From philosophy to POMDPs to reinforcement learning & hierarchical planning to the publishing model in academia, I really enjoyed this conversation with Leslie.
Sorry Lex, I admit to having misspelled your name when telling people about your channel -- but I won't do it again ;-) Thanks for your efforts and interviews!
Being someone whose work environment is not alongside other programmers where I have to either use lay terminology or keep to myself with descriptions of what I do, it's intriguing and almost refreshing to hear conversations on this podcast constantly referring to everyday life in terms of functions, problem spaces, sets, and the like. really enjoying it.
Begins with a GEB mention, eloquently articulates issues I have been trying to categorise for years, is pro open access, isn't getting distracted by ill-formed big ideas... anything this person has ever said or written is now priority reading for me. Genius.
Leslie is one those amazing guests who do not proffer opinions on supposedly deep questions, but are very lucid in what they do say. I really liked her!
3rd yr undergrad student. Learning ai on his own. I could understand the problem statements for deep learning and computer vision(couldn't solve them , obviously) , but not so much in reinforcement learning. This really helped. Reinforcement learning isn't just a computation problem. It's a merging of the disciplines mentioned under symbolic systems . One can specialize in one or more of thosw fields, but to make things work, all those perspectives are needed. Thanks for this.
I think the output we want from a "perception" system is a cost or a credit of the current state of the world. Just like we do in inverse reinforcement learning or target propagation for the credit assignement problem. Awesome video btw !
Any person who doesn't value competition based on 'personal feelings' loses a lot of credibility. Its better than resenting it for ideological reasons, but its our most general method, and possibly most fundamental method of finding truth. Dismiss it at your peril.
From philosophy to POMDPs to reinforcement learning & hierarchical planning to the publishing model in academia, I really enjoyed this conversation with Leslie.
Sorry Lex, I admit to having misspelled your name when telling people about your channel -- but I won't do it again ;-) Thanks for your efforts and interviews!
Leslie is so eloquent, I think this is my favorite interview from the podcast
Thank you so much for this, Lex. Much love...
Like this lady. A free thinker who doesn't care for competition and care for investing into hard problems
I was just following Leslie's MIT OCW course and thinking what a great teacher she is. I then find this! So excited to listen now.
Same here
Thanks for this podcast
Being someone whose work environment is not alongside other programmers where I have to either use lay terminology or keep to myself with descriptions of what I do, it's intriguing and almost refreshing to hear conversations on this podcast constantly referring to everyday life in terms of functions, problem spaces, sets, and the like.
really enjoying it.
Right?!
It's literally a different language and I perfer it.
Begins with a GEB mention, eloquently articulates issues I have been trying to categorise for years, is pro open access, isn't getting distracted by ill-formed big ideas... anything this person has ever said or written is now priority reading for me. Genius.
What a great conversation.
Great conversation!
Wow Leslie is smart as heck!
Leslie is one those amazing guests who do not proffer opinions on supposedly deep questions, but are very lucid in what they do say. I really liked her!
Great channel thank you
Mind-opening
3rd yr undergrad student. Learning ai on his own. I could understand the problem statements for deep learning and computer vision(couldn't solve them , obviously) , but not so much in reinforcement learning. This really helped. Reinforcement learning isn't just a computation problem. It's a merging of the disciplines mentioned under symbolic systems . One can specialize in one or more of thosw fields, but to make things work, all those perspectives are needed. Thanks for this.
wow!!...very knowledgeable...
I think the output we want from a "perception" system is a cost or a credit of the current state of the world. Just like we do in inverse reinforcement learning or target propagation for the credit assignement problem. Awesome video btw !
Rock out! Nice love it !
You know Listening to her made me think that humans are amazing !! really
@lex can you please add the outline back for videos?
interesting talk
It will take a surprising amount of time to walk through Kuala Lumpur airport
How to create your own deep learning library?
She's great. I hold almost exactly the same opinions, but I am much worse at articulating them.
Glad to see a few women in this field. 😍
Liked her AI perspective.
Who is the author mentioned at 0:45?
en.wikipedia.org/wiki/G%C3%B6del,_Escher,_Bach
I really like the way she.....Talks?
It would be great to see Jeff Hawkins on Your podcast.
Feels like listening to AMSR
What did she read that makes her interested in computer science?
"paper is not required for prestige, as it turns out." sums up todays colleges/universities.
She sounds, and kind of looks like Judith Butler :D
Any person who doesn't value competition based on 'personal feelings' loses a lot of credibility. Its better than resenting it for ideological reasons, but its our most general method, and possibly most fundamental method of finding truth. Dismiss it at your peril.
Here @ 2278; views..... ...... ......
Third
Anyone find the intro just a bit creepy?