zenburnmyface

OpenAI is such a mess atm:

1. They created chat + work split in June / July, now they are combining them back later this year.

2. Their 28-days-of-shipping-or-reset was embarrassing. I think over half were resets.

3. They finally, right at the end, flip-flopped on 100/200/500 plan usage. Also, those names won't scale with inflation.

4. I see _eight_ (8!) models in my codex model selector.

5. _All_ their produce announcements (codex, chat, work, dots, agents) have the same messaging: "extra capabilities designed for long running tasks" - so which do I choose!?

I mean, I know it's a new technology and products are evolving, but...

tip: for suspected permutations, like use a string like "1234567"

Gatekeepers? Someone is pouring something into your ear.

Want to understand this more? Read the triplet of books by Ash and Gross, specially Elliptical Tales

of course you would include bitcoin in the latter, too, right? Right?

This is A+ satire

This is in that direction: https://jannesklaas.github.io/ai/2025/07/20/claude-code-agen...

Check out courses by David Beazley: https://www.dabeaz.com/

Lavingia should be ostracized from tech for this. What an embarrassment.

meh. I feel this is just a linguistic shortcut, similar to how _trained_ biologists can talk about a species or organism evolving some trait. Of course the organism isn't _really_ evolving with any goal in mind, but that's clear to the speaker and audience. Whether or not LLMs understand (very unlikely), it's clear what we mean by an LLM "understanding": has the context + prior training to make reasonable predictions. But no one wants to write that each time.

slop

None of these people have to deal with other people.

you're really showing your hand here...

Oldest commit was from today: https://github.com/sympy/sympy

Where are you getting 14 years from?

I've also taken David's compiler course, and it was excellent. I highly recommend taking any course he offers that interests you.

We are building micro-bioreactors on the Raspberry Pi. Yes, hardware is _hard_ (and fun!)

https://pioreactor.com/

Who said anything about low-income housing?

It’s call FBS, and it can be grown in a lab, too (if it’s even required…). See companies like Future Fields.

My email is already too full -- how about a Twitter feed? My friend did this one:

https://twitter.com/mathisonian/status/399348431291817985

A few reasons:

1. I lived in Toronto when I started writing, plus the graphic designer currently lives there.

2. It's nice to see a Canadian connection ;)

3. The results of Bayesian inference sorta look like a skyline, see http://i.imgur.com/bF4YrBQ.png

Yes, there are plans. There is currently a PDF version, floating somewhere in the Github repo. This version is out-of-date, and is only a draft. A more physical book may be coming mid-fall though.

Short answer: Yes.

Long answer: Here's an analogy. Computers have been abstracted enough that I have no idea how a compiler works, what assembly is, or what the difference between a Flash Drive and a SSD is, but I can still code as I please. Is this practice wrong? No, and I don't need to know (nor do I want to). This book tries to abstract inference (read: programming), from mathematics (read: compilers, assembly etc.).

Hmmm, is this still happening to you? Is it happening to anyone else?

Hi, Author here. I don't have any plans to write that blog post, but I'll can provide some resources:

1. http://timsalimans.com/observing-dark-worlds/ 2. http://timsalimans.com/winning-the-dont-overfit-competition/

You mention: "trained in mathematical Bayesian Inference in an Econometrics class but I never did anything practical with it" . This book tries to bridge that, from theory to practice. The examples I provide tend to be very practical.

I'm glad you enjoyed it =)

And please, I'm curious about a response to Don_Draper's question: have you been able to apply either Bayesian inference, or Bayesian thinking?

it's back up now I believe.

haha ironically left-arrow right-arrow replace space-bar scroll.

I am the author. Thanks, I appreciate that!

If you are interested in the practical practice of Bayesian methods (and you love Python), check out our open-source project/book Bayesian Methods for Hackers:

https://github.com/CamDavidsonPilon/Probabilistic-Programmin...

We aim to empower the non-mathematician with really cool tools and methods to solve otherwise very difficult problems. Plus it's all opensource, and every plot/diagram is reproducible and extendable.