mrdmnd

Yeah, I think this is the goal - remember; there are some problems that only need to be solved correctly once! Imagine something like a millennium problem - you'd be willing to wait a pretty long time for a proof of the RH!

I've been doing some reading on LLMs for protein/RNA structure prediction and I think there's a decent amount of work on SO3 invariant transformer architectures now

ex-Loon engineer reporting in. Can confirm, I'm having a good chuckle.

When new players learn Go, they're told to "lose their first fifty games as fast as possible."

Location: San Francisco, CA

Remote: Yes

Willing to relocate: No

Technologies: C++, Rust, Python, Java, Scala, Lua, PostGIS, SQL, all the standard geospatial data science stuff

Résumé/CV: https://drive.google.com/file/d/1-Zsa5C7fQKJmj7YgUJlRa4b_V_9...

Email: mttrdmnd@gmail.com

--

Mid-career jack-of-all trades problem solver with a decade of software engineering, data science, and analytics experience. Very experienced working with large geospatial datasets, planning, simulation, and control policy work. Looking for roles involving physical science, chemistry, energy, or other fun science and engineering problems.

I bet the folks at Skydio would want to talk to you.

this reminds me a bit of Cockatrice - hope your version ends up cooler though!

I can't believe anyone else remembers this game but my best friend in elementary school and I used to spend our entire sleepovers playing Oni. What a legend.

Good note; thanks! If a mod wants to change the link to that one, it'd be great.

Looking at the datasheet, it looks like there's one qubit with quite a bit worse error/noise than the others - anyone know why this might be?

Somewhat relatedly, this reminds me of the instruction I learned about recently: the PEXT instruction.

https://software.intel.com/content/www/us/en/develop/documen...

This is the best comment I've ever seen describing the actual practice of mathematics.

(as a historical aside, the name is "Quipper" because I kept trying to pronounce the project name (ChromeOS-Wide Profiling, or CWP) and ended up quite liking "Quip".

The internal aggregation code, of course, is known as Bartlett.

Fun fact, I wrote the first version of this code as a Google Intern. Imagine my surprise when I saw that they're still using it, and it's been developed and fleshed out!

This is an interesting look at how transit is shifting around public Micromobility options like scooters and bike share. Notably, commute hours seem to be drifting away from bimodal morning-evening. A neat take!

I think Bayesian Optimization is what you're looking for here. There's an internal tool at google ("Vizier") for which a white paper has been published that solves this exact problem. I don't know if there are any public implementations of Vizier but you could probably reverse engineer some of it from the white paper: https://static.googleusercontent.com/media/research.google.c...

Location: San Francisco Bay Area

Remote: Yes, flexible.

Willing to relocate: no

Technologies: C, C++, Python, Scala, Mathematica, Matlab

Resume: Contact me directly

Email: mttrdmnd@gmail.com

--

Interested in research grade problems. MIT-trained computational geometer. Current interests include earth science prediction problems, robotics, and geometric optimization.

Most recently worked at Google X as balloon systems simulation engineer. Contact me for some wild stories about airspace ;)

Just remember,

http://funroll-loops.teurasporsaat.org/

I saw an article on here a few days ago that suggested you could detect isotopes present in "more recent" forgeries that came about as the result of the nuclear testing age that would not be present on the originals.

He's also the chief contributor to the S2 Geometry Library.

I'm on a google machine now and it's a symlink to /bin/bash.

That video is 100% filmed on the multi-use path outside google :D

As someone who just did this internally:

Do it. It's worth your time. Very well paced exercises, and it walks you through the flow quite nicely.

Interesting that the optimal solution is not "slide it along the space diagonal" but rather "slide it parallel to a face".

He may just be quick at executing the Doomsday algorithm - neurotypical here, but I enjoyed learning this trick, and you can too: https://en.wikipedia.org/wiki/Doomsday_rule

"Complicated S2?" That's surprising, the S2 library (https://github.com/google/s2geometry) seems really clean and fairly intuitive to me.

I remember a classic MIT problem set in computer science where we reduced the problem of finding a "profitable arbitrage loop" in a directed graph to a shortest path problem: imagine a graph where nodes are currencies and edges are exchange rates: we're seeking to find some loop of nodes U,V,W,...U such that the cumulative product of the edge weights is greater than unity.

The trick is to transform the graph by taking the negative log of the edge weights, which turns problem of finding a cumulative product > 1 into one of finding a negative sum loop. Then, you can just run the Bellman Ford algorithm and if it detects a negative cost cycle in the transformed graph, this corresponds to a positive arbitrage cycle in the original graph.

I always thought that was a neat application.

AQUABIKE!

This is neat =)

Solved to an exploitability of 1 milli-big-blind / game, which is stated to be within ~approximately optimal over the bounds of a human lifetime of play.

I don't play EVE because there are already enough demands on my time, but damned if this commercial (entirely done with voice comms) hasn't come close to pushing me over the edge:

https://www.youtube.com/watch?v=AdfFnTt2UT0