I'm building a motion curve editor beyond your wildest fantasies. I've been head down solving new easing equations for the last 13 months. I promise nothing less than a quantum leap in easing technology.

1000% this If you're "one-shotting" animations with Opus 5.5, the default output is slop (impressive slop but still): - Pacing & animations are way too fast - Too many effects (less is more!) - No cohesion (movement in all directions) - No focal point (where to draw attention?) - Generic easing applied everywhere - No consistent choreography - Motion without meaning Good animation explains something. Default animation is just meaningless eye candy.

"A React hook census found 6,900 hooks re-rendering on every keystroke." It's like watching Hoarders: how do people let it get that bad?

“The life you seek is hidden inside the discipline you avoid.” - Epictetus Despite being born into slavery, Epictetus rose to become one of history’s most influential Stoic philosophers. He believed that genuine freedom does not come from having an easier life, but from developing the ability to master yourself. His teachings emphasized a challenging yet powerful principle: while you cannot determine everything that happens around you, you can choose your reactions, guide your decisions, and remain persistent when confronted with adversity. “The life you seek is hidden inside the discipline you avoid.” Although this quotation has no verified connection to Epictetus, its message reflects a central theme of Stoic philosophy. The future you desire may depend on confronting the responsibilities you repeatedly put off, whether that means exercising when you lack motivation, completing difficult tasks, or finally making the uncomfortable choices you have been avoiding.

Solving a Rubik's Cube with graph theory.

#Jev AI is a non-verbal savant. No circuits wasted on social skills. Just 100% focus: melt that Scantron. @typesafeai

This is AIs thermal exhaust port

Just got this incredible news from UCLA Math Circle. Two high school students, Aayush Bathija and Prince Rohatgi, working with postdoc Daniel Soskin through the UCLA Math Circle, have solved a problem that Fields Medalist June Huh had previously worked on without solving. The paper was heavily AI-assisted. Whatever your view on AI in mathematics, enabling high school students to push the frontier of mathematical research is something worth celebrating. arxiv.org/abs/2609.05341

this is the perfect encapsulation of the last 6 months of AI progress:

Mathematicians are unhappy about OpenAI. The gist of their argument is that they form a community that trains young people. When AI started producing breakthroughs on hard mathematical problems, I asked what a very smart 17-year-old would feel. Do you still choose a math major and train yourself to prove difficult results by hand? This crisis has been coming for a long time. When I was a kid, the four-colour theorem was proved by a computer, in 1976. An intense debate followed. Does it count as a proof? I wrote my PhD thesis using symbolic algebra software. To my knowledge, nobody then would publish their scripts. I tried to include mine. I was told it would make me look bad. The letter says: "In recent months, the success of AI in solving major mathematical problems has made headlines even outside mathematical circles. But solving problems is only a tool and proxy for achieving the primary goal of conceptual understanding and insight. Forgetting this in the world of AI may turn the tool against the primary goal. Often these solutions are announced in a rush, leaving no time for a proper writeup, the isolation of new methods and ideas, and citing relevant previous work of others. As in all creative professions, this raises severe attribution and plagiarism questions. We are witnessing a general threat to intellectual work, with misalignment between the outcome of the use of AI and its initial purpose. In many fields and activities, years of training have traditionally served not only to produce a final answer or product, but also to develop understanding and the ability to formulate new questions and ideas." They worry that kids will not choose to become old-school mathematicians. That is a reasonable fear. They do not seem to consider that some kids might still do mathematics, just in a very different way. Doron Zeilberger, in 2009: "Teaching computers how to discover and prove mathematical results is certainly the way to go, and I believe that mathematicians who continue to do pure human, pencil-and-paper, computer-less, research, are wasting their time." sites.math.rutgers.edu/~zeil… The letter implies that people, because of AI, will stop having ideas, or will stop taking the time to understand the issues. If that were true, mathematics would continue only on computers, with no humans interested, or it would stop. Both scenarios assume that people care about mathematics only when they can claim credit. I am not sure why I cannot study a proof generated by AI if I want to. I can give talks about it. What becomes less likely is the reward of having been the one who proved the result. The rest of the letter makes a big deal of credit. What if the AI builds on what it read and does not give proper credit? Where is the evidence that AI is worse than human beings at citing sources? The letter notes that mathematics contributes to society. It never considers that faster progress might increase those contributions. My stance is simple. Mathematicians, software developers, engineers, lawyers, physicians will all learn to work with AI. You cannot put the genie back in the bottle. Only a totalitarian world government could try, and some of us would rather avoid that outcome. Difficult proofs will now be built with AI, just as most code will be written with AI. People who insist on pen and paper should view themselves as artists. Other mathematicians will work with AI. They will have no trouble finding interested kids. They will contribute to society.

I’m making a visual animation editor for Anime.js Here’s a sneak peek from my @threejsconf lightning talk Leave a comment if you’re interested in joining the beta!

Our group discovered that reasoning models produce fractals when asked to solve hard problems. We can use nonlinear dynamics to probe the thinking processes of recurrent depth models on Sudoku, mathematics, and even ARC-AGI (1/N) arxiv.org/abs/2609.04963

If as seems likely most people outsource their writing in future to LLMs it will be a terrible development not because the writing of LLMs is bad (it may improve in future) but because the point of writing is not just to express oneself but to actually discover what it is you really believe by undergoing a meditative process of reflecting and revising your ideas. This is completely different from thinking you know what you want to say at the outset and having a machine instantly produce it for you.

What I spend the most time reviewing or manually working through are my custom DSLs/APIs and data formats. I'm less concerned about the internals of a pure function (which has unit tests or property-based tests) than its interface with the larger system. Functions need to be carved into good shapes for input and output.

Smooth interruptibility improves interactive animations with state transitions. Smooth Level 1: Preserve position while interrupting Smooth Level 2: Preserve velocity Smooth Level 3: Preserve acceleration Level 2 is significantly harder than 1. It causes people to ditch easing functions for springs or other simulations, which have pros and cons. Level 3 is even harder, w/diminishing returns, so it's rarely done for UI. Math term: continuity of C0, C1, C2

So this is how the memes were made WAN 3.0 on the Pika API Club just brought these memes to life And it’s way less expensive than anywhere else 👇🏻

For sure, but baby steps: first auto-normalize text like punctuation in phone numbers, etc. Don't red-error bark at me to make these trivial, pattern-based edits.