RE: https://techhub.social/@jimluther/116586946206062489

Graham Platner is yet another example of someone with no background serving the public going for a high level office.

At the beginning of 45s term, you had to type “Idioc” to get that result.

On this holiday in the United States, I’ll note that I only have to type “Idi” into most major search engines (Google, DuckDuckGo, Bing, and probably others) for the autocomplete match to be “Idiocracy”

Because some watching my timeline have not seen this https://youtu.be/KMnLTTA-Q-I

Apple’s Developer Group was completely in charge of the WWDC in the early years before it became a lot more of a marketing event, and in 1991, I was representing DTS on the Agenda Team. The Agenda Team came up with a snarky t-shirt - one of my favorites. The 1991 WWDC logo and Agenda Team are on the back of the shirt.

Happy 37th Anniversary WWDC! (for those who celebrate). I was in the Apple II Developer Technical Support group at that time, and got a t-shirt 😄

Check out this podcast about Atlantic Records and the producers, engineers, songwriters, etc. who worked there. https://offtherecordonthecharts.podbean.com

The hosts are the children of 3 of Atlantic’s most important producers from the late 1940s through the 1970s.

The first full episode is an interview with Jerry Wexler’s son.

The second episode is with Mike Stoller (of Leiber and Stoller).

Type in your zip code and find out the percentage of your neighbors who have been vaccinated against #measles.

For me, it’s a fairly low 70%-79% both zip and county. My daughter has the same for her zip, but only 60-69% county.

https://abcnews.go.com/Health/new-map-shows-spot-measles-risk-level-zip/story?id=129179712&fbclid=IwY2xjawPefFpleHRuA2FlbQIxMABicmlkETE4Q1JtNHFaWXAwdVVUUHhtc3J0YwZhcHBfaWQQMjIyMDM5MTc4ODIwMDg5MgABHlJplYCwRYZaiCW1YAvvlY-e3ahoU029iBXahQyplRHVYn5kIy-3bViBb1pR_aem_182eP5rlml5LQD-QuTgQ2A

The Washington State Department of Health (DOH) reaffirms that vaccines are a proven, essential tool for protecting people’s health. We join health agencies and associations across the country, including the American Academy of Pediatrics and the Autism Science Foundation, in confirming that there is no credible scientific evidence linking #vaccines to #autism.

https://doh.wa.gov/newsroom/washington-state-department-health-statement-vaccine-safety-and-autism-claims

Here at Indivisible, we don’t let leaders who stand up to fascism do so alone. So we’re putting out the call to this movement today: If you’ve got a few bucks to spare, please chip in to support Rep. McIver’s legal defense. https://secure.actblue.com/donate/lm-july-2025-indictment

https://www.techdirt.com/2025/10/08/america-is-drowning-in-scam-calls-and-texts-and-donald-trump-is-making-it-worse/

Help my friend Becky fight her recent cancer diagnosis. Like many, I played games Becky helped create on the Apple II/IIgs, Macintosh, and other personal computing platforms.
https://mastodon.gamedev.place/@burgerbecky/115316833728680548

I think this needs to be repeated, since I tend to be quite negative about all of the 'AI' hype:

I am not opposed to machine learning. I used machine learning in my PhD and it was great. I built a system for predicting the next elements you'd want to fetch from disk or a remote server that didn't require knowledge of the algorithm that you were using for traversal and would learn patterns. This performed as well as a prefetcher that did have detailed knowledge of the algorithm that defined the access path. Modern branch predictors use neural networks. Machine learning is amazing if:

• The problem is too hard to write a rule-based system for or the requirements change sufficiently quickly that it isn't worth writing such a thing and,
• The value of a correct answer is much higher than the cost of an incorrect answer.

The second of these is really important. Most machine-learning systems will have errors (the exceptions are those where ML is really used for compression[1]). For prefetching, branch prediction, and so on, the cost of a wrong answer is very low, you just do a small amount of wasted work, but the benefit of a correct answer is huge: you don't sit idle for a long period. These are basically perfect use cases.

