Old and new apps, via modern coding agents by Terry Tao

Building visualizations with LLMs has been a major boost for my CS classes:

https://htmx.org/essays/universities-and-ai/#demos-visualiza...

Many visualizations that I have always wanted but just didn't have the time to build, I now have.

To give an example, I wanted a simplified 8-bit computer to complement the 16-bit teaching computer I use and designed this in a few days with the help of claude:

https://bdp.cs.montana.edu/

Terry Tao using coding agents to build apps means we're one step away from a Fields Medalist asking an LLM why his Docker container won't start, just like the rest of us.

There is infinite latent demand for software, most especially outside the traditionally software-focused spaces. If LLMs stopped improving today it would take us 10 years to catch up to the new software-writing abilities that have become available. This is a great illustration of that fact.

Terry Tao using coding agents feels like watching a Michelin-starred chef discover microwave dinners and get genuinely excited about them.

Nice balanced perspective there at the end:

"as such [LLM-coded interactive] supplements are not mission-critical to the core of the paper, I again feel that the downside risk of using guided interaction with LLM agents to generate such visualizations is acceptable."

It's a tool. Good for some things but not others and generally not to be trusted.

Running legacy educational Java applets, especially around math and physics, has been a longstanding popular use case of our CheerpJ Applet Runner extension, running Java bytecode in the browser via WebAssembly.

I am not sure how to feel about agents solving the problem via proper modernization. It's certainly positive that students will be able to interact with this content in a modern and more accessible way, but the educational use case for our product, although not commercially important, has always been a source of pride.

https://chromewebstore.google.com/detail/cheerpj-applet-runn...

I always enjoy these "domain expert has fun using AI to do something in their domain" articles. But it's always a hobby project, never something serious.

Using LLMs to generate dashboards is probably their most productive use case

even though there's still a lot of work to push things over the finish line, i have enjoyed how much it has reduced the activation energy for starting and finishing "one of these days..." projects!

The article's awkward opening statement proves it wasn't written by AI.

I have been interested in machine-assisted ways to do and teach mathematics from as far back as 1999, when I started coding several applets in Java 1.0, both for my complex analysis and linear algebra courses, to visualize various mathematical objects I was interested in (such as honeycombs or Besicovitch sets).

I am far from a mathematician but I am excited by the possibilities of using AI for generating more math. Math in my mind exists purely in the world of forms, and cannot be appropriated for profit, but is downstream to everything else. I am keen to see what this enables.

This is amazing!

His website using mathematical knowledge is refreshing. There's a small UI bug, but personally, I wish more educational materials were this rich in audiovisual content.

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The more Terry talks about AI, the more I'm starting to feel like Terry may have some undisclosed conflicts of interest.

https://www.reddit.com/r/mathematics/comments/1tryyw7/terenc...

LLM will do very good job in pure mathematics since it don't need the senses to logically understand/conclude a given topic.