A Quote by Jeff Dean

Previously, we might use machine learning in a few sub-components of a system. Now we actually use machine learning to replace entire sets of systems, rather than trying to make a better machine learning model for each of the pieces.
There's a lot of work in machine learning systems that is not actually machine learning.
And initially, a lot of companies avoid trying to make a really radical new kind of title for a new system, because that would involve learning a new machine and learning how to make the new title at the same time.
We are going to completely change what it means to do advanced analytics with our data solutions. We have machine-learning stuff that is about really bringing advanced analytics and statistical machine learning into data-science departments everywhere.
Nature is a self-made machine, more perfectly automated than any automated machine. To create something in the image of nature is to create a machine, and it was by learning the inner working of nature that man became a builder of machines.
Doctors can be replaced by software – 80% of them can. I’d much rather have a good machine learning system diagnose my disease than the median or average doctor.
Transportation, with self-driving vehicles, is going to be a big use of machine learning.
Deep learning is a subfield of machine learning, which is a vibrant research area in artificial intelligence, or AI.
You need to use data science and machine learning to get the ground truth of what's happening inside of a company.
When you're young you want to show people what you can do, no matter what the cost. Whereas when you're older, and you realise that maybe a drum machine is better than you playing, then use the drum machine.
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.
... regard this body as a machine which, having been made by the hand of God, is incomparably better ordered than any machine that can be devised by man, and contains in itself movements more wonderful than those in any machine. ... it is for all practical purposes impossible for a machine to have enough organs to make it act in all the contingencies of life in the way in which our reason makes us act.
I'd like to make a fundamental impact on one of the most exciting, intelligent questions of all time. Can we use software and hardware to build intelligence into a machine? Can that machine help us solve cancer? Can that machine help us solve climate change?
If all individuals were conditioned to machine efficiency in the performance of their duties there would have to be at least one person outside the machine to give the necessary orders; if the machine absorbed or eliminated all those outside the machine, the machine will slow down and stop forever.
Who is all-powerful in the world? Who is most dreadful in the world? The machine. Who is most fair, most wealthy, and all-wise? The machine. What is the earth? A machine. What is the sky? A machine. What is man? A machine. A machine.
Genomics, Artificial Intelligence, and Deep Machine learning technologies are helping practitioners deliver better diagnosis and actually freeing up time for patient interaction.
The nice thing about the violin repertoire is that it's small enough that you can plan on learning everything at some point - whereas the piano repertoire is so enormous it wouldn't be possible unless you're a learning machine.
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