Does not matter in this case, if they don't host an online version of it. My impression is that Siemens wants to shut down the project completely.

If Siemens does not re-distribute them, then Siemens does not violate any copyrights on them. Only if Siemens would continue to distribute binaries of OpenRadiuss to customers, they would be in violation.

It depends on how the contributions were licensed. A lot of projects require either copyright grants to the project steward (for example, the FSF) or explicit permission for the steward to distribute the code under some other license. Occasionally there are good reasons to relicense code, like the transitions across GPL versions, but this is the obvious risk of giving those permissions.

Or: We eliminated the positions necessary to merge the changes coming from the outside, and we will support the customers in house, if there are any paying customers at all. After that, we will close the project for good.

While in general, I agree with your sentiment, you mentioning the Dunning-Kruger effect is not appropriate here. Dunning and Kruger (1999) does not claim incompetent people would consider themselves above the experts. It's just that incompetent people do no consider themselves as incompetent as they really are, and competent people don't understand how far above the laymen their knowledge is. But both would agree, that the expert knows more about the topic than the layman, and both would sort themselves in the right categories.

You could consider the effect of Dunning and Kruger (1999) as a "mental regression to the mean".

That's not the issue - insurance companies have no problem giving insurance to humans which have "individual learning capabilities."

The problem is that while insurance companies can extract compensation from humans - essentially they can coerce the humans to work "for them" to pay them back - they can't get compensation from the AI, and there isn't a good framework to get compensation from the AI developers.

The issue isn't that the AI learns - the issue is that our legal framework doesn't have a good way to get "compensation" from errant AI - because the AI itself doesn't care if it gets shut off. You can't hold the AI itself "liable" like you can a person. So until we change the liability framework, we'll be stuck. This isn't a technical problem, so much as a social one.

That pretty directly disagrees with what you claimed the first time around. It privileges establishment sources rather than weighting all sources equally, and values safety and grounded answers over misinformation.

Part of self-driving cars being safer than people is that they don't drive "very close together" - they follow at the appropriate following distance and speed for the lines of sight. This alone accounts for a large portion of the improved safety performance of these systems.

Autonomous cars are actually very good at the driving task. Where they fail is when they encounter situations that are "abnormal" and I think the industry has a problem here; state of the art is either to train specifically for every situation (impossible in the limit) or to kick the decision to a human in a support center somewhere. Things like emergency vehicles, school buses, farmer markets, construction zones, etc.

The industry needs to figure out how to get their systems to "get confused, then reason their way out of a situation."

This long tail is where humans still do better - when there is some "new" scenario, like a particular combination of debris in the roadway, on a Tuesday, with gawkers, during a fireworks display. You will never be able to "train" your way out of that - you need the correct structural formulation for the problem space.

The big takeaway I have from their study is that their study areas - major metropolitan centers - is that cities have way, way worse than average incidents per vehicle mile travelled.

I mean the national average is only something like 1.25 fatalities per 100M miles, injuries only 75 per 100M miles, and "all" incidents like 140 per 100M miles. But the benchmark numbers on the linked websites range from 200 to almost 700 injury incidents per 100M miles in those cities.

Like, if you are using the average number, you can't even reduce the number of incidents by 841 over 271 million miles, because the expected value is only 203. You have to have a rate of at least 300 injury-incidents per 100 million miles to reduce by 841 at over 271 million miles. So really, their results are driven by San Francisco, Austin, and Atlanta.

Their confidence bands are also pretty low; for example they quote 2 serious or greater injuries in San Fran, which on 82 million miles there is a rate of "0.02 per million miles". But 2 injuries is not really enough to make a statistical inference.

Least of all because all the miles are with different versions of their software - you can't make any predictive claim.

Statistics never lie, but you can make them say whatever you want...

At present, no. I've done a number of experiments with LLMs' capabilities with generating fiction, and while they are impressive for a beginner writer -- because fo the lack of spelling and grammar mistakes, they are nowhere near being able to write competent fiction.

This is because they don't model reader or character minds, they're based on word probabilities, like a predictive text keyboard. The engineers can compensate for for this to a surprising degree by feeding it data to recognize specific situations (e.g. the car wash is 100 feet from my driveway; should I drive or walk?). But this is turd-polishing.

"I'll america you in your americaing america!" – Smurf Intelligence

AI technology practice isn't foundational. Critical thinking is. The closer AIs come to being able to do something that looks like them doing our thinking for us, the more capable we have to be at thinking without them. A human who can't outthink an AI adds nothing to an AI-human partnership.

This proposed school is a typical scheme by people who think because they have been educated, they understand how the education works. This is like thinking because you eat, you know how to cook. Project work in education is nothing new; it goes back well over a century. And in real life, you may get a STEM degree, but your real education in engineering comes from real life work. But that doesn't mean classes in calculus and physics don't do anything for you.

Or English classes, for that matter. Nobody doubts the value of project work in education, particularly *androgogy* -- the education of adults. But for *pedagogy* you have to establish foundational skills as the student matures intellectually and socially. Entering the high school years, a typical student has had *no* training in critical thinking skills. To develop critical thinking skills in an area, you need both general skills (epistemologicla literacy: research, location of orignial sources, dealing with conflicting evidence) and domain specific training in that area. In other words, *liberal arts* training is foundational in an AI-saturated world. "Liberal Arts" -- from *artes liberales*: literally the skills necessary to be a free person.

But I think these people have at least got the problem right: as AI drives the cost of elaborate projects down, we all have more projects in our future. Big, elaborate, faultlessly plausible-looking projects which may or may not have actual value.

Where they are completely wrong is the solution, which is to organize education around practicing using AI to make impressive projects. In a word of AI-enamored dunces this will put you at the head of a very sorry class of ignoramuses. The answer is to build fundamental cognitive and intellectual skils at every stage of a student's development. Project work is surely part of that, but it's just a technique, not a solution.

In a nutshell, the academy is training students to be the next step down the evolutionary scale from code monkeys. More like the pigeons B.F. Skinner trained in WW2 to peck at a screen, in an attempt to create a primitive guided missile without computers. They want to create "main characters"; and they'll probably create a few. There are always a few natural autodidacts in any moderately large group. But what they are set up is to produce a bunch of fragile, economically privileged narcissists trained to cover their lack of education with impressive-looking AI slop.

When I am looking at the contracts my company has for our company phones, I doubt your promise. As an American company, it has decided that providing company phones to its employees is not a core competency of the company. So it outsourced the task to the lowest bidder, and the lowest bidder has bought data plans for our phones which abruptly switch off everything above EDGE, as soon as the data allocation for the period has been exhausted. No warning. No graceful change. Just a hard cut-off. For everyone, including Field Service, who needs to have mobile internet connectivity to get and update trouble tickets.

Nowhere did I blame renewables. I was replying to someone talking about the huge price spikes pointing out that they applied to people lucky enough to have power.

We were out 5 and a half days for the derecho. We were in a hotel out in Sealey.

We had a generator for Beryl, but hadn't had it wired into the house yet. We had a lot of extension cords.

Later, I got the inlet and subpanel wired in. We ended up powering the house on gasoline pretty regularly without any named storms until we moved away from Houston.