Explore Quotes on Learning

We have a good sense of the pulse of the industry. We know what's going on out there. We know that deep learning adoption is broad. It's going into production at scale.

I wasn't a dancer learning to play Baby Houseman. I was Baby Houseman learning to play a dancer. I was someone who'd never done any Latin dance. I'd taken jazz classes and ballet growing up in New York, so I had dance in me, and I knew I loved it, but I'd never done a dance audition.

For me, college was a big learning experience on and off the court, just growing as a person, becoming more mature.

Yes, there will be challenges, and things will blow up in your face, but learning experiences are different from wasting your life pushing a boulder up a hill.

It would be great to have every engineer have at least some amount of knowledge of machine learning.

Deep learning is a really powerful metaphor for learning about the world.

I am concerned in general about carbon emissions and machine learning.

Machine learning is a new way of creating problem solving.

Definitely there's growing use of machine learning across Google products, both data-center-based services, but also much more of our stuff is running on device on the phone.

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.

I think one of the things about reinforcement learning is that it tends to require exploration. So using it in the context of physical systems is somewhat hard.

Supervised learning works so well when you have the right data set, but ultimately unsupervised learning is going to be a really important component in building really intelligent systems - if you look at how humans learn, it's almost entirely unsupervised.

It's pretty clear that machine learning is going to a big part of science and engineering.

If you only have 10 examples of something, it's going to be hard to make deep learning work. If you have 100,000 things you care about, records or whatever, that's the kind of scale where you should really start thinking about these kinds of techniques.

The idea behind reinforcement learning is you don't necessarily know the actions you might take, so you explore the sequence of actions you should take by taking one that you think is a good idea and then observing how the world reacts. Like in a board game where you can react to how your opponent plays.

Reinforcement learning is the idea of being able to assign credit or blame to all the actions you took along the way while you were getting that reward signal.

Intelligence is what you use when you don't know what to do: when neither innateness nor learning has prepared you for the particular situation.

Public education must be viewed from the lens of providing each child with the learning environment that best meets his or her needs. If we can send a low-income child to a parochial school, knowing that his odds of attending college will increase as a result, then that should be our mission.

Of course, learning is strengthened and solidified when it occurs in a safe, secure and normal environment.

To me an influencer must embody 2 critical skills, continuous learning and storytelling. Accenture enabled me to accelerate my learning about exponential technologies and how they were impacting businesses, the economy and the world.