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Michael I. Jordan

Published podcast speaker

Claims
14
Episodes
1
Shows
1
Named items
0

Claim ledger

What Michael said.

14 transcript-backed records

01 / belief

You know, they'll just burn a lot of money and, you know, cause some headaches. And then they'll also create things like search engines and and I think a lot of the companies are also really focused on creating value.

“You know, they'll just burn a lot of money and, you know, cause some headaches. And then they'll also create things like search engines and and I think a lot of the companies are also really focused on creating value.”
Publisher
Machine Learning Street Talk

02 / belief

I think eventually we'll all kind of merge, but along the way, just doing something so disruptive with all of these metaphors that's not good social science or not good mathematics, It's just metaphors.

“I think eventually we'll all kind of merge, but along the way, just doing something so disruptive with all of these metaphors that's not good social science or not good mathematics, It's just metaphors.”
Publisher
Machine Learning Street Talk

04 / uncertainty

I don't know who's got more money than who wants to bid more than others but I have this mechanism called an auction that reveals their value.

“I don't know who's got more money than who wants to bid more than others but I have this mechanism called an auction that reveals their value.”
Publisher
Machine Learning Street Talk

05 / evaluation

No one's going to want that. They're going to want, well, here's 50 people that are pretty much like you according to the embedding we're using in this big network.

“No one's going to want that. They're going to want, well, here's 50 people that are pretty much like you according to the embedding we're using in this big network.”
Publisher
Machine Learning Street Talk

06 / evaluation

Well, what's happening there is that there's probably not many examples in the training set of proteins with quantum fluctuation because it's not been that studied in the past and it's hard to crystallize.

“Well, what's happening there is that there's probably not many examples in the training set of proteins with quantum fluctuation because it's not been that studied in the past and it's hard to crystallize.”
Publisher
Machine Learning Street Talk

07 / preference

It'll just solve problems for us, and then we're we'll be happy. And it it you know, I got away from Silicon Valley partly because that's just the way that people talk and I got tired of it.

“It'll just solve problems for us, and then we're we'll be happy. And it it you know, I got away from Silicon Valley partly because that's just the way that people talk and I got tired of it.”
Publisher
Machine Learning Street Talk

08 / recommendation

We've got to make that market a little bit more valid and we could actually have that when someone's watching things, they can have a some sort of economic connection to the person who made it and then there can be incentives flowing that this person now incentivized to make more because here's my audience.

“We've got to make that market a little bit more valid and we could actually have that when someone's watching things, they can have a some sort of economic connection to the person who made it and then there can be incentives flowing that this person now incentivized to make more because here's my audience.”
Publisher
Machine Learning Street Talk

10 / evaluation

Markets mitigate uncertainty. And they they don't do it because someone designed an optimal experiment design or ran or did some multi armed bandit, not directly.

“Markets mitigate uncertainty. And they they don't do it because someone designed an optimal experiment design or ran or did some multi armed bandit, not directly.”
Publisher
Machine Learning Street Talk

11 / uncertainty

If you put a lot of people keep saying, well, we got to put logic back in or symbols because that came from the that came from our previous kind of view of what humans are doing. And probably humans are capable of doing some logical reasoning and probably have some symbols, whether they're kind of built in some complicated network or they're reified somehow, I don't know.

“If you put a lot of people keep saying, well, we got to put logic back in or symbols because that came from the that came from our previous kind of view of what humans are doing. And probably humans are capable of doing some logical reasoning and probably have some symbols, whether they're kind of built in some complicated network or they're reified somehow, I don't know.”
Publisher
Machine Learning Street Talk

12 / preference

We put all that together almost seamlessly. And then we do this in a social context where if I don't know how to get from here to the other side of town, I will ask someone who looks Danish.

“We put all that together almost seamlessly. And then we do this in a social context where if I don't know how to get from here to the other side of town, I will ask someone who looks Danish.”
Publisher
Machine Learning Street Talk

13 / evaluation

Alright? So, you know, Google doesn't need this because they created this artificial advertising market, which we could talk more about, that kind of super powered all this nonsense.

“Alright? So, you know, Google doesn't need this because they created this artificial advertising market, which we could talk more about, that kind of super powered all this nonsense.”
Publisher
Machine Learning Street Talk

14 / evaluation

So the current generation is just way too you know, there's not much thought going on, not much intellectual stuff. It's just, yeah, it's possible to build it, it's possible to steal the data from wherever you want to because that's what the Internet allowed to happen and not return any value to the person who originated the data.

“So the current generation is just way too you know, there's not much thought going on, not much intellectual stuff. It's just, yeah, it's possible to build it, it's possible to steal the data from wherever you want to because that's what the Internet allowed to happen and not return any value to the person who originated the data.”
Publisher
Machine Learning Street Talk
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