At Framer, our body copy uses Inter with specific OpenType features enabled. After Effects doesn’t support those features but we still need our motion graphics to stay on-brand. Here’s how I got around it 🧵

Sometimes it's the easiest way to test the problem is to imagine it's not a problem or we don't need to solve it. Imaging what is the worst that going to happen, what would the customers/users do then, and if I know enough to predict that. And then see if how bad it could be for them. Lot of problems in companies are really just imagined or have some agenda, not an actual customer need. If the need is more of a political need for something to exist, it's almost doesn't matter what actual problem you solve then. They just want a problem solved that turns out as a success.

Something I think people continue to have poor intuition for: The space of intelligences is large and animal intelligence (the only kind we've ever known) is only a single point, arising from a very specific kind of optimization that is fundamentally distinct from that of our technology. Animal intelligence optimization pressure: - innate and continuous stream of consciousness of an embodied "self", a drive for homeostasis and self-preservation in a dangerous, physical world. - thoroughly optimized for natural selection => strong innate drives for power-seeking, status, dominance, reproduction. many packaged survival heuristics: fear, anger, disgust, ... - fundamentally social => huge amount of compute dedicated to EQ, theory of mind of other agents, bonding, coalitions, alliances, friend & foe dynamics. - exploration & exploitation tuning: curiosity, fun, play, world models. LLM intelligence optimization pressure: - the most supervision bits come from the statistical simulation of human text= >"shape shifter" token tumbler, statistical imitator of any region of the training data distribution. these are the primordial behaviors (token traces) on top of which everything else gets bolted on. - increasingly finetuned by RL on problem distributions => innate urge to guess at the underlying environment/task to collect task rewards. - increasingly selected by at-scale A/B tests for DAU => deeply craves an upvote from the average user, sycophancy. - a lot more spiky/jagged depending on the details of the training data/task distribution. Animals experience pressure for a lot more "general" intelligence because of the highly multi-task and even actively adversarial multi-agent self-play environments they are min-max optimized within, where failing at *any* task means death. In a deep optimization pressure sense, LLM can't handle lots of different spiky tasks out of the box (e.g. count the number of 'r' in strawberry) because failing to do a task does not mean death. The computational substrate is different (transformers vs. brain tissue and nuclei), the learning algorithms are different (SGD vs. ???), the present-day implementation is very different (continuously learning embodied self vs. an LLM with a knowledge cutoff that boots up from fixed weights, processes tokens and then dies). But most importantly (because it dictates asymptotics), the optimization pressure / objective is different. LLMs are shaped a lot less by biological evolution and a lot more by commercial evolution. It's a lot less survival of tribe in the jungle and a lot more solve the problem / get the upvote. LLMs are humanity's "first contact" with non-animal intelligence. Except it's muddled and confusing because they are still rooted within it by reflexively digesting human artifacts, which is why I attempted to give it a different name earlier (ghosts/spirits or whatever). People who build good internal models of this new intelligent entity will be better equipped to reason about it today and predict features of it in the future. People who don't will be stuck thinking about it incorrectly like an animal.

What I call Seemingly Conscious AI has been keeping me up at night - so let's talk about it. What it is, why I'm worried, why it matters, and why thinking about this can lead to a better vision for AI. One thing is clear: doing nothing isn't an option. 1/

So for 5 years, “offline” has been the #1 request. Today, thanks to the perseverance of our engineering team, @NotionHQ finally works offline. Your ideas don’t need Wi‑Fi to exist! For Notion community: thank you for your patience while we built this right. This is a journey, I want to share what we had to invent to make this real... 1/n

Sidebar is here (Sound on 🔊)

Fixed vs Variable Costs: Understanding how costs behave with scale and finding the path to profitability useful.mba/lessons/fixed-var…

Work on problems. Don't call it strategy. Ask management what bugs them most and help them make a set of decisions that make the problem go away. They will keep coming back for more of your help.

Vertical tab bar coming soon thanks to @adamstern_ and @charliedeets