onhn

Unless I misread it, if a project is deemed to have an "FBA" then the project leader is an "FN", in the author's opinion. And yes, some such projects have been explicitly called out.

>Really Bad Acronyms, or FBAs, are spawned by FNPLs (Nerdy Project Leaders) when naming new systems

Nothing like personal attacks to get your point across. Well done author.

The standard and most effective form of curation in science is the reference list at the end of a paper.

But usually you just read everything that is relevant to your research interests from the daily arxiv posting.

"You can upload your research and publish it on the open web. Members of the community will be able to vote on your research to raise its visibility."

Oh dear.

Are you sure it was peer reviewed at all? It looks like a conference proceedings.

I think the article misses the point of what physics is. It is not a collection of "sparse" models and principles, rather, it is a scientific discipline from which such models have emerged.

You will notice the article conflates the two things: physics and the known laws of physics (e.g. first para in section 1.2). Simplicity of the latter does not imply simplicity of the former, but the article assumes that it does in order to tackle/state the question as posed: "Why is AI hard and physics simple?".

The author is talking about how a given physics model appears simple when they are presented with it, e.g. a particular quantum field theory. This is the kind of limited perspective about research that an undergraduate physicist may develop simply by solving the hand crafted problems that are presented to them.

However, the true difficulty in physics is arriving at that model in the first place. Decades of work offered up against experiment, the associated conceptual leaps in understanding required to get to e.g. a quantum field theory which succesfully predicts things are nothing short of a monumental achievement. To say that physics is simple is ludicrous.

"The counterfactuals that matter to science and physics, and that have so far been neglected, are facts about what could or could not be made to happen to physical systems; about what is possible or impossible."

On the contrary, if I had to describe theoretical physics in a nutshell, I would say it is entirely about what is impossible. Pick any physical law or theorem. I cannot exceed the speed of light. I cannot globally decrease entropy. I cannot measure a force between two static electric charges in vacuum that deviates from the Coulomb force law.

Note that if f(x) = x^2 then the second derivative f''(x) = 2, so it looks like you're off by a factor of 2 (as well as the accuracy issue).

Knowledge of complex numbers are required to solve quadratics too (when the discriminant is negative).

If you liked Primer, the film "Timecrimes" does an excellent job at the physical consistency of time travel.

It is interesting that they chose to use a first person shooter as an example screenshot since gameplay would be broken by visual changes in occlusion.

I think we need more clever people making more predictions (and especially from people quoted in the article like Gross, Witten, Rattazzi etc), and fewer blog articles like this designed to discourage them.

The last time a huge, costly, dedicated collider was built, it was in service of the Higgs prediction, and that worked out quite nicely.

IANAL but I expect not. I would imagine the rental company would then just bill or sue the driver for the loss and inconvenience (or otherwise claim it on insurance).

On a similar note, I would like to think a rental car company would suffer consequences if a drunk person waddled up to the rental desk and they were handed a set of keys.

> astronomers use supernovae to measure distances, which is important for cosmologists to study, for instance, the expansion of the universe and dark energy.

AFAIK supernovae datasets are usually obtained as a survey, resulting in a statistical sample which can be used to compute cosmological observables. Here it seems that there is a new sample bias introduced by the neural network classifier. Can this bias be accurately quantified?

I think this would be great, yes.

The store has no reason to hide the markup if its fair, reflecting the convenience they added.

I think only in the same way that 'soccer' is not a good name for football, as a reference to domestic violence

In that case, hypothetically what about a separate app that only sells game currency, like vbucks?

There is a fundamental reason not to publish scientific code.

If someone is trying to reproduce someone else's results, the data and methods are the only ingredients they need. If you add code into this mix, all you do is introduce new sources of bias.

(Ideally the results would be blinded too.)

As a theoretical physicist your results should be reproducible based on the content of your papers, where you should detail/state the methods you use. I would make the argument that releasing code in your position has the potential to be scientifically damaging; if another researcher interested in reproducing your results reads your code, then it is possible their reproduction will not be independent. However they will likely still publish it as such.

For me its also the quality of the ads which is a problem. Over and over I get Grammerly adverts even though I always flag them as repetitive, inappropriate or irrelevant (always signed in). They have nothing to do with my interests or viewing habits.

Twitch does an outstanding job by comparison.

It may appear higher resolution but I don’t enjoy looking at the extra details knowing that they are probably fictitious.

I was referring to, and should have written explicitly: "anthropogenic climate change" -- this was the context of the parent's comment. I don't think your examples are immediately obvious as evidence for it.

Not sure about ordering people like this, but to your underlying point: I would say that the evidence for Earth not being flat is directly and immediately observable in everyday life. Climate change evidence on the other hand, one has to either put in some effort in the form of research/reading, or, place trust in an authority or peers.

The article would have been a lot better if there was at least one example of where a coding ligature was a problem, rather than talking about feet and inches

For instance it mentions the pairing => but provides no examples.

After reading I’m far from convinced that carefully curated language specific ligatures are a bad idea.