sebastian thrun

sebastian thrun bw

beginnings of udacity, ted meet up with khan thinking et al 2012:

http://www.wired.com/wiredscience/2012/03/ff_aiclass/all/

update in thinking 2013 – udacity blog:

udacity blog

 

find/follow him/his work:

http://en.wikipedia.org/wiki/Sebastian_Thrun

https://twitter.com/SebastianThrun

sebastians homepage

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udacity site:

udacity site

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previous note:

tuesday, january 31, 2012

sebastian thrun

via @uncollegeprof thrun drops out of stanford – udacityvideo
googles lab for wildest dreams
vie sagt mann. love it.
160000 students for ai via stanfordinstead of lecturing we would quiz
principal way of engaging.. the student has to thinkthey prefer him on video (30000 a year) – because they can watch in lurk mode
volunteer – 2000 translators

these are not your typical stanford students

let them fail and i’d come to their rescue.
there was no purpose of weeding, no certificate to be earned
we don’t set up kids for success but for failure
we don’t help our students become smart
grades are the failure of the ed system
rather than grading, get everyone to a+
?
today, when kids get a c, we don’t take the time to bring them up to an a
this medium is giving us the opportunity to do that

in response to comments – how can you teach with 160000

change the world with ed, free for world, core of a society

stop empowering the prof’s and start empowering the students

in 7 weeks – anyone could build their own google. search engine..

part of this.. is getting rid of compulsion… esp in k-12.. no?

thank you sebastian, and dale and sal, and …

love this via Sebastian:

the real question is not, what’s going to happen to the uni, but what’s going to happen to the people…

his company 50% female.
classes 10% female.
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wednesday, december 19, 2012

moocs & change

George Siemens (@gsiemens)
12/18/12 8:55 PM
“there is time and room..to invent another model [mooc], a responsible and relevant one for the challenges of our time” globalhighered.wordpress.com/2012/12/18/the…

Education brands are investing in digital platforms for maintaining the traditional way of learning for the benefit of the same big ones, this. “If we want things to stay as they are, things will have to change” as Lampedusa told us in his famous novel The Leopard. This is how digital technology is perversely used and how we miss their powerful enticement for innovation in education processes.

our myth.. if we’re changing … we’re good.
if it’s shinier … we’re good.
let’s not moot mooc..
interesting where minds are going (perhaps where actuality is going) with moocs.
interesting the things talked about as lacking in this article are the very essence of their beginnings several years ago..
no?

Back to Cormier, the guy who coined the term “MOOC” back in 2008, long before Stanford’s massively-hyped online artificial intelligence class. That’s an important piece of education technology history that’s been overlooked a lot this year as Sebastian Thrun and his Stanford colleagues have received most of the credit in the mainstream press for “inventing” the MOOC.
But MOOCs have a longer history, dating back to some of the open online learning experiments conducted by Cormier, George Siemens, Stephen Downes, Alec Couros, David Wiley and others. Downes and Siemens’ 2008 class “Connectivism and Connective Knowledge,”for example, was offered to some 20-odd tuition-paying students at the University of Manitoba, along with over 2300 who signed up for a free and open version online.
In July, Downes made the distinction between “cMOOCs,” the types he has offered, and “xMOOCs,” those offered by Udacity, Coursera, edX and others. The terminology is very useful to help distinguish between the connectivist origins of MOOCs (and the connectivist principles and practices of open learning and online networks) and the MOOCs that have made headlines this year (with their emphasis on lecture videos and multiple choice tests). While cMOOCs are strongly connectivist and Canadian, xMOOCs, as Mike Caulfield contends, exist “at the intersection of Wall Street and Silicon Valley.”

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sebastian thrun article

“To all those people who declared our experiment a failure, you have to understand how innovation works,” he wrote on his blog. “Few ideas work on the first try. Iteration is key to innovation. We are seeing significant improvement in learning outcomes and student engagement. ”

Some draw an analogy to mobile phones, which took several generations to progress from clunky and unreliable to indispensable.

Mr. Thrun stressed that results from the second round of the San Jose experiment over the summer were much improved, with the online algebra and statistics students doing better than their on-campus counterparts. Comparisons are murky, though, since the summer classes were open to all, and half the students already had degrees.

spot on to iterations..

imagine an iteration where there was no agenda.. ie: algebra/statistics as required..

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jan 2016
on udacity guaranteeing job or money back.. thrun excitedly announcing on fb.. and Audrey sharing fine print (ie: working for their partners); and that sounding like udacity as internship; and then wondering why paid employment is our answer.. ie: graeber jobless law; and how our everyday would change if we weren’t seeking a degree or a paid job or..  perhaps we’d see a nother way as best for humanity .. for (blank)’s sake.

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ted 2017

[https://www.ted.com/talks/sebastian_thrun_and_chris_anderson_the_new_generation_of_computers_is_programming_itself]

3 min – you don’t have to think anymore you just give them data..t

huge.. ie: what if we’re giving them the wrong data.. not.. ie: statistically wrong.. but conceptually wrong.. what if the data we need the tech (as it could be) to be looking at is  ie: self-talk as data.. perhaps tech use could be more about data from curiosity than from driving.. more about keep healthy sans cancer.. than how to cure/medicate cancer..

6 min – if you give enough data.. it finds its own rules

14 min – what machine learning is .. is re writing the rules

15 min – machine learning has been thriving because of: massive amounts of specialized data

17 min – we’ve become dermatologists.. lawyers.. doing repetitive things..

perhaps less about using ai to make those things more efficient.. perhaps more about.. noticing things then.. that could become irrelevant.. ie: lawyers.. dermatologists (just because those are the things you ie’d)

19 min – i think 90% of my day as ceo is repetitive.. i don’t like it.. i’m burning for another way.. i think we’re all creative..

ie: on de slaving us from farming and factory work

perhaps those were also irrelevant to humanity.. health earth.. ie: affluence w/o abundance.. and the downhill starting when agri began..

20 min – my firm belief as an ai person.. i haven’t seen any real progress on creativity..

so why not have tech work on our creativity/curiosities.. perhaps the repetitive ness doesn’t even need to be done by computers.. perhaps we’re not only wasting people.. but wasting tech..

21 min – ai is really a tech that helps us do repetitive things..t

so.. let’s let that repetitive thing be.. equity (everyone getting a go everyday)  ..like groundhog day ness.. via 2 convos

ie: hlb via 2 convos that io dance.. as the day..[aka: not part\ial.. for (blank)’s sake…]..  a nother way

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