and build the first universal AI foundational model for biology.
Creating the first and only Foundation model for biology
Creating the first and only Foundation model for biology
Creating the first and only Foundation model for biology