Recent submissions

Comment · 1 month ago
Comment · 1 month ago
Moved on to PopOS long ago, and am loving it, especially with the COSMIC desktop now. I just feel so much less worried. Today’s LLMs with their agent harnesses take the past hassle of configuring and maintaining your Linux desktop completely off the table. No more hour long digging and research after an update, just let your AI keep your machine in shape. No proprietary software spying on you. Problem solved :)
Comment · 4 months ago
Update: on LinkedIn the Faros team replied to me and stated that they see both usage and issues increasing over time.
Comment · 4 months ago
2y of data. They should address that confounder and demonstrate the results are stable even if you stratify over time. 2026 models are very different from 2024 ones, after all.
Comment · 1 year ago
I really liked the main question. But I’m more interested in the structure how we journal, not if you use Logseq, OrgMode, paperback, etc.

For example, I try to journal by treating my work as “experiments” and tie those in turn to goals and challenges. And my experiments consist of a plan, prediction, the actual data, and the evaluation (of the data against the prediction). Finally, I constantly track the current state relevant towards the goal. If that sounds familiar to the Toyota Kata, that is because it is. And it should sound familiar to anyone trying to apply the scientific method.

I’d be curious to learn HOW others journal?

Comment · 1 year ago
Thanks for the warning! From the git docs:

> Set it to refs/notes/commits to enable rewriting for the default commit notes.

Why wouldn’t that at least be the default? Why is rewriting off by default in the first place?

Comment · 1 year ago
How does that compare to Claude Code? How protected are you when using CC?
Comment · 1 year ago
For Mixture of Expert models (like GPTs are), they can produce different results for an input sequence if that sequence is retried together with a different set of sequences in its inference batch, because of the model (“expert”) routing depends on the batch, not the single sequence: https://152334h.github.io/blog/non-determinism-in-gpt-4/

And in general, binary floating point arithmetic cannot guarantee associativity - i.e. `(a + b) + c` might not be the same as `a + (b + c)`. That in turn can lead to the model picking another token in rare cases (and it’s auto-regressive consequences, that the entire remainder of the generated sequence might differ): https://www.ingonyama.com/blog/solving-reproducibility-chall...

Edit: Of course, my answer assumes you are asking about the case when the model lets you set its token generation temperature (stochasticity) to exactly zero. With default parameter settings, all LLMs I know of randomly pick among the best tokens.

Comment · 2 years ago
To me it implicitly means: “I am selling you my distilled copy of the book at nearly the price of the book. That lets me recoup my investment, and after a few days I will take it offline, so I don’t get a law suit from O’Reilley for copyright infringement.”
Comment · 2 years ago
Oh, wow, scummy to scammy, indeed! It’s all in the fine print… I didn’t bother reading this appendix on the first read of the blog post.

Disclaimer: I do really enjoy this book, as it reminds my of uncle Bob’s Clean Code, but a short version, and with the focus on what to do after writing code, when you need to change it or want to understand it better.

Yes, it is structured very much like a collection of blog posts. Which is great for me, as I typically work on learning one “tidying” a day or less. So I am not yet done with the book, end-to-end.

Comment · 2 years ago
That’s an interesting viewpoint, even surprising to me. Can you be more concrete about what you think is wrong with the agile software development movement Kent Beck co-founded, and how it destroys developers?
Comment · 2 years ago
I agree on principal, but believe it is more nuanced and hybrid can work if you implement it uniformly across the company. For example, I’ve seen places where everyone can WFH Tue & Thu or Mon, Wed, Fri where hybrid have a quite smooth collaboration culture. But if it is “random”, every day ends up being WFH - that’s in effect just the same as fully remote, and you need to act accordingly. And if you work in a global company with globally distributed teams, the company already is de facto fully remote, and the picture becomes even more nuanced.
Comment · 2 years ago
Comment · 2 years ago
Comment · 2 years ago
Here’s another example: Apple Arcade decided to discontinue my kids’ favorite local multiplayer game (Marble Knights). Apple erased the game from my devices and there is no way to get this game at all now, at least as far as I know. With the pending increase in Arcade’s monthly costs, that was the last straw for me to say goodbye to this Apple “offering”.

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