I've started to call nonsense like this 'illegal but allowed by courts'

We can all read the constitution and our laws. We've been told the legal system tells us what they mean, but increasingly, the explanations we are provided and the decisions that are made seem at odds with the basic. Things like parallel construction, the good faith exception, and pretextual stops makes a mockery of people's rights and the ability of the justice system to even evaluate police conduct.

Theres a spectrum in here between soverign citizens and serious citizen pushback on legal overreach...but its a spectrum increasingly worth reflecting on. Obviously this is US specific.

It is primarily the hardware to software interface. It runs every feature in the car that converts software code into an out out voltage to do a thing. It is also how everyone interfaces with the car - teams, drivers, f1 tv, and even the race track itself.

https://f1chronicle.com/f1-standard-ecu-explained/

The standardized ecu was introduced as a cost savings and fairness measure in 2008. The contract was won by McLaren Applied (which was part of the same McLaren that is the current reigning champion but is now spun off and owned by private equity).

The teams basically get an sdk and are largely responsible for the software the cars run at pretty much everything above the hardware layer of abstraction.

As a weird piece of history, McLaren applied was not the original winner of the contract for the first standardized ecu in 2008. When it was announced, in 2006, Microsoft was.

It is likely better in some ways and worse in others...and few of hte people involved will have the understanding to tell the difference.

Tristan Buckmaster speaks about his role in the controversial Navier-Stokes solution. We are seeking an interview with OpenAI too. ... Since the video was finalised and uploaded, we have heard back from OpenAI and we're trying to schedule an interview. If we're successful, it will be uploaded ASAP and linked here.

Comments URL: https://news.ycombinator.com/item?id=49911380

Points: 3

# Comments: 1

On a regular basis I have students bring me “machine learning” models they have trained, which sounds great. But they have no idea what problem they are solving, what data they have or should have, and no idea why that method, etc. There is no understanding. They use words and concepts from a broad variety of fields, with confidence, but with little deep understanding. The Internet and AI give access to knowledge which is necessary but not sufficient for wisdom.

While K-12 bears a lot of blame (as a system not “teachers”) I’ve come to believe the problem is more societal. What we value and what kids logically perceive will be them ahead in life. If all they ever see is that surface level performance of knowledge is enough…why bother with more?

Many people, see prior conversation on HN, have already decided that AI solved it. The standards of reasoning and rigor in academia are complex enough that we all argue over them and harumph as we epistemically trespass on each other's domains.

The public, really humans if care for Herbert Simon, are much more apt to evaluate knowledge emotionally and by other standards. We may see them as wrong but standards only matter in context. The NYT, HN, and Annals of Mathematics will always have different standards of truth.

Would anyone be surprised if major model companies had tagged the accounts of competitor employees for extra tracking? Given the concerns about distillation and bench marking it hardly seems irrational, but how it is used matters quite a lot.

That aspect alone would/should be unthinkable to any serious academic. Authorship reflects who did the work and changing it for business competition reasons should be a red flag for multiple different reasons. They include, the sheer tactlessness of treating a major theoretical advancement as a competitive posturing first, the norms of academia second, and all the misunderstandings of the culture of the disciplines culture that people will now suspect are hiding beneath the visible surface (insert topography joke).

Math as a field is fairly unique even in how they list authorship. It was long the norm that authorship to be alphabetical because the idea of first, second, senior etc authorship is harder to define than many other fields.

“The stated rationale for alphabetical order is that it treats co-authorship as intellectually joint work: every listed author’s name carries equal weight, and no one has to negotiate, or be seen to negotiate, over billing. That is a genuine advantage over position-coded conventions, where disputes over who is “first author” are one of the most common sources of authorship conflict in fields that use them” [0]

That norm is changing, slowly, but one option people are pursuing is notable: randomized author order. Their is a perception that alphabetical is too biased…that’s the world OpenAI is stepping into when they make that offer of authorship to one scholar with a demand that he exclude his partner.

I can’t speak to the facts of anything else in this, but if a grad student came to me and said someone made them that offer, I would tell them to run and if they were brave report it.

[0] a to the point lay description of the history of math authorship can be found here: https://casrai.org/guides/mathematics-alphabetical-authorshi...

An analogy is akin to reviewing a paper. If I review a paper with some novel findings and then use my massive lab of graduate students to do the obvious next step before the other paper makes it through type setting and then shove it out as a pre print, I didn’t win - I was a jerk.

There are lots of cases of people using peer review or other accesss to efectively forerun others work and get credit. It’s a known problem of the nature of knowledge validation in academia, it’s not solved and it’s not deterministic but people know it when they see it.

This has gone on for a LONG time, but the change to empower it with AI tools that are presumed accurate is the new amplification.

In this day and age, GPS mapping tools have major implications for societal function, safety, economics, national security, healthcare, etc. I'm struggling to think of an industry where a sudden absence/subtle changes of named GPS mapping data would not have an effect.

If everyone relied on the same data base which could push changes to the map in the pocket of every resident of a nation that would be the first thing I would think to hack. Probably easier than actually jamming or spoofing GPS/GNSS over a huge area.

The internet security practices I experienced when working with the DOD in a prior life were…interesting?

Outside of the classified realm, there seemed to be little to no on the ground understanding of the Internet. Many things where internet connected that shouldn’t be or weren’t that should. I was involved in one contract where we had to demonstrate the ability to remotely access and control a system (to satisfy the system’s owner) as well as demonstrate that the system could not be remotely accessed via the internet (to satisfy the base IT folks). The solution was a hotspot kept in a lock box…that I doubt was ever locked after we left because it was constantly attached to our internal monitoring network despite our pleas.