freerobby

Cessna ceased production of all light aircraft in 1986, citing increasing lawsuits and legal liability for things it could not control in any practical sense. This had a huge negative impact on the GA economy and culture, because until that point, Cessna was producing more aircraft than any other company in history, and its 152 and 172 models were the most widely used trainers and safest GA aircraft ever made.

In 1994, Congress passed GARA[1], and two years later Cessna began producing new aircraft again. But having been out of the industry for a decade, Cessna lacked some combination of the means and confidence to bring back its entire fleet; so it focused on the 172 for the training market and abandoned the 152, which never saw production again.

https://en.wikipedia.org/wiki/General_Aviation_Revitalizatio...

Thank you! (PPL student here, still lots to learn).

Another reason there are so many Cirrus accidents is that in an effort to improve its safety record, Cirrus began advising its pilots to use the parachute whenever in doubt. I don't mean this as a knock in the slightest -- the statistics are very convincing that this is saving lives[1]. But a funny side effect is that you see a bunch of accidents where someone parachutes a Cirrus into a field that any other airplane would have just landed in.

[1] https://airfactsjournal.com/2016/08/whats-right-cirrus-pilot...

Does your Mooney have the TKS system, or are you saying there's a general benefit to a M20 over a 172 in terms of icing?

The problem is the same is true about 2-seaters, except they only really seat 1. :)

I have a '78 172 w/ 180HP STC, and I think it's a pretty good sweet spot. You can take a friend, a ton of bags, full fuel on long range tanks, and still climb easy on a humid day. You can also travel light, dial back the throttle and cruise around at 5.5GPH, making it similar in cost to operate to a 152 (still a 2000 vs 2400 TBO though).

Your main point is well-taken: you definitely pay a performance-per-dollar premium for using the world's most popular training platform. But you also get some benefits: the most familiar and one of the most forgiving airframes ever made; a platform that every A&P knows inside and out and every supplier stocks parts for; and a plane that can very easily get in and out of any strip you can spot.

A big party will attract some small people.

> For example no Porsche Taycan buyer is ever going to choose a Model 3/S just because it has a few extra kilometres of range.

Would you be willing to expand on this? The reason I ask is that there are plenty of ex-Porsche (and ex-BMW) owners over at TMC and /r/teslamotors. Are they the minority, or are the brand loyalists the minority?

That talk is a spin on Nick Bostrom's Paperclip Maximizer. See: https://wiki.lesswrong.com/wiki/Paperclip_maximizer

Doesn't meet "similar cost" criterion, but check out Torqeedo: https://www.torqeedo.com/us/en-us

Yes -- this is what is commonly misunderstood about Martingale. What Martingale really does is change the probability distribution of outcomes to be heavily weighted toward winning a very small amount of money.

You can, for a given number of plays, use Martingale to make the odds of winning greater than the odds of losing. However what you can't do, is change the expected value of that set of plays. So what you've really done is created a situation where you have a high chance of winning a small amount of money, and a low chance of losing a lot of money.

Apple could pay off all of Tesla's debt with like 5% of its cash reserves. Tesla is highly ratioed, but that's a function of its own financials -- to a company like Apple, the debt isn't very scary.

8 seasonal tire swaps, a couple issues with the door handles, and a couple recalls.

This doesn't reflect my experience at all.

I've been to the Dedham and Watertown MA service centers about a dozen times in the last four years. I've never had to wait more than 2 minutes on the phone or at the counter. I have had a couple emails get lost, but after a bump or two I got the answers I needed.

Appointments do book out a few weeks, but scheduling is pretty easy (especially now that it's all online). The one time something urgent came up with my car, they took me without an appointment, and even put me in a rental car since they were out of loaners.

I've never had service anywhere near that good when I had a Toyota or a Subaru.

Appeal-to-authority arguments are always uncompelling, but they are especially uncompelling against Musk. Authorities said hydrogen fuel cells were the future. Authorities said EVs will never outperform gas cars. Authorities said batteries will always cost too much. Authorities said reusing rockets will never work.

