One of the most compelling ideas I encountered this year was the ancient Greek perception of time in two distinct forms: ‘Kronos’ and ‘Kairos’. Their contrast helped me understand a feeling I’ve carried for years but never quite named: time anxiety, the persistent fear that I’m not making the most of my time. In English, we have only one word for time, but the Greeks were more precise. Kronos refers to chronological, measurable time. Think of it as the hours, minutes, and seconds that structure our schedules and calendars. It is the version of time that moves in a straight line, divided into boxes we often feel pressured to fill with as many tasks, milestones, and achievements as possible. Kairos, on the other hand, is almost its opposite. It describes the quality of time rather than its quantity: the elastic, subjective experience of moments that sometimes rush by and sometimes stretch out endlessly. Kairos invites depth instead of speed. When we inhabit Kairos, we stop tallying productivity and instead ask ourselves whether we feel present, engaged, and alive. And in doing so, time anxiety loosens its grip. The distinction matters because we live in a profoundly Kronos-driven society. Our calendars look like pieces of lego. Infact, there is an unspoken Kronos timeline for our lives too (when we’re expected to buy a house, get married, have children and so on). Falling “off-schedule” often carries a sense of shame, as if failing to fill the boxes on time means failing overall. Kronos makes us efficient, but it also make us robotic. I realized that our mental well-being tends to flourish in Kairos. Organic, immersive experiences such as creativity, connection, presence don’t obey clocks. They can’t be forced into evenly sized blocks. And while it might be impossible to live in Kairos constantly, the challenge is not to reject Kronos but to carve out moments of Kairos within it. The easiest way I have implemented this in my life is asking myself this question - “What is a non-quantifiable way of measuring success today?” My answers to this question range from learning a new song on guitar, going for a long walk without any gadget, cooking a new meal, or just yapping with my friends for 2 hours. As a result, I feel the best way to optimize my time is to find ways to build Kairos into my life deliberately: choosing depth over speed, quality over quantity, and aliveness over mere productivity. Living between Kronos and Kairos is not about choosing one over the other but about learning to move intentionally between them, measuring our days not just by what we accomplish, but by how we live them.

GLM-5.2 is Fully Open, Frontier Intelligence Belongs to Everyone Today, the sudden restriction of certain frontier models is deeply regrettable. At a time when access to frontier models is abruptly cut off for non-technical reasons, we are even more convinced of one thing: science should be global. The path to AGI (Artificial General Intelligence) must never be enclosed by high walls. We have always believed that AGI should be the cornerstone for all of humanity to collaboratively explore the boundaries of intelligence and solve complex challenges, rather than a privilege monopolized by a few rules and subject to revocation at any moment. In the face of external blockades and restrictions, our attitude is one of radical openness. Frontier intelligence must remain open-source, accessible, and buildable, serving every dedicated developer. GLM-5.2 is Zhipu's most capable open-source model to date. It not only supports a truly usable 1M context window but also maintains a continuous lead in the independent completion of long-horizon tasks, providing solid foundational support for building complex agent applications. It also continues to be our main engine for creating the strongest domestic coding model. Tonight at 5:21—at this special moment—GLM-5.2 will officially be available to all GLM Coding Plan users (including Lite / Pro / Max). The API will also go live next week. A step closer to frontier intelligence for everyone. The future of AI is open, and it is for the people. ModelKey: GLM-5.2

This should be a big wake up call for the government.

In light of today’s SpaceX IPO, a story from inside Jane Street on the day of the 2012 Facebook IPO:

Nobody wants to admit it but "vibecoding" works until your app has actual users. Then you discover what senior engineers have been getting paid for.

A lot of people seem angry that Elon is now a trillionaire, so it’s worth reminding them that he didn’t achieve this by making anyone else poorer. Wealth isn't zero-sum. Paul Graham explained it well: paulgraham.com/wealth.html

What's the better business model for an AI lab, subscription or API? (1/4)🧵

Best use case I’ve seen for Fable so far. Hitting the real pain points

Anthropic's Web crawler has a familiar ring to it

Always back to the basics: LatentMoE was probably inspired by MLA, which was inspired by LoRA, which was inspired by SVD, which was inspired by eigendecomposition.

Introducing text-to-lottie: an open source skill and harness for generating production ready Lottie animations with codex/claude code. $ npx skills add diffusionstudio/lottie Prompts guide and repo in the comments.

these outages are getting a bit out of hand @AnthropicAI

You know the product launch is sick when most people are digging the backing audio.

🏃‍♂️ I've gamified my own run so I can race my own ghost with the Meta Ray-Ban Display. I built a web app for the glasses, loaded a previous GPX from Strava, and dropped game mechanics on top. Pick up coins when you keep pace, sprint zones reward extra points if you push, and a mini leaderboard on the lens shows how you're tracking against your past self in real time. Best part: it actually works. Seeing your ghost 20 m ahead is a way stronger nudge than any number on a watch. 😅

why does gpt write like a threadboi??

The problem with intellectuals is that they’re motivated to say smart things instead of true things.

You can usually tell a lot about someone based on the battery percentage at which they start freaking out to charge their phone.

I'm suspicious of that that whole story about Uber blowing their AI budget and being disappointed in the results - I dug into it and it appears to have been built on very shaky foundations

i mounted a tiny microphone on my apartment balcony to listen for any birds passing by and built a site to collage them as they're heard

An undervalued reason to be optimistic about gen-AI investment is that even if the tech is overbuilt and the hype is a bubble (which I doubt), most of the stack has big uses outside gen-AI. Data centers = Cloud computing Transformers = Data compression, sequencing (e.g. genomics) GPUs = graphics, imaging, modelling, crypto Vector databases = Indexing and archiving knowledge Power, networking = wide uses Water = drinking