Similarly, face detection in a camera is great. If you can find faces and adjust the focal depth automatically to keep them in focus, you improve photos, and if you do it wrong then the person can tap on the bit of the photo they want to be in focus to adjust it, so even if you're right only 50% of the time, you're better than the baseline of right 0% of the time.

In some cases, you can bias the results. Maybe a false positive is very bad, but a false negative is fine. Spam filters (which have used machine learning for decades) fit here. Marking a real message as spam can be problematic because the recipient may miss something important, letting the occasional spam message through wastes a few seconds. Blocking a hundred spam messages a day is a huge productivity win. You can tune the probabilities to hit this kind of threshold. And you can't easily write a rule-based algorithm for spotting spam because spammers will adapt their behaviour.

Translating a menu is probably fine, the worst that can happen is that you get to eat something unexpected. Unless you have a specific food allergy, in which case you might die from a translation error.

And that's where I start to get really annoyed by a lot of the LLM hype. It's pushing machine-learning approaches into places where there are significant harms for sometimes giving the wrong answer. And it's doing so while trying to outsource the liability to the customers who are using these machines in ways in which they are advertised as working. It's great for translation! Unless a mistranslated word could kill a business deal or start a war. It's great for summarisation! Unless missing a key point could cost you a load of money. It's great for writing code! Unless a security vulnerability would cost you lost revenue or a copyright infringement lawsuit from having accidentally put something from the training set directly in your codebase in contravention of its license would kill your business. And so on. Lots of risks that are outsourced and liabilities that are passed directly to the user.

And that's ignoring all of the societal harms.

[1] My favourite of these is actually very old. The hyphenation algorithm in TeX trains short Markov chains on a corpus of words with ground truth for correct hyphenation. The result is a Markov chain that is correct on most words in the corpus and is much smaller than the corpus. The next step uses it to predict the correct breaking points in all of the words in the corpus and records the outliers. This gives you a generic algorithm that works across a load of languages and is guaranteed to be correct for all words in the training corpus and is mostly correct for others. English and American have completely different hyphenation rules for mostly the same set of words, and both end up with around 70 outliers that need to be in the special-case list in this approach. Writing a rule-based system for American is moderately easy, but for English is very hard. American breaks on syllable boundaries, which are fairly well defined, but English breaks on root words and some of those depend on which language we stole the word from.

How close we are to repeating history. https://www.foreignaffairs.com/germany/warnings-weimar

Thinking…

You can't outsource to Claude Code the part where you understand "the affair of the world" that your program is intended to act upon. Claude Code might help you with specific boring parts of the codegen (the way an IDE helped generate code back in the very bad days of very bad Java) but it can't help you with the theory of the program part.

Or with understanding who you're building the thing for.
And what it's supposed to do for them.
And what success looks like.
And what a good solution feels like to use.
Or what good is.

Talk > Think > Type

in that order of importance and time spent. Claude Code helps with “type”. It helps _a lot_ with “type” if you know how to make it help. I think it's no accident that the most experienced programmers around me have figured out how to wrangle the most out of Claude, and it's ALL in the clear instructions. The most experienced people have figured out how to do that better after years of pain.

So congrats, you now have a lot of help with the easiest part of the thing, the typing. You don't get a free pass out of talking to other people about what to do, or thinking about the best way to do it.

In conclusion, your job is safe, but Florida is in a *lot* of trouble.

ETA: Companies who lay off people thinking anything different are also in a lot of trouble. Executives are such lemmings. This is an insult to lemmings.

https://www.npr.org/2025/08/25/nx-s1-5517335/trump-federal-reserve-governor-lisa-cook

Donald J. Trump looked in a mirror today and said, "In light of your deceitful and potentially criminal conduct in a financial matter, they cannot and I do not have such confidence in your integrity."

Refreshing to hear of a boss not being a lemming
https://www.theregister.com/2025/08/21/aws_ceo_entry_level_jobs_opinion/

Found it…

https://static1.srcdn.com/wordpress/wp-content/uploads/2024/11/hunting-buffalo-v0-q7yu3bhvcweb1.jpg

Gary Larson predicted this in The Far Side years ago. https://www.npr.org/2025/08/09/g-s1-81907/texas-big-game-hunter-killed-african-buffalo