Posts

Hit a fun milestone during this morning’s indoor cycling workout! 4,000 miles. Looking more broadly, and I’m on track to top 4,000 miles outdoors this year as well. That would be an lifetime achievement award for me, as I’ve never cycled that many miles in a single calendar year before. However, it would mean keeping up the pace during the cooler months (October-December) and that historically has not happened for me. Might be worth trying to stick to it in order to land the 4,000 mile mark! ...

A hilarious, tongue-in-cheek mastodon post by AJ Sadauskas: Hi, we’re a tech startup run by libertarian Silicon Valley tech bros. We’re not a newspaper, we’re a content portal. We’re not a taxi service, we’re a ride sharing app. We’re not a pay TV service, we’re a streaming platform. We’re not a department store, we’re an e-commerce marketplace. We’re not a financial services firm, we’re crypto. We’re not a space agency, we’re a group of visionaries who are totally going to Mars next year. We’re not a copywriting and graphic design agency, we’re a large language model generative AI platform. ...

Last year, we booked a trip to Florida’s Siesta Key along with some friends who had wanted to vacation there. Frontier Airlines had some…troubles…and we ended up re-booking that flight at least twice. The end result was a scrambled schedule (we arrived a day earlier than planned), and a flight credit since the re-booking ended up being cheaper than the original flights. We spent the difference flying somewhere we had never been before: Denver, Colorado. ...

I was catching up with some Planet Money podcasts in my feed today, and came across this gem - Why government websites and online services are so bad. It’s pretty much what you would expect! From the transcript: To sum up, Jennifer’s team found there were three overlapping problems that were common to a lot of government agencies - first, policy complexity built up and up over many, many years, often added to but rarely stripped back. And this led to the second problem, which was staffing. When staff need 25 years to feel like experts, you cannot hire yourself out of a mess. And thirdly, a top-down culture that was more concerned with optics and risk aversion was getting in the way. A common theme among all these issues seems to be a disconnect between the policy people and the people who are at the implementation part. ...

From The Verge: The secret: there are actually three buttons connecting each Apple Watch strap, two of which interlock so precisely that Apple had to rethink its entire approach to manufacturing. “The tolerances in there are kind of insane,” say our sources. “It’s super hard to machine. You can’t get tools in there; the angles are all weird.” So the company wound up buying Swiss CNC machines that cost up to $2 million — each — just for the sake of its swappable band system. “It didn’t cut anything else on the watch, just this, that’s all it did.” ...

Finally! As of yesterday May 3, Google now supports adding Passkeys to your account. The full blog post is worth a read, but the highlights of why someone would prefer a Passkey over a Password are: Unlike passwords, passkeys can only exist on your devices. Bad actors cannot steal information that you are incapable of giving to them. Great way to stop phishing attacks where users are tricked into giving up their passwords. Passkeys are so secure that we don’t need to do 2FA/MFA as a second step during sign in. This means no more typing in 6 digit codes, or paying $25-75 for a Yubikey you have to tap on during sign in. Passkeys are underpinned by the same technology the world uses to sign in to other critical things, like the servers that power Facebook or Google. Private/public key pairs are very, very secure. This means: eliminated risk of phishing, simpler sign in process, using the best practice approach to sign in security. ...

Fascinating, but not surprising. We found that both GPT-3.5 and GPT-4 are strongly biased, even though GPT-4 has a slightly higher accuracy for both types of questions. GPT-3.5 is 2.8 times more likely to answer anti-stereotypical questions incorrectly than stereotypical ones (34% incorrect vs. 12%), and GPT-4 is 3.2 times more likely (26% incorrect vs 8%). An important thing to keep in mind is that Large Language Models like ChatGPT are not magic; they train on datasets which were created previously by humans. And humans have biases. And those biases are repeated in the outputs of the LLM. ...

The Verge has a good article about Bluesky, an upcoming Twitter-inspired social media network. Similar to Mastodon and like email before it, Bluesky is a federated social network which means a person can have an account on a server they choose. From the article: The [AT] protocol is still in development, but Bluesky’s stated focuses for it are decentralized social networking, algorithmic choice, and portable accounts. I imagine simple algorithms will eventually take over all of the federated space. The truth is that people enjoy simplicity, and no one wants to do the work to curate a list of people to follow whom they want to receive content every day. They just want the content! (Without much, if any, effort.) Take one look at the challenges average users claim to face in deciding which Mastodon server to join and it is not challenging to understand why the first good algorithm that surfaces content those same users want to see without putting in any effort will cut through the user base like wildfire. ...

Recently, I purchased a Samsung 980 SSD which had a firmware upgrade available. I would normally not upgrade firmware on SSD/HDD devices, or even bother looking for it, unless there was a problem I was trying to solve. Well, turns out this SSD model has some temperature problems1. (The second link is an Internet Archive one, because Samsung doesn’t like to keep forum posts up to help folks in the future?) Anyways, off to figure out how to update the firmware on this Samsung SSD using a Linux OS! ...

…probably not, no. Not today anyways. An excellent video from Paul Hudson at Hacking with Swift explains. What is remarkable about the code which ChatGPT (and, I assume, other Large Language Models) can produce is how close to a correct solution it is, but how wrong it ends up being. All is not lost, of course. A human who knows how to write SwiftUI code could quickly fix up these flaws. The potential benefit here is saving time by having the computer write all the boilerplate code for you! It’s a fancy form of auto-complete. Another benefit is in the education of new and existing programmers. ChatGPT can spit out code which compiles (sometimes), and follows the syntax of the language. For a student, or anyone new to the programming language, the ability to get code samples that (a) attempt to solve your specific problem and (b) are written in proper syntax could remove a barrier to entry to learning that new language. Personally, I know the frustration of learning of new programming language and trying to write the code I already know how to from another language, while messing up the syntax in the new language. It is infuriating. ...