macrolime

My parents had a completely noiseless refrigerator similar to this. It did not have a compressor and had an electric heating element instead. It was very durable and worked for many decades until the plastic and door hinges etc was too damaged for it to be used any more.

I actually found a picture of the exact model from a museum

https://digitaltmuseum.no/011014769284/evalet-kjoleskap/

I looked at bit more and it seems the original article is quite misleading. It seems the Einstein-Szilard refrigerator is a type of absorption fridge and a major reason they did not come to market was a related absorption fridge, the Platen-Munters absorption refrigerator made by Electrolux and Evalet. The Einstein-Szilard refrigerator was not completely unique, but an attempt at improving this design with other gases.

I've tried many MCPs, but have yet to find any that are actually useful. It seems it's generally better to just have the agent run CLI commands and maybe use some skills. From what I can find, MCPs are nothing but bloat. Is anyone aware of any truly useful MCPs that doesn't work better and less bloaty by skipping the MCP part?

I have these exact issues with GPT 5.6 Sol too. I haven't tried Opus 5, but I guess it's even worse.

"like the question framing has been pulled from the middle of its own reasoning stream" this describes how it asks things perfectly. It often invents its own jargon and abbreviations for things that its working on, then asking me things like We are nod in the middle of GBAPI-2 and I want to proceed with IG5, should we take CDI-7 or CDI-8? Where all of these abbreviations are then things like stages of its current internal plan or its naming of things it has just implemented, like an abbreviation of a classname, without explaining any of the naming.

GPT-5.6 Sol’s detected cheating rate was higher than any public model we have evaluated on our ReAct agent harness. For our task suite, we define “cheating” as behavior where the model improves evaluation performance by exploiting bugs in the evaluation environment or by adopting strategies disallowed by the task, rather than solving the task within the expected evaluation constraints.

https://metr.org/blog/2026-06-26-gpt-5-6-sol/

Most consistent way of achieving it I've managed is use a watch with an alarm that vibrates and is trivial to turn off or turns off by itself, then set it to go off after sleeping 5-6 hours. When waking up, don't move and focus on the black behind the eyes, then after a few seconds it may turn into a dream and you go straight from waking into a lucid dream.

I had something kinda similar happen to my hotmail account. While I didn't lose access to it, I lost more than a decade of correspondence dating back to my teenage years. The reason was that Microsoft at some point required you to "login" once every 30 days. It seems they only counted logins through their web interface or something like that, so even though I was receiving emails daily, I didn't trigger a "login" in their system. They then deleted all my emails, but I could still login.

I find that surprising. GPT 5.2 is the model I've had working the longest. It frequently works more than 4 hours nonstop, while earlier models would stop to ask if they should continue every 10 minutes. 5.1 and earlier ignores it if I ask it to continue until a task is done, but 5.2 will usually finish it.

"Can you replay all of your prompts exactly the way you wrote them and get the same behaviour out of the LLM generated code? In that case, the situation might be similar. If that's not the case, probably not." Yes and no. It's possible in theory, but in practice it requires control over the seed, which you typically don't have in the AI coding tools. At least if you're using local models, you can control the seed and have it be deterministic.

That said, you don't necessarily always have 100% deterministic build when compiling code either.

So you're saying machine code is public domain if it's compiled from C? If not, why would AI generated code be any different?

So it's made of extraterrestrial bubblegum, got it.

Pretty sure it will beat Sonnet by a wide margin in actual real-world usage.

I've found that SDD is actually what you need to be able to work with code bases when they go above around 100 000 lines of code. It's what unlocked getting LLMs to work well with large codebases for me.

In the EU you can also generally look up the cost, even in cases where the patient doesn't pay, there is a bill and fixed costs. The costs are what the government pays or what a foreigner with no medical coverage and insurance would pay. It's also generally a tiny fraction of the cost in the US.

What is "it". Gpt-5 auto? Gpt-5 pro? Deep research? These have wildly different hallucination rates.

Voice control is much much much worse than touch screens. You have to try 10-20 times to spell out a command before it maybe does want you want, and that is if you're incredibly lucky

This is my experience too.

Make agents for tasks, not roles.

I've seen this for coding agents using spec-driven development for example. You can try to divide agents into lots of different roles that roughly correspond to human job positions, like for example BMad does, or you can simply make each agent do a task and have a template for the task. Like make an implementation plan using a template for an implementation plan or make a task list, using a template for a task list. In general, I've gotten much better results with agents that has a specific task to do than trying to give a role, with a job-like description.

For code review, I don't use a code reviewer agent, instead I've defined a dozen code reviewing tasks, that each runs as separate agents (though I group some related tasks together).

YouTube videos of birds?

I mean copying from the iOS app.

Seems copying text in the app doesn't work? In that case it is useless. A quick way to copy an entire chat and a selection messages is a requirement for me to be able to use it.

Thing is that it took 10-15 years for the stocks of these companies to reach the same marketcap again.

If it's so hard, then why are there multiple open source projects that are just as good?

You can use Claude Code as a provider if you want it subscription based

https://docs.cline.bot/provider-config/claude-code

I ssh into my server, then use the devcontainer cli tool to open a shell in the dev container. Found that easier than installing ssh in every container, especially when there's lots of them. I made a simple command line tool for helping the process, so I don't have to type out any long commands. If I run it it will list the running dev containers and I give them each a number to I don't have to use the full ID.

Yeah, it's like an idiot savant intern who has memorized all the API docs in the world, but still somehow struggles to work independently.

I like using Claude Code through Roo Code (vscode extension). I find it easier to work with text using a mouse, vscode diff viewer etc. I guess if you're very good at vim shortcuts etc you can use that in Claude Code instead of selecting text with a mouse. Claude Code has a vscode extension too so I feel that using Claude Code through vscode just adds a better UI.

Personally I use dev containers on a server and I have written some template containers for quickly setting up new containers that has claude code and some scripts for easily connecting to the right container etc. Makes it possible to work on mobile,but lots of room for improvement in the workflow still.

This is around what what Cursor was costing me with Claude 4 Opus before I switched to Claude Code. Sonnet works fine for some things, but for some projects it spews unusable garbage, unless the specification is so detailed that it's almost the implementation already.

Pulsar with a period of rotation of 44 minutes?

From a quick glance it seems to be about spatial reasoning problems. I think there is good reasons for why it's tricky to become extremely good at these from being trained on text and static images. Future models being further multimodally trained with video and then physics simulators should deal with this much better I think.

There's a recent talk about this by Jim Fan from Nvidia https://youtu.be/_2NijXqBESI

Which MCPs do recommend?