With each of these breakthroughs, Musk presented a well-reasoned view that was highly contrarian against the authority consensus; and in each case, his view turned out to be not only correct, but so correct that it became the new authority consensus.

Maybe this time he is wrong and you are right. But if you are wondering why the market and the masses believe him, it's because he continues to provide reasonable explanations for what he's proposing, and he has a track record to back them up. If history predicts the future, then in a few years, we'll add "authorities said you needed LIDAR for self-driving" to the list above. This is already starting to play out in the SDC space, with Hotz of Comma.ai sharing Musk's views on vision, and Levandowski sharing his more generalized concern about LIDAR (the latter is more recent if you're not familiar):

> Levandowski contends that this “race” to deploy autonomous vehicles has yet to start in earnest largely due to shortcomings from “crutch technologies,” a descriptor he uses for hardware like LiDAR and HD maps. His position is that while these provide sensing and localization for the vehicle in the present moment, they have serious compromises and don’t produce the level of predictive ability required to commercially deploy autonomous vehicles.

https://techcrunch.com/2018/12/18/anthony-levandowski-pronto...

Karpathy was able to explain in very simple and understandable terms this week why Tesla's approach is advantageous. If the critics understand this domain so well, how come they can't provide a straightforward retort? If Feinman could do it with quantum physics, surely a machine learning expert can do it with neural networks. I would love to read/hear/watch such a retort if anybody is interested in presenting one.

> Tesla is [...] innovating faster

This is the point that so many people miss when arguing that an EV revolution is coming and others will catch Tesla. It's not that Tesla's lead is insurmountable; it's that Tesla's lead is growing, not shrinking, with each passing day.

No single feature or technology tells this story adequately but the compound effect of all of them does: it's 2019, and not a single manufacturer can produce a car that rivals a 2012 Model S.

> How will they manage if every part essentially needs to be custom made since they're constantly changing the parts?

That's not what happens in practice. Their revisions still obey interfaces wherever possible and follow the principles of modularity. E.g. when a v1 Model S door handle breaks, they replace it with the v3 version. When a v1 battery fails, they replace it with the v6 version.

Prediction: In ten years it's going to be very funny to look back at Tesla as the supposed bankruptcy risk and not Toyota.

We've heard variants on the parent-comments line of thinking ever since the Model S came out in 2012. Yet, fast forward to 2019, and the gap between Tesla and traditional automakers has only widened (to name a few axes: EV sales, EV margins, rate of software improvements/OTA updates, Supercharger network, battery production).

This is what should terrify big automakers: it's not that Tesla's gap is per se insurmountable; it's that the pace at which Tesla is improving and innovating is far greater than the pace at which any other automaker is doing it.

Most comparative analyses between Tesla and other auto companies suffer from a fallacy that relates to this: they compare the Tesla of today to the ___ of tomorrow. Perhaps some day a traditional auto manufacturer will offer an all-electric, self-driving car. But how long is it going to take them to get there? Not to announce something, or to design a concept car, but to actually build them and sell them at scale and with positive margins? And what will Tesla offer by the time they do?

My wager is that by the time Toyota offers a compelling all-electric car (by today's standards), the feature gap between a $x Tesla and a $x Toyota will be so great that the Toyota will no longer be compelling to the market.

Throw in lower margins as companies build their first EVs, the baggage of dealerships, a likely recession some time in the next decade, and it's not at all clear to me how traditional manufacturers like Toyota will survive the transition.

According to the vehicle purchase agreement and Tesla's lawyers, nothing on the order page is binding anyway (and ditto for Elon's claims). I agree they have changed the "promise" they are making to new purchasers on the page you've cited, but I don't see evidence that they are scaling back what they intend to deliver vis a vis FSD.

Now, all they need is the car...

I think you're confusing the next incremental step toward FSD with the end state of FSD. Tesla changes its marketing materials and web site copy all the time, but the Master Plan Pt 2 post (which outlines what you're alluding to) remains unchanged. Additionally, just three weeks ago, Elon was on the Ark Invest podcast claiming FSD will be safe enough for a human to sleep at the wheel by end of 2020[1]. I don't think Tesla's FSD plans have changed.

