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  • we're talking about in the specifically even in that extended that intelligence you're talking about government.

    我們說的是在具體的 甚至在擴展的情報 你說的是政府。

  • You're talking about private industry, academia.


  • Where should the center of that research live?


  • If there is a center, it's a good question.


  • I think that M.


  • I t.

    I t.

  • Would argue.


  • It should be.


  • And I think it's this.


  • This round is quite shocking, I think, to the academics, because most of the money and the power of the core computer sciences and big companies uneven, open AI that some of our friends made that was a nonprofit and not inside an economic institution.


  • And I think it's sort of surprising Historically would have probably been a group of academics with the government, so this is a new thing.

    我認為這是一種令人驚訝的 歷史上可能會有一群學者與政府, 所以這是一個新的東西。

  • But I feel like as we start to emerge out of just the computer science mode to how does this affect society, for instance, to stake one of the areas that were really interested criminal justice, bail and parole?


  • That's probably much better to have a statistical AI supporting the the judge, but then it's not just about whether it's more efficient.


  • You don't want to be judged by machine, right, so these as we start to move out.


  • I think it will be interesting to see who gets involved.


  • I think as you start to get into the social sciences and the law and the philosophy that becomes more in government in academia.


  • But it is curious, and I think that just way can't compete.


  • We academia can't compete from the These guys are getting paid millions of dollars at post stock levels.


  • They've got a tremendous amount of resource is.


  • So I think we have to kind of assume now that But now the military are talking about funding a I so there may be another player that has a lot of money, but right now, most of the $1,000,000,000 labs all of them are really Look, I mean way No, the guys who are funding him and talkto Larry or others, uh, their general attitude, understandably, is the last thing we want is a bunch of bureaucrats, and you know that are slowing us down here as we chase uh, with unicorn.


  • At the heart of the problem that we've seen is that our general commitment is a society to basic research has diminished.


  • Our confidence in collective action has been chipped away, partly because of ideology and rhetoric.


  • And so, if the notion is if it's government, it's bad.


  • And that's something that I do think needs to be reversed.


  • Now that requires government to be more nimble, faster, quicker, smarter.


  • It's hard in a big democracy with a lot of diverse views, sometimes to get it moving fast enough in the direction that something like a eyes moving.


  • It's moving so rapidly that sometimes governments always playing catch up.


  • But you that the analogy that we still use 50 years later when it comes toe a great technological achievement is a moon shot.


  • And, uh, somebody reminded me, maybe better.


  • I want you that the space program was 1/2 a percent of GDP, and that doesn't sound like a lot 0.5% of GDP.


  • But in today's dollars that be $80 billion that we would be spending annually on a I and right now we're spending less than a 1,000,000,000.


  • That undoubtedly will accelerate.


  • But part of what we're gonna have toe understand is that if we want the values of a diverse community represented in these breakthrough technologies, then government funding has to be a part of it.


  • If government is not part of financing it, then understandably, those who, uh, pay the piper calls the tune.


  • And all the issues that Joy's raised about the values embedded in these technologies end up being potentially lost, or at least not properly debated.


  • You bring up a really interesting tension there that Joey you've written about that idea of innovation happening on the margins or at the edges, and then with space program and NASA really essentially governed.


  • How does that relationship change this this kind of development and thinking about where the transmission of those ideas can happen?


  • Well, I want to emphasize that the way we now think about crowd wisdom essentially on a bunch of experiments everywhere.


  • Uh, I think that can accelerate rather than impede progress as long as everybody's linked together with a sense of common purpose and responsibility and accountability, just to give a very concrete example.


  • Part of our project and precision medicine is together big enough database of human genomes from a diverse enough set of Americans, all kinds of racial types, ethnic types, body types, you name it gender that instead of financing medical research, where way give the money to Stanford, Harvard or some other school, and they've got their samples.


  • They're hoarding them and they're working on it.


  • It's a very linear process, you know, now have this entire database that everybody has access to on the potential to short circuit.

    這是一個非常線性的過程,你知道, 現在有這個整個數據庫 每個人都可以訪問 在潛在的短路。

  • The research process before you've got promising candidates for treatment could be hugely accelerated because people aren't all holding on to their stuff.


  • And that's the power of the Internet.


  • That's the power of connectivity and the networked world that we live in.


  • What I've tried to emphasize, though, is is that just because the government is financing it and helping to collect the data, it doesn't mean that we hoard it or only the military as a It's got to be a top down approach.

    我一直試圖強調,雖然, 是,只是因為政府是資助它 並幫助收集數據, 這並不意味著我們囤積它 或只有軍隊作為一個, 它必須是一個自上而下的方法。

  • But there does have to be some common set of values a common architecture to make sure that the research is shared by people, that it's not monetized by one group rather than another on.


  • There has to be some core principles that we all agree to and nets, I think, on appropriate role that some group like and I h, for example, complaint and I think that if you look at the moon shot, a lot of the value were the tools that were created in order to do that or if he will get CERN.


  • They've got some esoteric physics problem, but they invent the Web while they're at it.


  • And so I think these mega projects bring together an interdisciplinary group to solve a problem.


  • And so that's really interesting.


  • And I think one of the problems with standard peer reviewed government funding is it goes out in this kind of hierarchical pattern that's very politically correct and very rigorous.


  • But it doesn't really get these big ideas going.


  • And I would say, The other thing that you have that you're doing well is the open data initiative, right?


  • So when you're talking about A I, you need data.

    所以當你在談論A I時,你需要數據。

  • The government has data, and I helped start a nonprofit in Japan after Fukushima to get citizens to collect data on radiation measures.


  • We have 53 million of them.


  • We did well, and so we came to Washington, D.


  • C.


  • And we did a workshop by the A I.

    我們還做了一個由A I的研討會。

  • P a E p a guys and the SS.

    P a E p a們和黨衛軍。

  • And then it says, say, you guys and they had all the data.


  • But they had It was open but wasn't published.

    但他們有 它是開放的,但沒有公佈。

  • And we showed that actually, there's data around the White House that was clap like for national security.


  • They didn't publish and we and we invited all those guys and our guys taught them how to make the kits, and they walked around and measure the radiation around as well.


  • Now that is public.


  • We really sedated.


  • What now developed Is this a bunch of citizen science kids?


  • A lot of them in Japan now working with the P A and the N s A.

    他們中的很多人現在在日本與P A和N S A合作。

  • And in trying to figure out how to take radiation data, empower citizens were selling these kids and these kits and high schools and pivoting into Teoh air and things like that.


  • And what's interesting is if you get kids that are sufficiently motivated, kids on the edges and give them some sort of interface to this data.


  • And I think right now you're agencies air getting much more inclusive and and it used to be you talk to some professor at some university, give them limited access to the data.

    我認為現在你是機構的空氣 越來越多的包容性,它曾經是 你跟一些教授在一些大學, 給他們有限的訪問數據。

  • But it turns out that that kids will figure out how to use the data, and right now it's mostly visualization.


  • But once we get a I, A farmer may be able to go directed and collect the data, build a model and use a I to to do something.


  • And that's just gonna be a lot of how tools get better, but also how the government interacts with those people.


we're talking about in the specifically even in that extended that intelligence you're talking about government.

我們說的是在具體的 甚至在擴展的情報 你說的是政府。

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    林宜悉 發佈於 2020 年 08 月 06 日