It would be alarming, if it were true. Doctors pretty much always recommend improving diet for illnesses for which it is effective (like the ones mentioned -- heart disease, diabetes -- not for acute conditions, infections, etc....) But two big problems (not the only ones, no doubt) with a nutrition-based treatment plan are patient knowledge (knowing what to eat) and patient compliance (actually making the recommended dietary changes). This study attempts to improve those aspects by providing meals for patients. That's the big innovation here, not that better nutrition leads to better health outcomes.

Also, I'm not sure why you think there is some sort of dichotomy here. There is none, and can't be. Virtually everyone being treated with drugs also eats food. The real question is more how much each is emphasized in the patient's care.

Yeah, it's too bad they've stopped trying to improve them and are claiming they're ready for the road now. Oh wait, that's exactly the opposite of what's happening, as cited specifically in the article:

It's easy (also stupid and pointless) to say that if they never improve, they'll never be good enough, because none of them claim they're ready today and all are focused entirely on improving performance.

I'm aware of at least one company for which that seems to be true. As for the more than 50 other companies doing or preparing for road tests, it's likely that you're not listening to or not understanding their claims (for the ones that have even made any claims at all) or sourcing your expectations/beliefs from somewhere other than where the actual work is being done.

An odd non-sequitur.

I guess you have a weird definition of "android". Traditionally, it's just an anthropomorphic robot. The truth is, we don't know what stimulus would be necessary to cause a system to display characteristics of human-like consciousness. Logically, the necessary inputs would tend to vary based on the complexity and attributes of the system.

I expect that as soon as we have machines that can reliably pass a Turing test, we'll come up with new measures, hopefully well thought out ones, to get at that.

Obviously, we can't know that unless and until an artificial construct demonstrates measurable aspects of consciousness.

The opposite, actually. The idea that we can make something simple(ish) and somewhat open-ended or non-deterministic that can evolve through self organizing/emergent behavior depends on "nature" (broadly used here to include natural processes happening to and/or acting on an artificial construct) to do part of the work.

You seem to be making a few assertions here that are simply your beliefs, but using them as facts to support your conclusion.

• For instance, the notion that we can't replicate something that has evolved over millions or billions of years. (BTW, humans/pre-human ancestors only branched off from other hominid about 7.5 million years ago. The earliest estimates for life existing on Earth are about 3.8 billion years ago, so no, human consciousness was not evolving before single-celled organisms.) However, we have replicated bipedal locomotion in robots, despite that taking considerable time to evolve in our ancestors. So I'm not sure why you think mental processes cannot be replicated.
• You also claim that humans will never understand human consciousness, but only cite a philosophical bon mot or two "a thing cannot make an artifact as complex as itself" and "you must know more about reality than the thing you are creating" that have a satisfying sound to them, but no evidence that they are actual "laws of the universe".
• Here's another good one:"We perceive the internal states of others and react to those states by modifying our own behaviors.... The HMA will never be replicated in a machine for this reason." Except that robots and chatbots that observe and respond to human emotion already exist. And evidence suggests that they will be better at it than humans before long.

It seems to boil down to either "I can't conceive of how it is possible, so it must be impossible" or just "it's a really hard problem", neither of which is a compelling argument to me. There's another piece to it, also, that you may not have considered. You seem to be assuming that people, humans, need to fully understand consciousness and will then need to build it from scratch. However, you're overlooking the possibility that an advanced set of hardware and algorithms that forms a "thinking machine" of some type will develop consciousness on its own. Consider that evolution of organic entities takes a long time because many generations may be needed to fully develop the adaptive traits. Software is much more malleable. It can change in response to stimuli in real time and undergo hundreds of iterations of changes in less time than it takes a person to recharge as is required daily (sleep).

Machines might never achieve consciousness or emotion that is similar to humans, but it's way to early to declare it impossible.

Well, who's the sexist now? No surprise, it's still you: assuming my gender AND that of any partners I may have, AND trying to assign us roles in the relationship?

Back on a serious note, I think we both realize there is gender bias -- aside from any self-selection bias -- in lots of industries, including entertainment. And pretending there isn't or pretending we have to precisely quantify it before we can even acknowledge it only perpetuates it.

