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breatheoften

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GPT-5.6 13 days ago

i wish they had renamed chatgpt to codex instead of the other way around ...

The "program produces this trace, reproduce it after changing xyz" loop is imo -- a kind of programming primitive for the current agent capabilities ... I've found technique like that really effective as well.

It's interesting because there's a part of me that sometimes thinks "hey look this pattern is pretty effective -- I wonder if this a nascent abstraction on the path toward reasoning about how to use these tools in effective ways" -- while another part of me thinks "six months from now, you won't ever have to do this or if this is a useful technique the agent will just apply it on its own when relevant" ...

Apple WWDC 2026 1 month ago

Man that conversation history navigation for the new Siri app looks super unuseable ... how the hell am I supposed to actually find the conversation I want with the super-dynamic non-ordered 2-column offset-row view thing ...?

It looks hard to use ...

Also the 'floating semi-window but not a window' thing when using contextual siri in the context of some other app ... sure looks like it won't work with cmd-tab navigation ... I really hope is not the case ...

Is there anything structurally to prevent a super wealthy buyer from guaranteeing this essentially -- moving money and debt around in order to essentially put a floor under the stock and guarantee buy rates until the retirement fund index purchasers have time to absorb all the shares at the artificially high price? Feels to me like this is almost guaranteed to happen -- ...

This is extremely what Ive been wanting -- I had previously thought about using one of the hackish apps that try to deliver this experience - or spinning up something for this myself ... - but integrating this directly is definitely the right way to provide the best system and product experience -- and this seems to work out of the box exactly as I would want!

Like so many things -- the evolution of AI math will I think follow trajectories hinted at in the 90s by the all time great sci-fi author Greg Egan. The nature of math won't change -- but the why of it definitely will. Egan imagined a future ai civilization in Diaspora where "math discovery" -- by nature in the future perhaps accurately described as "mechanistic math discovery" is modeled by society as a kind of salt mine environment in which you can dig for arbitrarily long amounts of time and find new nuggets. The nuggets themselves have a kind of "pure value" as mathematical objects even if they might not have any knowable value outside the mines. Some personalities were interested in and valued the nuggets for their own sake while others didn't but recognized that there were occasionally nuggets found in the mind that had broader appeal.

Research institutes like those founded by Terence Tao in our current present feel like they will align to this future almost perfectly on a long enough timeline -- tho I think on a shorter timeline this area of research is almost certain to provide a ton of useful ways to advance our current ai systems as our current systems are still in a state where literally anything that can generate new information that is "accurate" in some way -- like our current theorem prover engines are enormously valuable parts of our still manually curated training loops.

Per-minute pricing for self-hosted runners seems like a very fast way for them to force everyone who actually is using self-hosted runners to migrate away.

I suspect we'll be doing that sometime in January or February.

I guess forgejo is the easiest migration path? https://forgejo.org/

I'm more and more convinced of the importance of this.

There is a very interesting thing happening right now where the "llm over promisers" are incentivized to over promise for all the normal reasons -- but ALSO to create the perception that the "next/soon" breakthrough is only going to be applicable when run on huge cloud infra such that running locally is never going to be all that useful ... I tend to think that will prove wildly wrong and that we will very soon arrive at a world where state of art LLM workloads should be expected to be massively more efficiently runnable than they currently are -- to the point of not even being the bottleneck of the workflows that use these components. Additionally these workloads will be viable to run locally on common current_year consumer level hardware ...

"llm is about to be general intelligence and sufficient llm can never run locally" is a highly highly temporary state that should soon be falsifiable imo. I don't think the llm part of the "ai computation" will be the perf bottleneck for long.

It takes more than just misaligned incentives to get a banking crisis -- you have to have structural corruption preventing the transfer of the loss gradient back to the "misaligned" decision makers. It's somewhat disingenuous (or overly innocent) to reimagine the pathways which power structural corruption as "innocent ignorance in the face of bad incentives".

The real world has "actually bad" actors -- not just misaligned incentives.

Docker Hub Is Down 10 months ago

In our ci setting up the docker buildx driver to use the artifact registry pull through cache involves (apparently) an auth transaction to dockerhub which fails out

Can there ever be a "living" standard to replace posix ...? Something that captures the good things about posix but allows all the related ecosystems to move everyone forward toward a better base specification (together rather than just increasing the number of bsd vs gnu special cases that with current plans will just have to be lived with forever)

Browser standards managed to do this in a lot of ways despite far more complex standards, more complex variations in behavior, and much more rapid continue evolution ...

The problem with python's async is asyncio ...

Structured concurrency libraries like anyio or trio are actually pretty nice -- "stacks" and stack traces are good things. Python multi exception concept is weird --- but also I think probably good ish.

It is still a pita to orchestrate around the gil/how terrible python multiprocessing side effects are wherever cpu bound workloads actually exist ...

Hilarious . I was a python fan before I was a reluctant user. It still has the most reliable debugger integration of any mainstream language which is my favorite thing about the language in its current state.

Debugger >> language -- next most popular language manifesto slogan (i hope).

Our $100M Series B 12 months ago

I predict that if they take this same philosophy and use this money to add some new pieces on top where those new pieces are 'open' in the same way as their current hardware stack but which allows them to also run 'gpu bound' workloads well -- then I suspect they will make a ton of money.

What IS the right way to model dates in a pacemaker ...? I hope the answer is "just don't do it" -- but I don't know what reasons there might be for a pacemaker to need to depend on calendar dates in order to best do its job ...

classes are a bad way to model data imo

I wish python had a clean way to define types without defining classes. Think a _good_ mechanism to define the shape of data contained within primitives/builtins containers without classes -- ala json/typescript (ideally extended with ndarray and a sane way to represent time)

Python classes wrapped around the actual "data" are sometimes necessary but generally always bad boilerplate in my experience.

I think the whole concept of source files as unordered blobs on the filesystem is just _wrong_ -- and a serious drag on the ability of a reader to quickly digest a codebase and make inferences about changes in isolation ...

Codebases are _ordered_ constructs -- regardless of the ridiculous broken build system abstractions that do everything possible to obscure this truth ...