I take some issue with that testing methodology. It seems to me that you're conflating the model's performance with the reliability of whatever provider you're using to run the benchmark.
Many models, especially open weight ones, are served by a variety of providers in their lifetime. Each provider has their own reliability statistics which can vary throughout a model's lifetime, as well as day to day and hour to hour.
Not to mention that there are plenty of gateways that track provider uptime and can intelligently route to the one most likely to complete your request.
I'll piggyback on this to highlight Refactoring UI as well. It's an ebook by Adam and Steve, though I'm not sure if it's technically part of Tailwind Labs or not.
This book taught me so much about modern UI design. If you've ever tried building a component and thought to yourself, "hmm something about this looks off," you might benefit from this book.
These days some of the examples might be a little bit dated (fashions come and go), but the principles it teaches you are rock solid.
I’d argue the goalposts have moved substantially over the past decade. The LLMs we casually use in ChatGPT today would have been described as AGI by many people 15, 10, maybe even 5 years ago.
I tend to agree. Cloudflare and Vercel were able to mitigate in the form of WAF rules, but it's not immediately clear what a user or vendor can do to implement mitigations themselves other than updating their dependencies (quickly!).
IMO the CVE announcement could have been better handled. This was a level 10. If other mitigations can are viable and you know about them, you have a responsibility to disclose them in order to best protect the safety of the billions of users of React applications.
I wonder how many applications are still vulnerable.
FWIW it looks like OpenRouter's two providers for this model (one of whom being Deepseek itself) are only running the model around 28tps at the moment.
After reading the post I kept thinking about two other pieces, and only later realized it was Taylor who had submitted it. His most recent essay [0] actually led me to the Commoncog piece “Are You Playing to Play, or Playing to Win?” [1], and the idea of sub-games felt directly relevant here.
In this case, running a studio without using or promoting AI becomes a kind of sub-game that can be “won” on principle, even if it means losing the actual game that determines whether the business survives. The studio is turning down all AI-related work, and it’s not surprising that the business is now struggling.
I’m not saying the underlying principle is right or wrong, nor do I know the internal dynamics and opinions of their team. But in this case the cost of holding that stance doesn’t fall just on the owner, it also falls on the people who work there.
If they are serious they should realize that "80% accuracy" is almost meaningless for this kind of classifier. They should publish a confusion matrix if they haven't already.
I haven’t tried it myself, but if you’re asking specifically about the human models, the article says they’re not generating raw meshes from scratch. They extract the skeleton, shape, and pose from the input and feed that into their HMR system [0], which is a parametric human model with clean topology.
So the human results should have a clean mesh. But that’s separate from whatever pipeline they use for non-human objects.
Doable for http and https, but if you're running it in a browser environment, you'll eventually run into issues with CORS and other protocols. To get around this you need a proxy server running elsewhere that exposes the lower layers of the network stack.
Very cool! I'm curious as to how it compares with WASIX in terms of both compatibility and performance.
Also tangentially related: I'd love to see a performant build of Node.js compatible with this runtime (or really any flavor of WASM), but I think you'd run into the same issues that I have with WASIX. Namely build headaches, JIT, and wasm(-in-wasm) support. I'd explore it myself but I've already sunk way more time than is reasonable on that endeavor.
The designer obviously knows a thing or two. I enjoyed the fun presentation that others seem to dislike.
Where I ran into trouble was the readability of the annotations on the visuals. The tiny font combined with the low contrast was too much for me. I found myself squinting and trying to get close to my monitor. Eventually I had to move on, even though I was enjoying the content.
I’ve got a random subdomain hosting a little internal tool. About twice a year, Google Safe Browsing decides it’s phishing and flags it. Sometimes they flag the whole domain for good measure.
Search Console always points to my internal login page, which isn’t public and definitely isn’t phishing.
They clear it quickly when I appeal, and since it’s just for me, I’ve mostly stopped worrying about it.
Sometimes I notice myself go a bit too long without a commit and get nervous. Even if I'm in a deep flow state, I'd rather `commit -m "wip"` than have to rely on a system not built for version control.
Many models, especially open weight ones, are served by a variety of providers in their lifetime. Each provider has their own reliability statistics which can vary throughout a model's lifetime, as well as day to day and hour to hour.
Not to mention that there are plenty of gateways that track provider uptime and can intelligently route to the one most likely to complete your request.