1: https://ark-invest.com/research/podcast/elon-musk-podcast

Added to the original comment, thanks.

The Sinclair method faces a lot of institutional incentive-related difficulties (generic drug, permanent treatment). It also has some aspects that are counterintuitive at first glance (e.g. it requires drinking alcohol, which creates skepticism when proposed by an alcoholic) but which are scientifically grounded. To anyone facing the problem of alcoholism: please do take the time to research it, read the studies, and form your own opinion. It’s really worth the time, and it’s not something you’re likely to hear about through traditional sources (yet) for the aforementioned reasons.

Show your sources. The studies that indicate it’s not effective are in comparison to a placebo when alcohol is NOT consumed with the drug. The Sinclair method is very specific about taking the drug with alcohol (and measuring its reduced usage over time).

To my knowledge liver damage has only been documented at doses far beyond what the Sinclair method directs.

Edit: source as requested below: https://academic.oup.com/alcalc/article/36/1/2/137995

She issued a correction on Twitter: only the employer-sponsored health insurance is contingent on signing the NDA, not the 60 days of salary.

> Because I’m not a labor attorney I got this part wrong the first twelve times I read it. (Legalese amirite?) If we don’t sign, they pull 60 days health insurance but not the actual payroll. Not complete horse shit but still horse shitty. /end correction

https://twitter.com/_KariedAway_/status/1087148173984903169

Definitely! I don't mean to downplay the inherent dangers of motorcycling. My point is simply that motorcyclists, as a whole, skew less cautious than drivers do. So e.g. a rider who never drinks and drives makes up more statistical safety ground than a driver who never drinks and drives.

I suspect that in the US, the lack of caution in bike culture is exacerbated by how relaxed our laws and regulations are (I've looked for data on this, but I haven't found great cross-country comparisons). We just don't impose on bikers in the same way we do on drivers. For example, we mandated ABS on all new cars nearly two decades ago, but we still don't require it on new bikes.

In fact, even in the US, I suspect riders have European laws to thank for the safety features on their bikes. It can't be a coincidence that, for example, Zero Motorcycles began installing ABS with their model year 2015 bikes -- just in time for the EU law that went into effect in 2016.

If you read the report, you'll find motorcyclists are more likely than car drivers to speed, drive drunk, and do both at the same time. And they frequently don't wear helmets.

There's no way to make motorcycling as safe as driving, but last time I did the math I found you can recover almost an entire order of magnitude just by obeying the law and wearing a full face helmet. And there's plenty more you can do from there -- take an MSF course, avoid congested areas during your first year on two wheels, and get a modern bike with ABS. Statistically speaking, the benefits of all these things are compounding.

There are at least three prior examples of Reveal publishing falsehoods about Tesla:

* Intentional underreporting of injuries.

* Disallowing the use of yellow tape at the factory.

* Disallowing audible warnings ("beeps") on forklifts.

The very "news organization" that is reporting this story has a history of publishing lies about Tesla. Google "Tesla Yellow Tape" -- that scandal was originally reported by Reveal, disproven within minutes of its release, and still has not been retracted.

In addition to what others have said, the concern about pixel-imperfect star tracking is somewhat moot, as we're talking about two different cameras. The effect on the imaging camera is very small.

There is the star tracker camera (widefield, fast), and the imaging camera (narrowfield, slow).

Star trackers use a fast widefield camera because it's easy to get a good signal:noise ratio (there is a lot of contrast between the stars and the background).

The imaging camera, on the other hand, generally takes much longer exposures (HST subjects are generally very dim, relative to stars). All those beautiful, nebulous HST photographs you see? Those have exposure times on the order of hours or days. In practice, being off by a pixel momentarily is not a big concern -- the amount of "bad" photons you collect during that time is very small.

OP is referencing the $35k/standard range model, which is expected to ship in 3-6 months. I can't figure out a way to direct link you, but look in the top right of the page at https://3.tesla.com/model3/design/<YOUR RN# HERE>#battery