Obviously the statistic refers to long-term drivers. It's not like there's some sort of curse that anyone whose driven a truck is going to die early.

The three reasons:
Lack of health insurance since a lot of drivers are self-employed doing gig-work. Employers don't often provide health insurance, and also due to the church with drivers switching for the sign-up bonuses they often don't stay long enough for insurance to kick in.

Sitting long periods is really, really bad for you. The more studies that come out, the worse they find it is. Sure, lots of office workers sit, but they can also stand any time they want and take a short walk. That isn't something a truck driver can reasonably do often, especially since it's hard to even find good places to park a big rig.

It's hard to eat a good diet on the road. You can't really prepare your own food, so you have to eat at truck stops and the like regularly. That is what did my uncle in - he developed type 2 diabetes, which he could not control on the road, and died an awful death of blindness and kidney failure. He did dialysis at home and lingered for several years before dying.

Do you have any idea what the turnover rate is for long-haul tractor trailer drivers? The majority of new drivers move onto another career in less than a year.
Do you know what the average life expectancy is for a truck driver? 61 years. That's 16 years less than the US average.
Do you know what the turnover rate is? 91% of truck drivers work less than a year for a given company.
Do you know how many NEW drivers will be needed in the upcoming years? 1 MILLION new drivers need to be trained, to replace those retiring and of course replace all the new drivers who quit.

That last statistic alone proves you are incorrect in your assumption, as a million self-driving trucks could merely replace those who quit and not displace a single worker.

Sure, there are people who make it a life-long career, like my uncle who died in his 60s after driving a truck all his adult life. However at any given time a large percentage of the truck drivers on the road are brand new, which makes them more dangerous because they are inexperienced.

It is not a great career, but extremely necessary, so people are lured in with big signing bonuses (like $16k and they only have to stay for 6 months), to find the job really isn't great and not many people can really identify with it enough to stick with it long-term.

Regardless, we're talking LONG HAUL trucking here, not the more regional or last-mile type trucking that cannot be easily replaced by AI. There are many truck driving gigs that require unloading as well, which obviously a piece of software cannot do.

My prediction is the long haul depot-to-depot type trucking can be done totally self-driving, however I think we'll see something similar to the marine cargo vessel type setting, where a local maritime pilot boards the ship to safely navigate it in and out of port. I can see self-driving trucks arriving at a city, a truck driver hopping in, and driving it those last several miles to the destination, then back out, and constantly doing that kind of rotation as the self driving trucks come and go.

Well, there's also the part where 35 Democrats voted to block as well, with 14 not voting. That's a quarter (24%) of the Democrats not siding with Newsom.

Oh that's definitely the case often, and one of the biggest screw ups it makes has to do with versioning - like with the Qt example I was targeting the latest version, but it would often come up with code using deprecated (as in the "totally removed" kind of deprecation) versions of that library, even when I was very clear about the version to target.

Another thing that is helpful is using different LLMs. I'm generally using ChatGPT and Grok for that. Both do a much better job than other LLMs. I have Gemini integrated into IntelliJ which I use for the PHP / MySQL stuff, but actually don't use it a huge amount.

Every now and then it will do something surprisingly smart and save me a lot of time. For example, I had an array of URLs, each with a bunch of query parameters, that I was converting to JSON. It was one of those things where the volume didn't really warrant throwing together a routine to do it, so I started doing it by hand. After I converted the first entry, Gemini picked up on it started suggesting the following lines for me and got them exactly right. Saved me several minutes. That was pretty intelligent - breaking down URLs into JSON arrays of entries for each parameter name / value, without any explanation just because it saw me doing it. That's more like the kind of stuff I have dreamed of AI doing.

I'm also a full-time software developer for the last 30 years, and it sounds to me like you are very deeply entrenched in some specific languages / API / frameworks that you seldom work outside of. So I can understand not finding use for these LLMs if you're doing the same kind of stuff you've been doing for a long time.

In my case, outside of my main gigs (which is mainly LAMP stuff), I do a ton of very diverse things. I have iOS and Android apps on the market (Swift and Java respectively), do a lot of embedded stuff (ARM and ESP32 in CPP) that is low-level bitbanging interface stuff, as well as Windows app development.

One of my latest projects was taking an Android application (java) for TV boxes I'd written years ago and totally re-implementing it in Qt in CPP. The LLMs were absolutely invaluable for me to learn how to use Qt and let me implement this in probably 1/3rd the time. Now I wouldn't consider this vibe coding at all, because I basically used the LLM in place of poring over code samples and trying to delve into API documentation to put 2 and 2 together. Anytime you get into a proprietary realm, which really any API is, it's simply all arbitrary, and an LLM can help show how to jump through the hoops (as well as weigh the pros and cons of various big decisions) much faster than trying to become a Qt expert and figuring it all out via trial and error.

