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timdumol

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I've tried using Jules for a side project, and the code quality it emits is much worse than GH Copilot (using Claude Sonnet), Gemini CLI, and Claude Code (which is odd, since it should have the same model as Gemini CLi). It also had a tendency to get confused in a monorepo -- it would keep trying to `cd backend && $DO_STUFF` even when it was already in backend, and iterate by trying to change `$DO_STUFF` rather than figure out that it's already in the backend directory.

3 bedroom flat. I use Ubiquiti equipment since sourcing Ubiquiti is much easier than Mikrotik here in the Philippines, and I've had bad experience with TP-Link, DLink, etc. randomly requiring restarts or outright failing after a few years.

* Unifi Security Gateway Pro (for the 2 WAN ports with failover)

* Unifi US-8-Lite-PoE

* Unifi AP-AC-Pro meshed to a:

* Unifi AP-AC-M

Freecad and openscad are basically your only choices for FOSS CAD work Freecad has pretty bad UX compared to Onshape and Fusion 360 (have to keep switching between lots of modes rather than a single unified UI), while openscad is more of a CAD DSL (that IIRC doesn't actually model solids as solids).

My issue with bitwarden (which is why I ended up choosing 1password) is that it doesn't provide an Android keyboard to insert passwords into apps that block clipboard access. (Keepass has this, but I wanted a simpler synchronization story.)

How to Remember 7 years ago

Some people have difficulty or are unable to visualize in their mind's eye (aphantasia).

Moving to TypeScript definitely helped us. The move itself revealed a couple undefined variable errors, and static typing has saved us a lot of pain. It was also extremely useful for when we decided to remove a few libraries; the static typing gave us confidence that we didn't miss a few usages.

In case you're still interested in an exact solution, I think computing the Voronoi diagram for the polygon (treating each vertex as a point) should help in finding the answer. The deepest point should lie on one of the edges of the Voronoi diagram.

Actually, based on my reading of the paper, it seems that they learn a representation using one data set (the one with 1000 labeled samples per identity), then use that representation to classify on other training sets (like the Labeled Faces in the Wild, which has 13,323 photos of 5,749 celebrities). In fact, from what I can tell from section 5.1, they seemed to use face pairs (and so trained on 1 sample per person, and then tested on the other sample).

tl;dr: They don't need 1,000 labeled samples per identity (once done with the representation phase), and they achieved 97.25% accuracy on ~6,000 distinct identities, with only one training photo per identity.

It's set in an alternate universe to the actual Harry Potter series, and starts from the events in the first book. You won't miss much from not having read the actual books.

You're welcome.

I do plan to try to add some Gaussian noise to the sample points -- thank you for reminding me. I also hope to find ways to optimize the fitness function and selection function. I think there is much that can be done to fix it up.

It is a cute example. It's meant to teach Pyevolve and basic genetic algorithms with an example that doesn't seem too contrived. But thank you for noting that -- I'll add it to the article as a disclaimer.