Not sure if you just didn't understand the article/summary, or you are just extrapolating what was actually said to "every industry, every hobby, and every interest" because that's easier whine about? What Cameron actually said is that in Hollywood in general, 14% of directors are female. And it's not like we don't know gender bias exists in the entertainment industry. Book publishing provides an easy example. A few years back, a female author submitted her novel to the same set of 50 literary agents under her own (clearly female) name, and under a male pseudonym. As a female, she got 2 manuscript requests. Under the male pseudonym, 17. For identical submissions, except for the name of the author. If your first inclination is to try to come up with a way that that doesn't show bias, maybe it's time to just admit that sexism is just fine with you? And 14% to 86% is a bit less, but similarly lopsided. Wouldn't it make more sense to ask why there is such a large split, instead of suggesting that there is no industry bias, and that women probably don't want to direct?

In what way is directing a film specific to male anatomy? It is obvious that using a urinal is, but I really don't get why you think standing up to urinate is analogous to directing a film?

Depending on where you are, they also include one-day or same day delivery (not even counting 2-4 hour delivery of selected products, plus grocery and restaurant delivery in places "Prime Now" has been rolled out). Plus all the other stuff --video, music, kindle books and magazines, etc... -- which, to be fair, may or may not have value for you.

And you can share (at least some benefits) of membership with family members, roommates, whatever. So you can split the cost. For people who use the benefits even only on a regular-ish basis, it's still a pretty good deal. Especially if you're splitting it 2 or 3 ways.

You're close, but more likely, they'll lay off two out of three (three out of five, if you're lucky) instead of just half.

I think you're both right, to some extent. There will be new types of jobs and perhaps new industries that either can't be done by machines, or that people would rather have (and pay a premium to have) humans do. But personally, I don't believe those will come near to matching the numbers of people who become unemployed, perhaps even unemployable, due to automation.

There are some hard-to-predict variables that confound discussions like this. For one, how fast is machine learning/AI/automation getting better? How soon jobs can be replaced depends on that. Will it be three years before we see significant impacts, or 5 or 10 or 15? Also, how fast will the adoption of new tech be? That depends on how costly the tech itself is, how much money it actually saves, how much retrofitting/redesigning is needed to incorporate it, and how good it is. I am sure that we will see companies that go out of business because they are ahead of the curve and try to deploy new tech before it's ready, as well as ones that wait too long and get out-competed by more automated businesses.

And if you can answer all those questions for AI/machine learning, for many jobs you will also have to answer them for robotics/sensors/physical environment components.

On top of those considerations, we can't really predict yet how automation might change business processes. There are certainly going to be things made obsolete by automation. There are also going to be things that are currently obsolete, but are still being done, that will be exposed by looking at whether a job/function/task can be automated. Very likely, there will be cases where one function or task prevents a job from being automated, resulting in that function or task being eliminated rather than holding on to human workers to do that bit. It won't always be possible, of course, but there will probably be a fair number of people surprised at losing their jobs because they thought it was "impossible" to get rid of some aspect of what they do.

How soon and how fast are the big questions, and that will of course vary by industry/job type. For something like self-driving cars, you would expect "how fast", i.e. rate of adoption, to be pretty fast once level 5 is reached since nearly 100% of any given driving job will likely be handled by the automation, and there are other advantages aside from the direct cost reduction of replacing the human labor (e.g. more than doubling the available operating time of vehicles in trucking, since human drivers have strict limits on hours of operation/service). Whereas if you have an automated system that can do 10 or 20% of a job, there is less incentive/advantage to adopt quickly.

That's true, but if they had decent backups at a minimum, they would be assured of getting all their data back. From what I've read, it is not clear that they did.

Wow, you are really struggling. Let me walk you through it. You tried to say that long commutes are a problem for wide adoption of EVs (which I will call "The Point") . They're not. I explained this in detail and laid out the numbers, refuting "The Point". But instead of substantively responding to that and staying on "The Point" you tried to raise a different argument, as if it had any bearing on what we were talking about (it doesn't).

And then? When I mention that your complete lack of substance to support "The Point" indicates that we've put "The Point" to bed (i.e. settled the matter), you act as if I were referring to your alternate argument. I don't know if that is just bad reading comprehension, or another attempt to incorporate extraneous matter into "The Point". Either way, I think you can do better.

By the way, we also settled your alternate argument that electrics are 4X the cost of gas cars.

Two things to say on the above:
1. 40 is not 4X of 15, so you're already wrong using your own numbers.
2. MSRPs or GTFO