jeremy howard

jeremy howard

intro’d to Jeremy here:

The wonderful and terrifying implications of computers that can learn

by letting computer do ginormous amount of trials… can learn ie: chess

computers can learn to do things that we can’t do ourselves (or have forgotten/lost how to do)

deep learning: an algorithm inspired by how the human brain works.. an algorithm that has no theoretical limitations on what it can do… the more data you give it and the more computation time you give it.. the better it gets..

computers can listen and understand.. ie: learn to translate to chiness

also learn to see.. ie: learn signs, image, … learned by looking over and over at cats, people..

much like the way humans learn.. not by what they are told what they see.. but learning for themselves what these things are

now computer can read images… read chinese

put in search words and gives back images… seems like what we’ve had.. but image search up to just a few months ago – has always been via text search.. of a page.. where image was

computers can read… understand what you tell them..

and write (still not quite at human performance but close)

nice thing is now human and computer can work together… freeing up people, ie: doctors to do things they were meant to do

14 min – use in app/chip – finding similarities for match ups…

this is going to be a change we’ve never experienced before.. your previous understanding of what’s possible is different

computers right now can do the things that most humans spend most of their time to get paid to do… how we’re going to adjust social/economic structure

short.. how to model another way

– –

footnotes from talk:



I hate the word “big data”, because I think it’s not about the size of the data, but what you do with it.

I believe that nearly everyone is underestimating the potential of deep learning.

deep learning


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Jeremy Howard (born 1973) is an Australian data scientist and entrepreneur. He is the CEO and Founder atEnlitic, an advanced machine learning company in San Francisco, California. Previously, Howard was the President and Chief Scientist at Kaggle, a community and competition platform of over 200,000 data scientists. Howard is the youngest faculty member at Singularity University, where he teaches data science. He is also a Young Global Leader with the World Economic Forum, and spoke at the World Economic Forum Annual Meeting 2014 on “Jobs For The Machines.”[4] Howard advised Khosla Ventures as their Data Strategist, identifying the biggest opportunities for investing in data driven startups and mentoring their portfolio companies to build data-driven businesses. Howard was the founding CEO of two successful Australian startups, FastMail and Optimal Decisions Group. Before that, he spent eight years in management consulting, at McKinsey & Company and AT Kearney.

He projects that the application of deep learning will have the most significant impact on medicine out of any technology during this decade by effectively aggregating data. 

unless dl has an impact on rather – human health.. so that we need less medicine..  no? by effectively aggregating data (self-talk)

Howard developed a new system for learning Chinese, which he used to develop usable Chinese language skills in just one year. The method he uses is called Spaced Repetitive Learning, in which a person prompts himself to remember information just prior to forgetting it.

groundhog day ness

echo chamber ness ie: Deb Roy style – (14 min above ted et al)