Tell me what that means to these very specific use cases and the importance of context now as part of the overall solution.

Yeah, I think there is a perception that there is a AI magic wand which can be waved across the data and everything falls in order.

The challenge is these AI models are very good for compute and processing power and ability to run things much faster.

But without answering the question, the prompts, what questions are they answering? and how are they actually solving for a problem, and what problem are they trying to solve, is all defined by that individual who's working in the medical field, or in a hospital system, or in an administration which controls this hospital workflows, or health plan workflows.

right without that input to that ai model you can have the most powerful ai models but the context becomes so important and what they're trying to solve for the challenge in healthcare has been healthcare industry is trying to copy some of the methods pathways from other industries there is also a problem with that because typically these industries go for point solutions whereas healthcare point solutions may not be applicable because it's a very integrated workflow between a career, a provider, sometimes an employer, the member, patient pathways, care coordination, utilization.

It's much more complex, which is why it is the biggest industry too.

So to thread them all together and thread all the data fields together, even if you bring the data together without understanding the context, It will not go anywhere.

Can you comment maybe on some examples of that?