A Quote by Andrew Ng
A lot of the progress in machine learning - and this is an unpopular opinion in academia - is driven by an increase in both computing power and data. An analogy is to building a space rocket: You need a huge rocket engine, and you need a lot of fuel.
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Anger is a fuel. You need fuel to launch a rocket. But if all you have is fuel without any complex internal mechanism directing it, you don't have a rocket. You have a bomb
If you think about the energy that a rocket engine has to put out and all the fuel and you're sitting on top of like a bomb. And on the Space Shuttle, that big orange tank is filled with liquid hydrogen and liquid oxygen, the white cell rocket boosters on the sides are filled with solid propellant. There's a lot of energy in all those chemicals there and you've got to control it in a way so it doesn't explode. So, there's a lot of plumbing, a lot of valving, a lot of control systems, and it's a very complicated thing. So, how do you bring the price of that down?
No rocket will reach the moon save by a miraculous discovery of an explosive far more energetic than any known. And even if the requisite fuel were produced, it would still have to be shown that the rocket machine would operate at 459 degrees below zero-the temperature of interplanetary space.
You need to be in the position where it is the cost of the fuel that actually matters and not the cost of building the rocket in the first place.
There isn't enough renewable fuel in the world to crack our growing addiction to foreign oil. We need to decrease miles driven and increase engine efficiency.
What patients want is not rocket science, which is really unfortunate because if it were rocket science, we would be doing it. We are great at rocket science. We love rocket science. What we’re not good at are the things that are so simple and basic that we overlook them.
I certainly remember building model rockets. It was fun to watch the rocket blast into the air, suspenseful to wonder if the parachute would open to bring the rocket safely back.
The expense of getting into space is the rocket launch, the rocket itself. Rocket's right now, commercial rockets cost probably somewhere between $50, or $120, or $150 million per launch. And those are all expendable. That is, you've got to buy a new rocket for each launch. So, that really is the critical part. If there was some kind of really, a revolutionary breakthrough and the price of rockets fell by an order of magnitude, I mean, just imagine what that would do as far as getting access to more ordinary people.
When I was growing up in Huntsville, Alabama, this is where the space and rocket center was. This is where all of the German rocket scientists came after war and started designing rockets for NASA, for the moon landing and all that.
Developing expendable rockets is always going to be painful and expensive. Throwing the whole rocket away on each attempt not only costs a lot, it also hampers figuring out just what went wrong because you don't get the rocket back for inspection.
For me, a rocket is only a means--only a method of reaching the depths of space--and not an end in itself... There's no doubt that it's very important to have rocket ships since they will help mankind to settle elsewhere in the universe. But what I'm working for is this resettling... The whole idea is to move away from the Earth to settlements in space.
With space travel, [it's] no different. You know, in 1990 I read the name Virgin Galactic Airways. Loved the name. And set out to try to find an engineer or rocket scientist in the world who could build a safe, reusable rocket that could take people to and from space and we could start a whole new era of commercial space travel.
I think there are a lot of industries that are collecting a lot of data and have not yet considered the implications of machine learning but will ultimately use it.
There's a lot of potential for machine learning all around the world. We're seeing it in academia, at other companies, in government.
Building advanced AI is like launching a rocket. The first challenge is to maximize acceleration, but once it starts picking up speed, you also need to focus on steering.
The concept of need is often looked upon rather unfavorably by economists, in contrast with the concept of demand. Both, however, have their own strengths and weaknesses. The need concept is criticized as being too mechanical, as denying the autonomy and individuality of the human person, and as implying that the human being is a machine which "needs" fuel in the shape of food, engine dope in the shape of medicine, and spare parts provided by the surgeon.
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