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People often prefer to see those who are similar to them in a positive light, since that’s their primary frame of reference. Some struggle to grasp that someone with a completely different perspective or set of social skills can have something valuable to offer. I see this most in hiring practices where hiring managers ask highly personal questions and claim it is to check your "cultural fit", but they are probing for people similar to them. I also see it in how people treat others they’ve just met that are from a completely different background, there is typically a faint form of aggression for literally no reason.

> At the opposite end of the personality spectrum are insecure people, who I’d also avoid, as they tend to see credit as a zero-sum game, needing to diminish you to bolster themselves.

Like many sweeping broad statements, it is entirely useless to base decisions on. The world isn't black and white, there are shades of gray all around.


Recently, a lot of development in this area has been in gaussian splatting and from what I have seen, the new methods are super effective.

https://en.wikipedia.org/wiki/Gaussian_splatting

https://www.youtube.com/watch?v=6dPBaV6M9u4


The parent explicitly asked for a mesh.


You can never be sure what someone's real intent is. They might mean "something meshlike". Personally I usually reply by asking for more info (I always have the XY Problem in my mind) but that is time consuming and some people assume you're being pendantic (I am however correct more often than not - people have posed the wrong question or haven't given critical parts of the context)


Yeah, I am explicitly asking about meshes, which is why I said that and also referenced photogrammetry. Sometimes people know what they're asking for help with.

Thanks for the links. Going to check them out this morning.


Just to be clear I wasn't singling you out. I don't know anything about you.

And furthermore I also often post questions that lack sufficient context.

My point was that it's always okay to ask for clarification or to assume that there was maybe some broader contact context or to offer a suggestion that doesn't follow the most literal interpretation of the question as asked.


The second link I posted contains n flow from splats to meshes


Yeah some very impressive stuff with splats going on. But I haven't seen much about going from splats to high quality 3D meshes. I've tried one or two with pretty poor results.


There have been a few papers published on the topic, but it's "early days".

Expect a lot of progress over the next couple of years.


Splats to meshes is an isosurface extraction problem, fundamentally. It's one of the great unsolved problems of computer graphics and having a good general algorithm would have massive ripple effects for any problem involving meshes.

It's a rabbit hole and I only really understood it when I realized that the minimum time between any GH committer's hobby example and implementing the 2003 state-of-the-art is ~4 years.

Fingers crossed that Gaussian Splatting makes the rewards high enough that resources get poured on this.


It's been a while since I read this article, but I remembered the title and it seems to imply that it is relevant

https://www.bitsaboutmoney.com/archive/optimal-amount-of-fra...


Imagine the insurance...


Yeah, when I listen to the videos my mother is watching on Facebook, 90% of the content is narrated by a bot. I'd imagine AI content is also super popular on TikTok. Folks on HN should keep in mind they are not representative of the average person when it comes to tech.


Norm Mcdonald also has a horrible joke about it

https://www.youtube.com/watch?v=n3LMSflEN54


The thing is, this payment from Google is billions in pure profit. If it were to stop, it would have a serious impact on Apple's valuation. Shareholders would want management to do anything they can to keep that cash flow coming.


The free version of chatgpt is better than your 70b LLM, whats the point?


The performance-per-watt isn’t necessarily the best. These scores are achieved when boosted and allowed to draw significantly more power. Apple CPUs may seem efficient because, most of the time, computers don’t require peak performance. Modern ARM microarchitectures have been optimized for standby and light usage, largely due to their extensive use in mobile devices. Some of MediaTek and Qualcomm's CPUs can offer better performance-per-watt, especially at lower than peak performance. The issue with these benchmarks is that they overlook these nuances in favor of a single number. Even worse, people just accept these numbers without thinking about what they mean.


M4 is also an ARM architecture, why would Qualcomm's be more efficient?


Since Qualcomm is using these custom cores to launch into the pc market and directly competing with x86


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