Saw that DGX Spark vs Mac Mini M4 Pro benchmark plot making the rounds (looks like it came from @lmsysorg). Thought I’d share a few notes as someone who actually uses a Mac Mini M4 Pro and has been tempted by the DGX Spark. First of all, I really like the Mac Mini. It’s probably the best desktop I’ve ever owned. For local inference with open-weight LLMs, it works great (the plot above captures that well). I regularly run the gpt-oss-20B model on it. That said, I would not fine-tune even small LLMs on it since it gets very hot. The DGX Spark probably targets that type of sustained workload. (From those who have one, any thoughts on the noise and heat levels?) The other big thing that DGX Spark gets you is CUDA support. If you use PyTorch, that’s pretty essential since MPS on macOS is still unstable, and fine-tuning often fails to converge. E.g., see github.com/rasbt/LLMs-from-s… and github.com/rasbt/LLMs-from-s… I also like the Spark’s for factor (hey, it really appeals to the Mac Mini user in me). But for the same money, I could probably buy about 4000 A100 cloud GPU hours, and I keep debating which would be the better investment. Sure, I could also build/get a multi-GPU desktop. I had a Lambda system with four GTX 1080 Ti cards back in 2018, but it was too loud and hot for my office. And if I have to move it to another room and SSH into it anyway, I might as well use cloud GPUs instead?

we're going to hit a breaking point soon, idk when but at that point, verified human internet apps are gonna start to look really, really good and i think even a step further than that, we're probably looking at the end days of the anonymous internet for social applications

🤔

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To me, seems like @sama telling us we need “proof of human” in an increasingly agentic world PS: $ETH is at the center of that solution (among others)

this explains a lot

So there’s 8px padding on the left and 12px on the right to make it optically centred

The rise and fall of the vector database category

When a model gives you the right answer to a reasoning question, you can't tell whether it was via memorization or via reasoning. A simple way to tell between the two is to tweak your question in a way that 1. changes the answer, 2. requires some reasoning to adapt to the change. If you still get the same answer as before... it was memorization.

Lmao, is this true??

🇪🇺 JUST IN: EU expedites digital euro plans with consideration to build on Ethereum instead of private networks, per FT.

Got a DM: the CCP has disappeared Wenfeng for his criticism of Chinese business culture in an interview a year ago. Think about it: when has anyone last seen him? DeepSeek is headless now… They always kill the goose that lays golden eggs. Like Jack Ma. This is why America wins.

Wishful thinking. You don't get how big a disaster V3.1 is… Xi killed DeepSeek with forced labor on Huawei plantations it's over. America won

Meta, $META, to downsize AI division, some executives expected to leave, per NYT

The Anthropic magic sauce is well and alive a non-TTC model beating GPT-5-high

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time to see how far this locodiff curve can go

economic security ATH & 10x flippening Ethereum: $150B = 35.7M ETH × $4.2K/ETH Bitcoin: $15B = 1B TH/s × $15/(TH/s) Ethereum is the embodiment of security. 100% uptime. Rich client diversity. 8K consensus participants. Massive slashable economic security. There is no second best. BTW @saylor—offer still stands. Let's debate Bitcoin's security. You can't outrun fundamentals: halvings gut the security budget, fees are 1% of miner revenue ☠️

From the AI workshop I'm in: "The S in MCP stands for security"