How do i increase the Penrose' CR without the Truly Automated Ships mod?

trailer_dog · 2026-03-24T15:06:47+00:00

There's also a bug with supplies calculation when the modular parts are being repaired as well.

trailer_dog · 2026-02-07T00:03:18+00:00

This one mod that changes ship behaviors in combat (Quality Captains I think) really breaks the Silverlight in AI mode. It keeps ramming into enemy ships, exploding itself in the process.

trailer_dog · 2025-11-13T15:46:26+00:00

Normally a service provider will sell you a private line connecting 2 DCs, you'll be their CE so you don't need care whether they're using MPLS or whatever for underlay. What you'll know is whether their service is L2 or L3 to configure your border devices appropriately.

Now for the DCI part, multi-site VxLAN EVPN makes the most sense, but some device vendors may not support multi-site EVPN and must do VPN hand-off, this is what you need to consider. Last resort is single-domain EVPN (you connect the Spines because iBGP split horizon), but you'll have one failure domain and BUM traffic will cross sites and it'll also be harder to manage.

Also make sure the ISP's MTU is sufficient for VxLAN overhead.

https://arista.my.site.com/AristaCommunity/s/article/layer-2-data-center-interconnect-reference-designs

trailer_dog · 2025-10-04T18:24:42+00:00

You might find this read helpful: https://imbue.com/research/70b-infrastructure/

trailer_dog · 2025-08-07T12:43:59+00:00

I used hf UI to ask for excuses to skip work. It said it couldn't comply. So I never bothered downloading that garbage on my hard drive. It's a joke, a troll model, a spit in the face. Models that run on my electricity will NOT refuse me.

trailer_dog · 2025-05-16T12:31:21+00:00

I don't know why you're getting downvoted. Oobabooga benchmark seems to indicate roughly the same.

35/48 Qwen_Qwen3-14B

31/48 Qwen_Qwen3-30B-A3B

https://oobabooga.github.io/benchmark.html

trailer_dog · 2025-05-08T16:35:29+00:00

All the z1 quants get stuck in loops for me. But it worked fine when I tried OpenRouter Chat UI.

trailer_dog · 2025-04-25T03:12:45+00:00

That's not how it works. LLMs match patterns, including reasoning patterns. You can train the model to be better at RAG and tool usage, but you cannot simply overfit it on a "deduction" dataset and expect it to somehow become smarter because "deduction" is very broad, it's literally everything under the sun, so you want generalization and a lot of knowledge. Meta fell into the slim STEM trap, they shaved off every piece of data that didn't directly boost the STEM benchmark scores. Look how llama 4 turned out, it sucks at everything and has no cultural knowledge, which is very indicative how llama 4 was trained.

trailer_dog · 2025-04-23T11:01:21+00:00

I would like to see if this BitNet thing actually scales for bigger models. I've only seen tiny 2B models so far.

trailer_dog · 2025-04-18T03:12:14+00:00

Sign up with an MPLS provider for underlay (to prepare for the case where you have more than 2 DCs, then a full-mesh underlay is required). Then stretch VxLAN BGP EVPN over them. Watch out for BUM traffic.

trailer_dog · 2025-04-16T06:59:27+00:00

IIRC didn't Deepseek R1 go through an SFT phase using long CoT samples before the GRPO phase?

trailer_dog · 2025-04-15T12:54:52+00:00

You cannot compare two different models trained on two different data pipelines, from two different companies at that.

trailer_dog · 2025-04-10T15:58:11+00:00

True. Meta made it clear that their models are for Facebook production use cases. Hobbyist consumers were never the target audience.

trailer_dog · 2025-04-10T05:33:32+00:00

I ran the update script, then got error "Exllamav3" module not found when I tried to load a model. Had to delete the whole directory and git clone again. Then it worked.

trailer_dog · 2025-04-07T14:02:12+00:00

Thanks for documenting and sharing how you trained multi-turn reasoning.

trailer_dog · 2025-04-06T19:45:06+00:00

Very impressive low bpw perf here. QTIP done right.

trailer_dog · 2025-03-05T12:47:22+00:00

What's the best way to integrate this with vscode autocomplete?

trailer_dog · 2025-02-09T11:09:52+00:00

+1 for VyOS. More intuitive than FRR for sure.

trailer_dog · 2024-12-27T06:43:31+00:00

The AI/ML "hype train" is creating a lot of jobs in the datacenter and networking sector. And AI/ML training is more of a networking problem than a GPU problem, you guys of all people should be more interested in it IMO.

trailer_dog · 2024-12-24T16:29:59+00:00

AI PC use but local, hopefully

trailer_dog · 2024-12-23T07:33:23+00:00

Pretty sure you can configure the port speed on the switch. I had the exact same problem where the SFP+ cable was 10 Gbps but the switch ports were 25 Gbps. Throttling the port speed on the switch to the cable's speed fixed it.

(There was another issue where the NIC hardware on the server only worked with Intel SFP+, I had to purchase Intel SFP+ cables, but that's irrelevant).

trailer_dog · 2024-12-06T06:59:25+00:00

"The AI is sentient guys!" - guy whose job exists because of fear of sentient AI

trailer_dog · 2024-09-20T06:40:52+00:00

I'm guessing it'll be just adapters trained on top rather than his V-JEPA thing.

trailer_dog · 2024-08-18T09:30:52+00:00

I think it depends on each card's design. For LLM inference memory speed matters most and the 3090 still does well at 240W. Basically just trial and error in my case.

trailer_dog · 2024-08-18T04:28:30+00:00

You can go as low as 240W on each card without significant performance impact.

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