nohat

Yep, I need to compare the new models and update everything. Foolish of me to generate ahead at all!

Fair points, thank you for the very thoughtful feedback! "Alexandrian who found area from mere sides" is a bad hint because it is fairly obscure, and really just a history trivia check. And the image is a bit random. You can view the explanation for the hint by clicking the ? button in the upper right corner after a word is completed if you are curious about the models reasoning.

As a bit of an explanation I generated these before Nano banana pro came out, and at the time I made a large comparison grid for various image and text models. For this style qwen image performed very well. LLM wise I started with 5.1 and updated to 5.2. Of course with the rate of model release my choices are pretty much already obsolete... Expense is also a factor for a hobby project, and NB pro is 7.5x more expensive than Qwen image.

Just a python script to render then api call with a prompt to check if the render looks right.

I tried this a few months back with claude 3.5 writing cadquery code in cline, with render photos for feedback. I got it to model a few simple things like terraforming mars city fairly nicely. However it still involved a fair bit of coaching. I wrote a simple script to automate the process more but it went off the rails too often.

I wonder if the models improved image understanding also lead to better spatial understanding.

Yeah, I definitely see using this for literate programming. Not quite sure the best way to organize it. Maybe use a static site compiler to auto host documentation version.

It was a stupid and shameful tweet. The thing that elevates this above a drunk tweet though are the "real life" postcards. Should we ignore the fact that the postcards seem very much a false flag?

It has been interesting seeing the sleuthing on this one. IMHO it is unfortunate to have this happen to a company that has been very pro open source.

The link just changed. Why? The original was the verge article, that was frankly terrible. It really read like the author had a specific goal.

Have you tried using ChatGPT to study? It's pretty incredible for learning, particularly interactive exploration. The point of this plugin is to give ChatGPT access to reliable information to help it be more accurate and informative, as well let it provide real sources so you can verify and continue learning. MIT OpenCourseWare is a great resource (the quality of the teachers is amazing), but it isn't easy to find what you want, and it lacks the interactive component of a real class. I made this to try combining the strengths of both.

This is a shame as bing search api was much better documented, and supported (at least as of a few years ago). Google switched api specs and dropped features at an even faster rate than their consumer facing products.

I feel like this headline is deceptive. This is a Jax reimplementation, and it was released a year ago. It is a cool library though. The basic operation of muzero is very simple, but training it efficiently is tricky.

We can define intelligence in a very real, practical way now. We see and identify intelligence all the time in humans and in animals and in AI. We may not be perfect at identifying it (just like grog might mistake a rising sun for a forest fire), but we don't need a perfect mathematical or philosophical definition that we all agree on to create it. We just need to rub sticks together really hard.

Mog: “What truly is fire? The divine blessing stolen by Prometheus? Concentrated Phlogiston? The element of change? Is it not madness to seek to create something we don’t even have a good definition of?”

Grog: “Grog rubs two sticks together” Lowers voice and looks around furtively “really hard.”