Innovation has always been a part of healthcare. It’s in the DNA of the industry - but so is caution. And that makes sense. “First, do no harm” isn’t just a motto; it’s a mindset. It wasn’t all the long again that arthroscopic knee procedures arrived on the scene. The first hip implants. The first heart transplants. These aren’t ancient history - they were bold experiments not that long ago. Plates, screws, bypasses...things that seem routine today once sounded risky, even radical. But pioneers leaned in. They stayed curious. They refined the techniques. They produced better outcomes. And one by one, those new ideas became the standard of care. We’re standing at that same threshold again. But this time, the innovation isn’t just surgical - it’s systemic. And it’s coming in the form of language and data. For the first time in our lives, the language of healthcare - contracts, care plans, coding structures, integrations - is available at scale, understandable by machines, and ready to be used as a tool for transformation. And now, that language is paired with something even more powerful: data. The underlying force behind this leap is the rise of large language models (LLMs) - the most significant technological advancement since the internet. Investment in this space is staggering: OpenAI has raised over $13 billion, Anthropic has secured more than $7 billion, and Mistral, Inflection, Cohere, and others are attracting billions more. Why? Because these models aren’t just novel - they’re monumental in scale. To put it in perspective: - GPT-1, the first step on this journey, was the size of a grizzly bear— relatively contained, with 117 million parameters. - GPT-2 grew into a whale, reaching 1.5 billion parameters. - GPT-4? It’s a small planet by comparison, with reportedly trillions of parameters and capable of consuming and computing across hundreds of trillions of tokens—enough to digest and make sense of the global healthcare lexicon many times over. This is no longer theoretical. It’s real. The language models are trained. The infrastructure is built. And the integration is already underway. At the same time, data has evolved from a static resource to a dynamic engine. We’ve always had data in healthcare. What we haven’t had is the ability to organize it, analyze it, and act on it - at scale and at speed. Now, we can. We’re entering an era where machine-readable language and AI-ready data can turn insight into impact - quickly and repeatedly. Whether it’s aligning teams, optimizing schedules, unlocking patient insights, or improving financial performance, the shift is here. We finally have the tools to move from information to execution. The question now is: Will we embrace it? We know from history that innovation doesn’t wait. The wins go to the bold. They always do. And today, the bold aren’t just doctors pushing the edges of clinical possibility—they’re also the administrators and operators with the courage to reimagine how healthcare works behind the scenes. Will we cling to what’s comfortable? Or will we lead like the medical pioneers we’ve supported for decades? It’s not about reckless adoption. It’s about thoughtful integration. Human-in- the-loop AI is the only responsible path forward in healthcare. And that’s exactly what makes this moment so exciting. Because when we pair these new tools - language and data - with sound human judgment, we unlock new possibilities for healthcare that were simply out of reach before. Better performance. Greater transparency. Stronger outcomes. The time is now. To be open to change. To trust in progress. To continue to believe that new and different can mean better. At The Hive, we’re not waiting for the future to arrive – we’re partnering with the pioneers, building, and creating real, measurable savings that make a difference. Let’s get to work. Rick Anderson CEO & Chairman The Hive Health