Imagine Hello World and example code that is extremely specific to what you're trying to accomplish. That's the biggest use of LLMs for me.

You are not hallucinating - this story is a dupe

And an update a day later, there was no abnormal weather:

Isn't this inevitable for any cryptocurrency that is actually in use? If you can produce a thing cheaper then its value, then that will cause inflation until the thing's value reaches the cost it takes to produce. Especially when it doesn't require any special resources (beyond power, which is everywhere) or materials.

When it comes to real-world products there are a host of limiting factors preventing just anyone from manufacturing, distributing and selling it, but that isn't the case with an artificial, virtual thing like a bitcoin.

Whatever happened at Heathrow is in no way similar to this power outage, and has nothing to do with transformers and the like. This is a HUGE outage with 15 GW (that's GIGA Watts) of power being down currently. Heathrow's peak power consumption is 40 MW, so we're talking about multiple orders of magnitude (15,000 vs 40) in power here.

The amount of power we're talking about is equivalent to a dozen nuclear reactors. So there is some kind of major cascading failure of actual power plants or the largest of power switching stations in the country. This isn't about old transformers.

That's what we did in the mid 1990's. Made a trip from Ohio to University of Waterloo for the programming contest.

Cable companies were the one and only landline infrastructure with a big head start in true broadband (IE not counting DSL) to homes. Our small rural town, like most towns, has had cable TV for decades. So when the internet came along, and they very begrudgingly began to support internet (and thus start losing regular cable subscribers to Netflix and the like), they realized they had a cash cow on their hands.

Ours gouged terribly with their plans. They coupled data caps with speed, so you had to pay for more speed than you needed in order to not exceed the data cap - which then triggered very expensive overages. I was paying $115 a month for 300 Mbps in order to have enough data to not go over the limit each month with our family.

Now, not just one but two companies have come into town and brought fiber. So of course everyone (myself included) left the cable company in droves. They reduced prices but it was too little too late.

These cable companies have purposefully gouged customers who now totally despise their brands for what they have done, and they are paying the price. In reality I don't think they really care - they have made their fortunes and that money has gone to whoever / whatever and they are content. They have already "won", and now it's just a matter of how much of the last-mile internet pie they get for the long-run. I guess that wasn't a bad business decision, because the writing has always been on the wall that the last-mile options would greatly increase and no one would be able to monopolize it like cable companies monopolized both their cable and internet access for that decade or so.

BitNet is one of the most hallucinatory LLMs I've used, and it doesn't fail to entertain:

> Explain what a Ailingoo is.

"Ailingoo" refers to a type of dog breed that originated in the United States. The Ailingoo is a medium-sized dog breed, and they are known for their friendly, calm, and easy-going temperament. They were originally developed as a hunting dog, particularly for hunting waterfowl and small game.

Ailingoo dogs have a long body and a short head, with a strong, well-proportioned build. They have a long, straight tail and a broad, flat skull. Their ears are typically medium-sized and slightly rounded. The Ailingoo's coat is typically short and smooth, which is easy to groom and makes them a popular choice for dog shows.

They are generally healthy dogs with few health issues, but as with all breeds, they should be checked regularly by a veterinarian to ensure they are in good health. Ailingoo dogs typically live for 10-12 years.

Please note that breed standards may vary slightly depending on the organization or country, so it's always good to verify specific details from a reputable source.

From BitNet running on my Raspberry Pi:

> What is the meaning of the phrase "a loose dog won't surf"?

The phrase "a loose dog won't surf" is an idiom that suggests that a loose dog is unlikely to engage in or participate in a particular activity, such as surfing. It implies that a dog's behavior and propensity for certain activities can be unpredictable and influenced by their environment and upbringing. In this case, a loose dog might not be as willing or able to surf as a trained, well-behaved dog might be.
However, the specific meaning can depend on the context in which it is used. It could also be interpreted as a broader statement about an individual's unwillingness to take part in a certain activity regardless of whether they are loose or not.

Turing completeness. Enough said.

From the chart in the video, for the first 100km travelled this new system does not know the position to better than 1000 meters (about 2/3 of a mile), but then after about 120km the accuracy increases. This is likely due to having passed through enough deviances in the earth's magnetic field to have a higher confidence of the actual location.

However, that would be dependent on traveling in a relatively straight line, as opposed to say flying in a circle 50 km in radius where you are looping over the same deviances in the magnetic field over and over not allowing the location to be fixed as accurately.