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And so, you know, I absolutely think people want to buy from people. I think that's still a very powerful concept in that these larger and firms that are investing in AI mechanisms and tools and giving up on and their hiring and and retention are going to see that lack in in the market reaction. You know, there's there's always pendulum swing swings as as new tools are developed, but I think ultimately you know, under capitalism and exponential profit, you know, you're going to still need people to buy products and use software and access services. And if those people aren't employed, there is going to be no one. I mean, that's sort of a catastrophic, dystopic look. But I have to say from my my academic background, i'm I'm often thinking about those more structural and systemic implications. And I think that, you know, that, yeah, that there will be a cost to that in a to put it as long as I could have possibly responded You know, I agree with you. If 70% of GDP is run by consumers and and then you put consumers out of work, you're just not feeding the system. that right I'm going to send you a link after this ah podcast. We wrote a paper and and released it last week and we compared our machine learning, which is very task oriented to the energy and water use of LLMs. And we came out with a glint because we're so focused in the way we built our machine learning. It's very purpose-built. It's not a generalist thing. We're less than 5% of the energy and water use for comparable tasks. and Wow, that's very exciting. Congratulations. it It's cool, yeah. And it really shines a light on the efficiencies of our machine learning. It shines a light on the value of how we think about things and measure sustainability. And what I learned about it is, boy, if I am an SME and I need to do my data center emissions,