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Claude AI built me a React app to compare maps side by side

(github.com)
221 points caspg | 2 comments | 17 Nov 24 13:39 UTC | HN request time: 0.671s | source
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jckahn ◴[17 Nov 24 14:56 UTC] No.42164495[source]▶
This sort of thing will be interesting to me once it can be done with fully local and open source tech on attainable hardware (and no, a $5,000 MacBook Pro is not attainable). Building a dependence on yet another untrustworthy AI startup that will inevitably enshittify isn’t compelling despite what the tech can do.

We’re getting there with some of the smaller open source models, but we’re not quite there yet. I’m looking forward to where we’ll be in a year!

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1. phony-account ◴[17 Nov 24 15:39 UTC] No.42164721[source]▶
> (and no, a $5,000 MacBook Pro is not attainable)

I know we all love dunking on how expensive Apple computers are, but for $5000 you would be getting a Mac Mini maxed-out with an M4 Pro chip with 14‑core CPU, 20‑core GPU, 16-core Neural Engine, 64GB unified RAM memory, an 8TB SSD and 10 Gigabit Ethernet.

M4 MacBook Pros start at $1599.

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2. zamadatix ◴[17 Nov 24 16:08 UTC] No.42164902[source]▶
I get where GP is coming from and it's not really related to typical Apple price bashing. You can list the most fantastical specs for the craziest value and it all really comes down to that single note: "64 GB memory for the GPU/NPU" - where the mini caps out. The GPU/NPU might change the speed of the output by a linear factor but the memory is a hard wall of how good a model you can run and 64 GB total is surprisingly not that high in the AI world. The MacBook Pro units referenced at $5k are the ones that support 128 GB, hence why they are popularly mentioned. ~ the same $ for the Mac Studio when you minimally load it up to 128 GB. Even then you're not able to run the biggest local models, 128 GB still isn't enough, but you can at least run the mid sized ones unquantized.

What I think GP was overlooking is newer mid range models like Qwen2.5-Coder 32B produce more than usable outputs for this kind of scenario on much lower end consumer (instead of prosumer) hardware so you don't need to go looking for the high memory stuff to do this kind of task locally, even if you may need the high memory stuff for serious AI workloads or AI training.