David R Pratten

Release Train Engineer (SAFe) and part-time UTS Computer Science PhD researching query languages that bridge databases and constraint programming.

[David R Pratten @davidpratten]

@julianhyde After discussion with Claude I chose Antlr as the parser. Py / Js support was the clincher. This is for the implementation of https://t.co/nkb77hZXYM

[Mario Tomic @mariotomich]

Just 8 minutes of walking increased creative output by 60%.

Stuck on a problem? Go for a walk.

[Dustin @r0ck3t23]

Terence Tao has an IQ above 200.

Youngest gold medalist in Math Olympiad history. Fields Medal winner. The greatest living mathematician by nearly any measure.

And he just said something most people aren’t ready for.

Tao: “This whole era of AI is teaching us that our idea of what intelligence is, is not really accurate.”

We spent centuries building civilization on one assumption.

That intelligence was sacred. Irreducible. Uniquely ours.

The one thing that made the entire human story make sense.

Then AI started solving things we swore only we could.

Chess. Language. Vision. Math.

And every time, we reached for the same defense.

That’s not real intelligence. It’s just tricks. Just pattern matching. Just an algorithm.

Tao: “You look at how it’s done and it doesn’t feel like intelligence.”

So we moved the line.

Again. And again. And again.

Because intelligence was supposed to feel like something. Something deep. Something we could point to and say… this is what separates us from everything else.

But AI kept solving the problems.

And that feeling never arrived.

Tao: “We were looking for some elusive, intelligent way of thinking and we don’t see it in the tools that actually solve our goals.”

Here’s what makes it worse.

Large language models work by predicting the next word. One word at a time. No grand architecture. No deep understanding. Just probability.

And it works.

Tao: “Maybe that’s actually a lot of what humans do as well.”

The greatest living mathematician just told you human thought might run on the same machinery.

Not some transcendent spark.

Pattern recognition. Prediction. One thought, one decision, one word at a time.

We built religion around intelligence. Philosophy around it. An entire species identity around it.

And a machine running probability just held up a mirror.

We didn’t lose intelligence to AI.

We just finally saw what it always was.

What haunts us isn’t that machines learned to think.

It’s that thinking was never what we needed it to be.

[Jay Van Bavel, PhD @jayvanbavel]

The best predictor of scientific impact isn't gender, seniority, methodology, or geography, it is the informal network of colleagues and mentors who provide guidance and feedback. We are often ignore the most important source of success.

Informal support networks are the unsung heroes in science. Joining a great community of supportive and collaborative colleagues might therefore be one of the most important keys to success.

This is based on a new paper analyzing the scientific impact of 86,000 scholars. The authors found that informal connections (ie the people who you thank in acknowledgement sections) are more important that your coauthors in predicting publication productivity and impact.

https://t.co/w8rJHWFpha

[Saurabh Kumar @drummatick]

crazy results

In digital logic, you know that a single NAND gate can build any Boolean circuit.

AND, OR, NOT, XOR... all reducible to NAND. Nobody had found the equivalent for continuous math, the stuff on scientific calculators: sin, cos, log, exp, sqrt, etc.
This paper shows that one binary operator does it:

for example eml(1, eml(eml(1,x), 1)) = ln(x) and eml(x, 1) = exp(x) - ln(1) = exp(x) - 0 = exp(x)

once you get ln(x) and exp(x), you can get anything from using same operator again and again

[David R Pratten @davidpratten]

@arpit_bhushan_1 Constraint programming programs are formed from the data ie facts on the ground. The two paradigms are tightly coupled but to this point there is a gulf between their mental models and code.

[David R Pratten @davidpratten]

@ShriramKMurthi @rahuldave @p0nk @EricWalkingshaw Fair enough. Thanks for taking the time to consider its relevance to your quest.

[David R Pratten @davidpratten]

@ShriramKMurthi @rahuldave @p0nk @EricWalkingshaw Concerning languages for combinatorial problems you may find our recent paper interesting. https://t.co/nkb77hZXYM

[David R Pratten @davidpratten]

@FilasienoF @BenjDicken I’m working on an initial implementation ATM. Part of PhD studies.

[David R Pratten @davidpratten]

@FilasienoF @BenjDicken @FilasienoF I’m keen to stay in touch as your ideas develop.

[David R Pratten @davidpratten]

@FilasienoF @BenjDicken Yes! Nicely put! We are bridging communities of practice, the query writer (whether human or AI) need master just one language for both manipulating data and exploring possibility.

[David R Pratten @davidpratten]

@jpwhitcombe @thogge Politicians choosing their own electors via gerrymandering comes to mind.

[David R Pratten @davidpratten]

@julianhyde Archive October 12, 2025
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[Murat Demirbas (Distributolog) @muratdemirbas]

[new blog post]

Academic chat: On PhD

https://t.co/8TjcXWTOfp

[David R Pratten @davidpratten]

@julianhyde Yes this is explained by the Sock drawer theorem

[David R Pratten @davidpratten]

@julianhyde @morel_lang Separating concerns is a positive pattern. SQL’s choice to admit bags doesn’t break the relational model because there is a trivial isomorphism between a bag and the otherwise equivalent relation adding a nonnegative integer attribute interpreted as multiplicity.

[David R Pratten @davidpratten]

Can anyone show how to write a .html file and serve it in so that @z3 solver wasm runs in the browser? Gemini, Claude and I failed miserably yesterday,