reitzensteinm

After completing a Hardcore Hell Sorceress run, I’m happy to report our CPUs are fully compatible with this software.

In a contemporary interview with Marques Brownlee, Musk said they didn’t currently have the technology and the specs were an extrapolation for what they expected to be available on release.

This isn’t a comment on your broader point.

If they’re rushing the M7, it’s possible the M6 Pro and Max will be MacBook Ultra only. It would certainly give it quite a halo.

By double counting the loss of the item and the lost revenue you can really make a title seem worth a click.

Yes

Paying a second of CPU time is an inconvenience to a user but trivial for LLM scraping.

The GPU cost to pretrain on that page once will dwarf by 2-3 OOMs the CPU cost to compute Anubis, scrape and post process it. And you’re not going to just train on it once!

At best you’re creating a speed bump for wannabe players scraping with no real plan. The folks training models people use just do not care.

You're right, I was talking past you.

I have an implicit belief that SQL isn't the most effective low level language we could have and LLMs will free us up to explore that space, similar to asm.js -> WASM. But I'm open to being wrong about that.

LLMs are also very good at writing code for newly invented languages, especially if they can execute it and iterate. I strongly believe the barrier to switch languages is lowered in a post LLM world.

Ten years ago I was at a startup where we used Datomic, and it was okay, but six months in the sales team was like “ok how do I run SQL queries so I can triage leads”. We had no answer of course.

Today it would simply be: type what you want in natural language and we’ll generate the query with Claude.

I just tried one representative query from that startup against a hypothetical datalog query tool in Rust and it did just fine.

What about cases where e.g. there's an earthquake with thousands of incidents and you need to triage help to the worst? It's not common, but there are absolutely cases where small amounts of intelligence applied in parallel is a genuine advantage.

M:N distribution itself has been massively devalued in Space Age - it’s so cheap and easy to build everything from scratch in situ with the new production buildings.

Eg you don’t need city blocks making circuits, just pipe in molten metal and make them with foundries and EM plants. And then you also get steel, copper wire, gears, whatever else you might need.

There are a few exceptions of course, like lubricant for electric engines, but it’s not nearly as complicated as it was pre Space Age.

Washing ore is probably the easiest solution - research high levels of mining productivity, put quality modules in drills, filter off uncommon+, and loop them through recyclers until they are at the desired quality level.

It’s inefficient but has a very low cognitive load.

You can improve the efficiency a little by increasing the quality floor each level, eg rare iron ore, epic iron plate, legendary steel. But in my post endgame playthrough I was drowning in so much legendary ore with this method I didn’t bother.

I agree they’ll be viable. They’re much harder to use but roughly equally good.

Also my late game experience is probably not representative of the phase just after victory where trains may have a slight edge - there could be a sweet spot there where the decoupling is worth it because you can horizontally scale through bottlenecks.

By the end I was using dedicated patches for each science so trains just get in the way.

Yes. Quality boosts storage for wagons and speed for trains. Also unloading is more compact due to inserter belt side selection.

I did a 1m eSPM base though, and I don’t think the totality of all of that would bring me back to trains. Belts are extremely reliable, and I have never managed to make trains so.

If anything, in immature engineering organizations, preserving netcode invariants to successfully deliver a multiplayer project might benefit from a little of that disposition.