Vibe-Biology
AI *is* a Vibe ⓧ AI and Scientific Revolutions ⓧ The Biology of AI
👋 On time for your weekend: a round-up of this week’s remarkable stories at the intersection of technology, business, design, and culture. Three to read and three to listen to—no fluff, just stuff ⚡
⏯️ Thoughtforms will take a break next week; the next edition drops Friday, April 28.
📚 Reading
The AI is a Vibe: A Short Manifesto for the AI Age:
We need to cultivate what we might call "collaborative discernment"—the ability to work with AI while maintaining our own judgment. This isn't about resistance or acceptance; it's about developing a new kind of dance. This means using AI's performances as inputs to our thinking rather than replacements for it. It means learning to prompt not just for content but for perspective, to use AI not as an oracle but as a thinking partner whose very limitations can spark our own insight.
Nate Jones | 14 minutes
AI and the Structure of Scientific Revolutions:
We need AI that can do both “normal science” and the science that creates new paradigms. We already have the former, or at least, we’re close. But what might that other kind of AI look like? That’s where it gets challenging—not just because we don’t know how to build it but because that AI might require its own new paradigm. It would behave differently from anything we have now.
Mike Loukides—O’Reilly Radar | 6 minutes
On the Biology of a Large Language Model:
The challenges we face in understanding language models resemble those faced by biologists […] While the basic principles of evolution are straightforward, the biological mechanisms it produces are spectacularly intricate. Likewise, while language models are generated by simple, human-designed training algorithms, the mechanisms born of these algorithms appear to be quite complex.
Transformer Circuits Thread—Anthropic | ♾️ minutes1
🎧 Listening
Breaking through discomfort:
Every time we achieve some version of success, we see a version of ourselves we never thought possible. And inside of that version, we have an increased hunger, a faster pace, bigger goals […] we also find stress and uncertainty and doubt and exhaustion and envy and burnout and all of these emotions. And so anybody who's telling you that they are super successful and super happy, well, then they're just at the end of their growth. And why would you ever want to be there?
Laura Gassner Otting—Lancefield on the Line | 46 minutes
A better way to plan, build, and ship products:
We are not going to start something unless we can see the end from the beginning. We're not going to take a big concept and then say what's the estimate for this thing. We're going to go the other way around and we're going to say what is the maximum amount of time we're willing to go before we actually finish something? How do we come up with a idea that's going to work in the amount of time that the business is interested in spending?
Ryan Singer—Lenny’s Podcast | 105 minutes
The Signal Scandal & DOGE Drama!
Everybody thinks it's these coders and they're doing efficiency stuff. But it's all lawyers who used to work for Ron DeSantis who are executing incredibly well on this ideological project of tearing out all the liberal ideology. And these idiots in Silicon Valley are giving incredible cover to them making all this noise. But nobody believes in that.
Ben Smith—More or Less | 59 minutes
💎 Timeless
1️⃣ year ago—The Real Crisis in Humanities Isn't Happening at College
2️⃣ years ago—Malleable software in the age of LLMs
3️⃣ years ago—Leadership In An Ecosystem Age: Secrets For Success
A bit cheeky to list the reading time as infinite. It is a long read, for sure, and one you’re best advised to use as a walking buffet of sorts. Typically, we don’t run this type of content in this fine publication, but it gets to something significant and worth sharing despite its impenetrability.
Transformer-based language models may be trained to predict the next word, one word at a time, but what comes out of that training and into the world is so much more than that—not unlike how ‘life’ is an emergent phenomenon that comes into being among networks of autocatalytic and self-reproducing cells.
It’s intelligent but not artificial; it’s synthetic, different, and sometimes genuinely alien. Thinking of it as a machine, even a thinking machine, seems like missing the forest for the trees. Phrasing as a vibe, a performance, or a symbiosis seems more correct directionally but also shows how I struggle to find the right words here. Please reach out if you want to help out here… 🙏✉️