Cavalcade of Mammals

Updated jim_voronoi.zip extension to work with Inkscape 1.3! (Original version of the extension.). To install, go to Inscape -> Extensions -> Manage extension -> Install packages tab -> click on file icon and select the zip file.

Takes as input a shape to fill with a Voronoi diagram. The number of levels of recursive Voronoi diagrams can be set.

Options

Random seed points: Number of starting points. The distribution of the starting points is set for each level of the diagram.

Options:
Levels of recursion: Within each Voronoi region, a new Voronoi diagram is created.

Level(rand_type):relax,…: Sets of parameters for each Voronoi diagram level.
<level>(<normalization method>[param1=n;parms2 = n.n; params3=foo…]):<Llyod’s relaxation interations>
The randomization type can be ‘normdist’, ‘normdist_edge’, ‘random’. ‘Random’ distributes the seed points randomly. ‘Normdist’ distributes the seed points around one or more ‘centers’ (default is 1 center), distributed around the centroid. ‘Normdist_edge’ moves the seeds away from the centers toward the edge.
Llyod’s relaxation moves each of the points halfway between its current position and the centroid of the Voronoi polygon it is located in with each iteration.

Parameters:
centers = 2 – Number of centers to cluster ‘normdist’ random points around. Centers are spaced at center_dist from the centroid of the input path.
keep_centers = 0,1,3… – Which of the centers to use. Numbering starts at 0.
center_dist = 1.23 – Distance from the path centroid to place the random seed centers. dist = size / center_dist. Default = 2.0. Large numbers push the centers towards the edge.
min_dist = 1.23 – Minimum distance of random points from the edge of the path. In Inkscape units. Default = 5.
sd = 1.23 – Standard deviation of the random points. sd = standard deviation of the random points. sd = size / sd. Larger numbers give a tighter distribution. Default = 2.5.
xy = x1,y1, x2,y2… – Explicitly enter random seed point locations. In Inkscape units. Overrides random dist center parameters.

Return lines or polygons: The Voronoi regions are added to the document as polygons or lines.

Keying off Kevin Drum’s The lessons of COVID, which is a good start but too limited in imagination.

What the US did right: the CDC has great world-wide infectious disease monitoring.

What the US did poorly: the US had spotty local infectious disease monitoring. And lack of data–ignorance–was used as an excuse for inaction. With post-COVID wastewater monitoring, the US is doing better, let’s keep the funding high for it.

Biggest mistake: the federal government responded slowly and ineffectively in the first two months. Faster response that seems like an over-reaction at the time is the best response. If the response is effective, and a disease is slowed or stopped, it should always feel like an over-reaction. Hoof-and-mouth disease is the model.

Tintin store in Porto

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In an ever-changing, incomprehensible world the masses had reached the point where they would, at the same time, believe everything and nothing, think that everything was possible and that nothing was true. […] under such conditions, one could make people believe the most fantastic statements one day, and trust that if the next day they were given irrefutable proof of their falsehood, they would take refuge in cynicism; instead of deserting the leaders who had lied to them, they would protest that they had known all along that the statement was a lie and would admire the leaders for their superior tactical cleverness.

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WuXi AppTec news / blocking Chinese biotech outsourcing

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The Museum of Science and Industry closed for mysterious reasons last week. Here’s why. It’s a sad day when it’s easier to get information out of the Pentagon than from the Museum of Science and Industry. by Neil Steinberg

Velvet Ants of North America by Dr. Kevin Williams, Dr. Aaron D. Pan, Joseph S. Wilson. 2024.
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Recomendo

The new AI / LLM tools have many potential applications, but many of them will have downsides for some people–replacing copy writers, some tech support, these are benefits for the companies that apply them, but many of today’s jobs in those areas will be eliminated.

One application that seems inevitable and all positive is raising the floor for human performance. An tool that you can ask for advice, or better yet an AI tool that monitors you, by email, or watches internet use across devices, and/or is watching on video, understands what the user is doing, understands the context, and provides advice will help people avoid mistakes. While these mistakes are not obvious to the person making them, they are obvious to a person with experience, or able to research the problem. Imagine a person playing chess alone vs. someone playing with a chess program to flag potential mistakes, with the general knowledge of an AI allowing it to work in many more situations.

This AI tool can develop slowly and in a modular fashion, will be useful even in crude form, but will become revolutionary once it gets good enough. Imagine a person using a crude form of this as an interactive chat tool. The person could say, I’m taking a vacation to Greece and get advice on things to do, what they need to know about currency or visas. Or imagine a more advanced AI would remind a person of an appointments, or tells them they need to change the house air filter. If a person was goiing to make a poor decision–routinely using check cashing places or buying a car with poor service record, the AI could warn them.

This AI tool would be able to slot in special modules as needed. A person starting a business could get localized advice on the steps to take. Someone buying a house could get advice on things to check, and a new homeowner could get advice on what to check and repair and reminders for maintenance.

What we talk about when we talk about The Future. A few thoughts on four genres of futurism. by Dave Karpf. Pundit futurism, The Professional, Techno-optimist Futurist, Cassandra-futurism, The Sci-fi futurist

Google Pixel 6 Pro, $220, specs

Bruce Schneier talked at Capricon about fifteen ideas he had on AI that are forming up into a 2024 book. One thing he mentioned is that AI would make lawsuits much cheaper to launch and carry out, and multiplying the number of lawsuits would mean that courts would need to adopt AI adjudication to adapt to this. Bruce passed over this pretty quickly, but I think this will have early and pronounced effect on society.

It looks like legal work is a problem AI will be able to solve soon. That is, AII tools will be able to contribute effectively to the process of filing and carrying out lawsuits. This is not one problem, but a set of related problems that AI will soon be able to do effectively. Given a set of facts and objectives, an AI will be able to determine what type of lawsuit to file, write it up in the proper jargon and format suitable for submission, determine and write a response to opposing counsel motions, summarize and prioritize discovery material, etc. A lot of legal work is routine, repetitive, and very similar to previous cases. Really, a perfect problem for AI.

The immediate upshot is that a lawyer using AI tools will be able to do much more legal work, work faster, and lawsuits will be much cheaper to launch. The short-term impact is that the number of lawsuit filed will go up multiple-fold and this will crash the courts. Gum them up. Bring things to a standstill. US courts are operating at capacity already and can’t handle more cases.

There isn’t any way for courts to prevent this. The lawsuits will be filed by lawyers at established law firms. Lawyers will use AI as a tool, review AI written suggestions and briefs, and from the court’s perspective these lawsuits will look just like the existing lawsuits, there will just be many more of them.

In the long term, it will make sense for judges and the courts to adopt AI tools to accelerate their end of things, but this will require new laws. New laws means years of hearings, discussion, negotiation, etc. Government functions require deliberation and consideration before making big changes. And who will develop AI tools for courts? The market is smaller and more uncertain than the market of making these tools for private law firms. And judges are very conservative, notoriously slow to act, to react, to adopt new technology.

So AI-assisted lawyering will hit the courts at some point in the next few years, but it will take a decade or more for the courts to effectively react.

Robert Comploj, glass artist.

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Librarian on social media, mychal3ts