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  • Weird. I would assume that rocks would be problematic for snow and would just encourage snow to stick and add street to the framing.

    The only rock roofs I’ve ever come across are in temperate places that don’t get snow.

  • Weird. I a few months ago I stumbled upon two mid century apartments in my town that both had rock roofs.

    I wonder OP’s roof didn’t used to be painted.

  • Thank god the vegancokehead signed this meme. That way I know who to google when I’m looking for their MoMA shitpost exhibition.

  • To each their own. I don’t dislike the industrial design. I particularly like the tail lights.

    The chrome plastic on the bumper and the drive mode selector are what feel the weirdest to me. They look cheap. Poor material selection.

  • I think that’s an intentional optical illusion. The black trim on the bottom goes pretty high up, and the trunk curls up from the ground quite a bit, and there is a higher up protrusion on the front bumper that makes the the bumper look higher than it is. The combination of those three things make the eye follow a base line that’s higher than what actually exists.

    My guess is that they waned smaller wheels and a lower ride, but they know Americans like crossovers and big wheels, so they did some magic tricks with the trim.

    IMHO, it kind of works. It fooled me until I really started scrutinizing it.

  • Researchers found that a fan next to some dirt blew the dirt around.

    Wait until they start researching leaf blowers.

  • Yes, mice eat red meat.

    Mice are omnivores and are opportunistic eaters. They’ll eat whatever they can find.

  • When do you think he’ll start shit posting about this on his social media platform?

    I’ll throw $20 down on 11pm est

  • There is a lot of top down shit, but there is definitely bunch non c-suite enterprise customers out there. A lot of product managers are curious about this shit.

  • Did Great Britain move in with Mexico after it broke up with Europe?

  • The point of a prototype is collaboration. It’s to get feedback from colleagues and end users.

    Previously we’d whiteboard that out, spend a few days writing some code or stitching together a figma prototype to achieve a similar results.

    I feel ya on the energy use, but don’t see how this is going to get me sued or isn’t allowing me to collaborate. The prototype code is going to get burned anyway, and now I my coworkers and I can pressure test ideas instantly with higher fidelity than before.

  • Once again, it all depends on the use case. The other day I used an LLM quickly mockup a carousel UI so I could see if it was worth writing real code for. It helped me explore a couple bad ideas before I committed to something worth coding.

    I’m not actually checking that code in. I’m using the LLM like a whiteboard on steroids.

  • All I’m saying is that is you ask people about AI with no use case, you’re going to get different answers than if you ask people about AI when it’s contextualized to a specific problem space.

    If I ask a bunch of people about “what do you think about automobiles,” I’m going to get a very different answer than if I ask “what do you think about automobiles that are used as ambulances” or “what do you think about automobiles instead of mass transit.”

    Context will give you a very different response.

  • America has something called the EnergyGuide, which looks like this.

    Energy”Star” is a little certification logo that gets awarded to products that reach certain efficiency targets.

  • Yeah, it’s basically like early days of cable, Uber, Instacart, streaming, etc. They have a lot of capital and are running at a loss to capture the market. Once companies have secured a customer base, they start jacking up the prices.

  • people don’t really like ai

    Once you start asking about AI in regard to specific use cases, I think you’ll find that quickly changes.

    My company and I have been running a lot of studies around how and where people find value in these tools, and a LOT of people find LLMs useful for copy writing, doing quick research, data visualization, synthesis, fast prototyping, etc.

    There’s a lot of crap that AI is bad at in 2025. Especially the poor in-app integrations that everyone is trying to standup. But there are a lot of use cases where it does provide a lot of value for people.

  • If anyone else was wondering why the article is talking about Miss United States and not Miss America - Miss United States is apparently a different thing. Two different pageants.

  • Nope, just a food delivery app.

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