- Earl was desperate.
EARL J. WAGNER: We'll be talking about a recent innovation of an action course online.
EARL J. WAGNER: Sure, so kind of seeing some of the same approaches in terms of thinking of engineering in terms of buildings
EARL J. WAGNER: That's helpful to actually get to the core of this approach.
EARL J. WAGNER: And so going back to kind of your own history, that's something that you found so transformative.
EARL J. WAGNER: Yeah, it sounds really powerful, that what had been such a struggle for you, like the troubleshooting, and for you
EARL J. WAGNER: Noticing how the way that you presented it evolved as you were kind of going through year by year.
EARL J. WAGNER: Yeah.
EARL J. WAGNER: Yeah, how did you-- maybe how did you know-- what were the first indicators that it was actually starting to take off?
EARL J. WAGNER: start where we talk about actually validating the idea, putting it out there, putting the idea out there, seeing if actually it grabs people.
EARL J. WAGNER: Yeah, say more about that, because that's definitely something that-- you were talking about sort of the older approach
EARL J. WAGNER: And along the way you've been translating the material into different languages.
EARL J. WAGNER: Getting the strong word of mouth.
EARL J. WAGNER: So it also sounds a lot like the open source world where software is developed in a collaborative way internationally
EARL J. WAGNER: That sounds kind of counterintuitive.
EARL J. WAGNER: Sure, it is understandable.
EARL J. WAGNER: So you mentioned the course starting off, I think, around 2010, 2011, with around 500, and then actually increasing about a thousand per year,
EARL J. WAGNER: --have taken the course.
EARL J. WAGNER: Yeah, the kind of word of mouth continues to accelerate.
EARL J. WAGNER: I also do want to open it up for questions from the audience based on-- let's see, so we had a chance to talk about your experience, how you first
EARL J. WAGNER: Interesting, just that it becomes this kind of lifelong kind of learning and application.
EARL J. WAGNER: Why isn't it something that somebody could just take a class or in a day?
EARL J. WAGNER: And then kind of shifting from-- like actually maybe learning new habits or new ways of being.
EARL J. WAGNER: So also coming back to the theme around teaching compassion at scale, I'm curious if you have for somebody else engaging in--
EARL J. WAGNER: Just starting off with something that has impact, that works, and then building.
EARL J. WAGNER: It's continuously iterating and improvement.
EARL J. WAGNER: So I'll go ahead and repeat the question for the recording, that for somebody who's just learning this, it seems so simple.
EARL J. WAGNER: What do you see as the differences in terms of supporting and fostering community for this kind of work, like in person,
EARL J. WAGNER: So just for both of those, you mentioned doing an exercise and sharing their results.
EARL J. WAGNER: Wow, yeah.
EARL J. WAGNER: Yes, I'll repeat the question.
EARL J. WAGNER: Other questions?
EARL J. WAGNER: Great.
EARL J. WAGNER: I want to follow up on that, because you mentioned it can be this long term learning process.
EARL J. WAGNER: Pretty heavy, yeah.
Earl Jones is a Montrealer who scammed the Anglo-Saxon upper crust community with his baby face and his participation
Earl Sweatshirt improvises a musical-- musical-- he basically does a live music video.
Earl on, when you're describing this course.
Earl , Tom Mela from Rage Against the Machine, The Hives, and six or seven other artists.
Earlier this year, I felt really burnt out from sitting at my computer all day long, testing all these new AI models.
Early AI looks weird and creepy?
Early Mesoamericans improved the rubber slightly by mixing the latex with juice from the tropical morning-glory, a local flower.
early on in his paper to make the distinction that anybody can become indoctrinated. It doesn't matter whether you are a Christian or an atheist or leftwing or right-wing or a meat eater or a
early. You want to give them as much of a heads up and enough time to be able to think process the way that you might be
early years in these fields.
Early in the nation, the most powerful states were slaveholding states. Virginia was by far the most important state. Four of the first five
early deep learning revolution to we're now going to start thinking of it as an AI factory? What does NVIDIA do? It produces AI, let's build a factory that makes AI.
early 20th century with Zermelo's idea. I mean, the history is quite fascinating because Zermelo in 1904 offered a proof
early interpreters, mens, had this idea, which can be seen as a crude justification for rebellion or for a kind of democracy to say that
Early on in this escalated war of '22?