What we love is good for us, sometimes
Plus, links and strange finds from the World Wide Web
What we love is good for us
"But that said, he admitted smoking played a huge part in his life. “I don’t regret it. It was important to me. I wish what every addict wishes for: that what we love is good for us.”
He went on: “A big important part of my life was smoking. I loved the smell of tobacco, the taste of tobacco. I loved lighting cigarettes. It was part of being a painter and a filmmaker for me.”
Wastebook
“Reams of founderspeak floated up into the warm breeze.” Tyler Cowen profile.
And: “‘I’m not very interested in the meaning of life, but I’m very interested in collecting information on what other people think is the meaning of life.’ And it’s not entirely a joke.”
“I feel that writing about the topic will make me stupider.” Also Tyler.
Gruber on Skype’s EoL: “I don’t think it’s an exaggeration to say that if not for Skype, podcasting would’ve been set back several years.”
“My toaster has developed self-awareness, which is concerning because its only purpose is to burn things.” AI IoT FUD.
“Vibe working is using AI to turn fuzzy thoughts into structured outputs through iteration.” Azeem Azhar.
“Stove touching.” Move fast and touch things.
“a beautifully crafted digital fortress.” Ian.
”far left government computer office." DOGE-slang.
“Who’s gonna help us? …nobody’s coming.” Noah.
Relative to your interests
macOS Tips & Tricks - lots of keyboard shortcuts. See also their iOS tips, and MacOS command line tips.
Agentic definition from Azeem Azhar and Nathan Warren - Good simple AI vs. agentic AI framing: “Some view AI as a tool – a system that passively performs functions, while others see it as an agent – a system that actively pursues objectives, makes independent decisions and may develop instrumental goals such as self-preservation.”
ServiceNow’s newest AI agents bring intelligent automation to telecommunications firms - ServiceNow’s AI agents analyze network data to diagnose and resolve issues, predict disruptions, and provide real-time explanations for unusual usage patterns, improving customer service and reducing complaints.
How AI ‘Reasoning’ Models Will Change Companies and the Economy - Lots of good thinking here, not least of which is a very delightful writing style. There’s about five quips in there that are fun. // Also notice that the benefits are accruing the individual here, the enterprises have yet to figure it out.
AI’s productivity paradox: how it might unfold more slowly than we think - The case that productivity effects of AI in the macro economy will be slow. Micro-economy (individuals) still looks good.
State of Java Survey Confirms Majority of Enterprise Apps Are Built on Java Performance, Superior Java Support - ”Typically, when the topic of developing AI or ML functionality arises, people think of Python. Perhaps surprisingly, the survey found that Java was used more often than either Python or other languages. In fact, 50% of organizations use Java to code AI functionality.”
Logoff
I’m not contributing to the AI slop problem. I’ve been posting some of the explainer queries I’ve had with ChatGPT (see the AskTheRobot category). I both like them, like easy content, and am curious if they draw incoming traffic. // It’s getting warm and sunny again in the Netherlands. I hope that means I’ll get my ass on the bike and get back to fiets-flâneuring.