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“ This is not the smoothness problem solution, but rather the Burgers vortex, an exact solution of the Navier–Stokes equations published by J. M. Burgers in 1948, chosen because it has the same anatomy: fluid drawn inward in a plane, stretched along the axis and thrown out of both ends, spinning fastest in a core.”

This blog post is essentially a summary of the original video.

https://www.youtube.com/watch?v=0Y-9GbsS9Fg

Funny to see that they did not include Fable 5 in their GeneBench and LifeSciBench comparisons because "it does not answer advanced biology questions and refuses the majority of questions in this eval".

Winner by default!

I presume all the Foundation AI companies have been doing this for years, to avoid training models on their own generated data?

The microbubbles in scuba diving that cause the bends are the ones trapped in joint space fluid. That fluid doesn't circulate at a useful rate, so unfortunately you can't really "burst them somewhere else" =(

This is a great puzzle game. I think it actually teaches the concept of "piece coordination" in chess very well.

One suggestion is to have all enemy pieces move simultaneously. I expected that the losing condition is that I am threatened and there are no unthreatened squares to move (checkmate).

However, since the opponents move one-at-a-time, I found that even if I moved to a safe square, sometimes I could be both threatened and captured in the same move! Which is somewhat different from normal chess, since now you have to consider the possible orders in which the opponents move. So even moving to unthreatened squares could be a game over.

In real-life, before the election there is a margin of error on the support of a bloc.

If you interpret a "tie" in this game as "either party could win within the margin of error", then it becomes a lot closer to solving the problem that gerrymandering algorithms try to solve in real life!

The game stores and allows you to see the RNG seed that controls the run's events and layout. The developers want players to be able to share seeds that produce interesting runs.

That requirement is what made this problem difficult for the devs to solve.

The only reason I think biotech companies are not yet raising hell (and invoking the False Claims Act) is that Thermo Fisher's antibodies are already known to be notoriously bad, and everyone serious seems to have to validate everything themselves.

I'd treat this about the same as datasheets for mechanical or electrical parts.

When I buy an electronic component as a regular consumer I expect the datasheet "typical" values to be accurate 90% of the time. I can imagine larger industrial customers would really raise a stink if it's worse than that. However, any critical components in my circuit must be verified and "binned", and that's on me.

In case people don't realize, this is satire.

Man, I really tried but I can't even get through the article because it sounds so AI written. I feel like I'm scrolling on LinkedIn...

What is the advantage of this Monte Carlo approach over a typical numerical integration method (like Runge-Kutta)?

Is there a visualization of the glider in the thread? Would love to see how it evolves with one dimension being time.

Be rest assured Ben’s previous job was in the medial imaging industry. While he worked on MRI machines rather than ionizing radiation, I think he’s very well aware of the dangers of X rays and has many projects dealing with ionizing radiation. There’s a lot of bad safety science YouTubers, Ben isn’t one of them :)

Funny thing: it’s actually rare to get radiation damage to human hands and feet since there’s not too much growing tissue there!

I’m not a mathematician, so could someone explain the difference in usage between Lean and Coq? On a surface level my understanding is that both are computer augmented ways to formalize mathematics. Why use one over the other? Why was Lean developed when Coq already existed?

Presumably they want to eventually put a human inside it, in which case having a humanoid robot to work off of wouldn't change the aero calculations and designs too much. The article talks about specific design considerations to avoid the exhaust gases.

Both OA and RA involve some inflammation (-itis means inflammation). RA is more T cell driven inflammation (and clinically visible) while OA is more macrophage driven. Mechanical wearing still makes the joint unhappy at the cellular level- you just don’t see it big and red as a symptom like in RA.

Glad to see this! We need better treatments for OA short of a joint replacement.

I'm not too surprised that this treatment works. It's essentially like localized steroids to just the joint- killing off the immune cells causing inflammation.

Good features is that it's localized (so no systemic immunosuppression) and the risk of cancer is low since you rarely get radiation-induced cancer in joints because there's not enough dividing cells. Unfortunately heading to radiotherapy is a logistical challenge, but there are enough people suffering from OA that would happily do this to get relief.

Is it not illegal in the US to break up a company to isolate liabilities?

I'm not too impressed with this article since it doesn't really give a definition for computing, just picks a few similarities between what we see as computing (in the practical sense) and what cells do.

It's a shame because there *has* been a lot of deep work done on what kind of computer life is. People often use the Chomsky Hierarchy (https://en.wikipedia.org/wiki/Chomsky_hierarchy) to define the different types of computer vs automata. Importantly, a classical Turing machine is Type-0 on the Chomsky Hierarchy. Depending on what parts you include from a biological system, you could argue it's anywhere from Type-0 to Type-4.

Interestingly, the PhD thesis of well-known geneticist Aviv Regev was to show that certain combinations of enzymes with chemical concentration states are enough to emulate pi-calculus, and therefore are Turing machines! https://psb.stanford.edu/psb-online/proceedings/psb01/regev....

While I think most of the examples are incredible...

...the technical graphics (especially text) is generally wrong. Case 16 is an annotated heart and the anatomy is nonsensical. Case 28 with the tallest buildings has the decent images, but has the wrong names, locations, and years.

Worth noting that Elon only gets the $1T if he can deliver >1M Robotaxis, >1M "AI bots", and bring Tesla's market cap to $8.5T.

Looks like they are really doubling down on the 2018 compensation package and the idea that Elon's attention is worth more than anything.

More details on the milestones can be found in the SEC statement: https://www.sec.gov/Archives/edgar/data/1318605/000110465925...

It's possible to simultaneously believe that private companies should have control over what messages are shown on their own platform while also believing that exerting such control can be negative to the world.

It's the same reason libel and defamation laws exist: someone realized that countries operate better when spreading falsehoods to tarnish a party is illegal, and so laws exist to influence public discourse.

Seems like it is based on this paper from CVPR 2024:

https://aiotgroup.github.io/Person-in-WiFi-3D/

Frankly I'm shocked it's possible to do this with that level of resolution.

Slightly misleading title- this is the overall blueprint for a large ongoing effort by the Imperial College London to formalize FLT in Lean, not the proof itself (which is huge).

The project webpage has more information about the efforts and how to contribute:

https://imperialcollegelondon.github.io/FLT/

Also discussed on HN in 2021 (132 comments).

https://news.ycombinator.com/item?id=26577062

A good step forward. Reading the referee reports and rebuttals from papers that previously opted in to transparent reviewing was incredibly useful to my own paper publishing process. In many ways Nature is ahead of Science on this.

I hope that making things transparent will help reduce the situation where big labs have an easier time getting their work into high impact journals through relationships with the editor.

The parent commenter is not speaking about science as a whole, they are speaking about US dominance in science.

You state that "hiccup won't stop or even slow down science in the US. All it will do is take government out of the equation." I disagree and I would suspect most scientists reading that statement would also disagree. I too have seen many bright people turning away from the US because of this. I am personally certain that these policies will significantly slow down science in the US.

After all, when David Hilbert was asked in 1934 "How is mathematics at Göttingen, now that it is free from the Jewish influence?", he replied “There is no mathematics in Göttingen, anymore”.