Just because others do it doesn't make it right. Just because organizations like Rockefeller's have purchased and corrupted our political system doesn't make it right. Just because similar organizations have purchased most of the media and broadcast the subtle propaganda that you have so faithfully reproduced doesn't make it right. Rockefeller illegally used his dominant market position to supress actual competition. That you so casually defend such reprehensible behavior speaks more to the effectiveness of the propaganda environment we live in than to the actual strength of any argument you are presenting. Your comment is basically an admission of your own slavery.

What are "robber barons" anyways? John D. Rockefeller, founder of Standard Oil is an excellent example of one. He gained an early lead in the oil industry. Then he used some rather extreme tactics to preserve his lead, none of which benefited consumers. For one, he bought up rail lines surrounding his competitors, and used this ownership to deny his competitors the ability to transport their oil. Those competitors responded by packing their oil in barrels which could then be loaded onto multiple means of conveyance (i.e. trucks). This is why oil is still measured in "barrels". Rockefeller responded by attempting to control the market on the compound that was used to seal the barrels from leaking. The government eventually responded by breaking up Standard Oil into many different companies.

The above doesn't sound like Space X under Elon Musk. Space X is the plucky newcomer disrupting the existing American launch contractor United Launch Alliance (ULA) and its cosy relationship with the US military. If anything, ULA, Lockheed Martin, and Boeing fall under the moniker of "Robber Baron". This writer sounds like a troll acting in the best interests of the decaying American launch industry.

I prefer to say that g is gravitational field strength in N/kg. It is equal to the acceleration of a free falling object, but I think it is clearer to think of it as the number of newtons of gravitational force one gets per kg in the field. Of course, 1N/kg is the same as 1m/s^2.

There are two approaches to radiation tolerant computing. One is to make the processors hardened to radiation. These processors are usually slower, and use an architecture with fewer knowledgable computer programmers. This seems to be the approach on Orion.

In contrast, the Space X Dragon Capsule uses multiple processors operating simultaneously to create a fault tolerant system. To quote:

An advantage of this is that the processors are far faster. There are also many more trained programmers available for these more current architectures. Such systems arguably have similar (or better?) radiation tolerance to the older hardened processors.

Read my post. Hydrogen as energy transmission is a dead end physics wise. Use the electrical grid and get 90%+ effiency, or use hydrogen and lose most of your energy. Electrolyzing water is, and always will be very inefficient. It will not, cannot reach the efficiency of the grid.

This is why I think electric vehicles have an advantage...you can put the charging station at your residence. All it needs is a wire. The infrastructure is already there, and can be expanded with relatively little expense. I can imagine charging stations everywhere one parks one's car. We all park our cars at some point, so we will all be able to charge our battery cars enough to make them usable, especially if the charging stations are high capacity.

In addition I think that in terms of space and expense, the potential power output of batteries is far larger than for fuel cells. I picture fuel cells as being finicky and complicated. If I am wrong, please correct me. However I have trouble imagining 800hp output (like the latest Tesla) from a fuel cell. My suspicion is that such a powerful fuel cell would be a Rube Goldberg machine.

Finally, and I think this is the real nail in the coffin for hydrogen as an energy source, is energy efficiency. Creating hydrogen from water, or from whatever other source you have takes a fairly large amount of energy. Let's say we take our hydrogen from water. How much of that input energy will actually make it to the fuel in terms of chemical potential energy? Some of the energy will be put into the O2 bond, which will not be transferred as fuel. Some (most) of the energy will be lost as thermal energy. Only a relatively small amount of the input energy will make it into the fuel. I would be surprised if it was even 20%, and I suspect it is less.

Compare this with gas turbine generators, that can have efficiencies well over 50%. So, you use your natural gas to generate electricity, in which you lose half of your energy already. Now you have a choice: you can use that electrical energy to electrolize water and lose 80% or more of that remaining energy. Or you can use the electrical grid to transfer the electricity directly to the car and lose only about 5% of the energy to the electrical grid.

The laws of thermodynamics are against the use of hydrogen is a fuel. Unless we can find a way of electrolyzing water that has an efficiency equivalent to the electrical grid (more than 90% - and such a process would violate the laws of thermodynamics), hydrogen as a fuel is an obvious dead end. If only the people who ran these companies knew a little bit of physics. I'll take a BSc in Physics any day over an MBA.

Here is a twitter discussion with Musk and Carmak that gives some reasons for using the fins. To quote:

My suspicion is that there will be a degree of unpredictability for this flight as they refine the control characteristics of these fins. Thus Musk was quoted as saying that the success probability was 50/50 for this landing.

This is a quote from Elon Musk on what he thinks about "process":

This just about nails it for me.

I forgot to mention...what I describe above is called learning by induction. Which is a form of probabilistic learning.

Perhaps I am not using the correct terminology. And I am not an expert...this isn't really my field. But I have seen neural network simulations which, for example recognize handwriting. You show the program many variations on the letter F, and the computer then learns to take symbols that look like the letter F and put them into that group. One can imagine that the brain is made up of many such processes. It certainly sounds like the way that I learned. See a spoon, see mommy using it to feed me, see mommy using it to feed herself. They are all different spoons, but they look similar and they seem to be used to move food from a bowl to a mouth. In a way it isn't that different than taking similar shapes and calling them a particular hand-written letter. It's just that we do this categorization at a myriad of levels on a myriad of objects and eventually of ideas themselves.

I suppose what I think might happen is that instead of building simulations of neural networks, that we will build actual neural networks using some form of electronic system. I don't know what that will look like exactly, but I suspect it is quite possible. After all, nature has already done it.

If we can make a human level brain, then we can make something much smarter as well.

There is the problem...I think that CPU's are the wrong tool. The problem needs to be re-framed. Perhaps we need synthetic neurons. Then we will need precisely one synthetic neuron to simulate a real one. I know...easier said than done. But we do know the basics of neuron function. Why can't we make a single electronic element that does something very similar?

Neurons can typically fire at a rate of 250Hz. There are about 100 billion neurons in a typical human brain. These neurons are networked in an extremely complicated and changeable parallel network. This network of neurons can be powered for reasonably long time with the energy contained in a bowl of oatmeal. Surely we will at some point be able to create a similar device, and one that doesn't require most of the world's computing power to run.

I suspect the breakthrough will come with a new computing paradigm, one that is based on massive parallelism. Perhaps it will consist of a silicon based device that mimics the network and function of neurons. I suspect it will be based on probabilistic computing, similar to how our own brains work. It will be taught rather than programmed. Perhaps there will be more states than merely 0 and 1.

I think that this is coming, because our brains are already doing it. And with incredible efficiency. Once we saw birds fly, and so we tried to do it ourselves. Eventually we figured it out. I think it will be the same with AI. We will copy nature, learn its principles, and then we will create our own version. And in doing so, I suspect our ideas of what intelligence is will fundamentally change.

There is a BBC documentary film maker named Adam Curtis who makes some fascinating and disturbing videos about society and control. He has access to the BBC film archives, and uses historical footage extensively. The assertions made are extensively documented and the interviews of powerful people are extremely interesting. I think that this video, The Engineering of Consent, is relevant to this discussion. It is one hour, and quite "stream of consciousness", but worth watching. It is the second episode in a series called The Century of the Self.

From the wikipedia summary: