德米斯·哈萨比斯爵士论 AI 革命、AI 的未来与人类创造力

晚上好。感谢大家前来。我是 David Joseph，皇家艺术学会的首席执行官。今晚是我们一年中的高光时刻之一。这一晚，我们会选出一位人物、一个想法，并宣告它意义非凡。

Good evening. Thanks everyone for coming. I'm David Joseph, CEO of the Royal Society of Arts. This evening is one of the highlights of our year. It's the night we choose one person, one idea and say that it mattered.

在开始之前，说说你们现在坐的地方——这个大厅。1877 年，就在这个房间里，Alexander Graham Bell 向人们展示了电话。他们就站在你们现在的位置附近，听到一个盒子里传出人声。也是在这个房间，William Cooke 爵士揭开了电报的面纱。在那天下午之前，信息传递的最快速度就是马的速度。

Before we do, a word about where you're sitting, which is the great room. In this room in 1877, Alexander Graham Bell showed people the telephone. They stood about where you are and heard a voice come out of a box. And in this room, Sir William Cooke unveiled the electric telegraph. Until that afternoon, the fastest a message had ever traveled was the speed of a horse.

同样在这个房间，Thomas Edison 的灯泡首次向英国公众展示。你家里的光，不再来自火焰。这里不是陈列物品的博物馆。那些都是真实的夜晚。人们走进来时一无所知，走出去时已见证了历史的诞生。

In this room, Thomas Edison's light bulb was first shown to the British public. Light in your house that wasn't a flame. And this isn't a museum of things. These were actual nights. People walked in not knowing and walked out having seen history made.

顺便说一句，每一次都有明智的人解释为什么这行不通。当 Edison 说他在造灯泡时，煤气股票暴跌，议会还成立了一个委员会。委员会得出结论：这个想法根本不值得务实之人关注。而当电话出现时，邮政局把它告上法庭并赢了，理由是电话非法地属于电报，而一通电话非法地属于一封电报。

And by the way, every single time someone sensible explained why it wouldn't work. When Edison said he was building a light bulb, gas shares crashed and Parliament set up a committee. The committee concluded the whole idea wasn't worth the attention of practical men. And when the telephone turned up, the post office took it to court and won, on the grounds that a telephone was illegally a telegraph and a phone call was illegally a telegram.

我个人脑海里挥之不去一个画面：一部电话戴着手铐，坐在警车后座。但每一次新事物出现，明智的人都会解释为什么它不可能发生。而几年之后，它就在每个人的家里了。

I personally can't get the image out of my head of a telephone in handcuffs at the back of a police car. But every time something arrives, sensible people explain why it can't happen. And a few years later, it's in everybody's house.

这就是皇家艺术学会的特别之处。270 多年来，这里一直是人们带来想法、在世界其他人决定如何看待它们之前先行检验的地方。也正因如此，今年我们重新定位皇家艺术学会，让它成为「为公共利益而创造」的家园。

And that's what's special about the Royal Society of Arts. For more than 270 years, this has been the place where people bring ideas and test them before the rest of the world has decided what to make of them. It's also why this year we're resetting the Royal Society of Arts as the home of creativity for the common good.

这听起来像是一个使命，但它其实是回归这个地方一直努力在做的事：找到有想法的人，把不同的世界连接起来，让创造力服务于改善每个人的生活。

It sounds like a mission, but it's really a return to what this place has always tried to do: find people with ideas and bring different worlds together and put creativity to work making life better for everyone.

这就说到了这枚奖章，以及今晚我们齐聚于此的原因。Albert 亲王执掌本学会 18 年。他去世后，学会以他的名义设立了一枚奖章。1864 年，我们把第一枚颁给了一位叫 Rowland Hill 的人。Hill 的想法是：一封信应该能用一便士寄到全国任何地方。

Which brings me to the medal and why we're all here tonight. Prince Albert ran the society for 18 years. When he died, the society made a medal in his name. In 1864, we gave the first one to a man called Rowland Hill. Hill's idea was that a letter should go anywhere in the country for a penny.

这听起来是小事，但并非如此。在 Hill 之前，信到的时候才付费，而且寄得越远，费用越高。人们在家门口拒收信件，因为他们付不起拆开看里面写了什么的钱。Hill 的便士邮政解决了这个问题，一夜之间，任何人都可以给任何人写信。

That sounds small, but it wasn't. Before Hill, you paid whenever the letter arrived, and the further it had come, the more it cost you. People turned letters away at their door because they couldn't afford to find out what was inside. Hill's Penny Post fixed it, and overnight anybody could write to anyone.

Hill 之后，奖章颁给了因镭而获奖的 Marie Curie；颁给了 Alexander Graham Bell——他再次获奖，但这次是为了 25 年前在这个房间向我们展示的电话；1945 年颁给 Winston Churchill；颁给把物理学装进普通人头脑的 Stephen Hawking；颁给发明万维网的 Tim Berners-Lee；颁给联合创办 JustGiving 的 Zarine Kharas；以及因牛津疫苗获奖的 Sarah Gilbert。这些在当时看来都并非理所当然。

After Hill, the medal went to Marie Curie for radium, to Alexander Graham Bell, back again, but this time for the telephone he showed us in this room 25 years before, to Winston Churchill in 1945, to Stephen Hawking for putting physics into ordinary people's heads, to Tim Berners-Lee for the World Wide Web, to Zarine Kharas for co-founding JustGiving, and to Sarah Gilbert for the Oxford vaccine. None of it looked obvious at the time.

我大半辈子都在音乐行业工作，所以请再容我多说一分钟。1982 年，音乐家工会的一个分会投票决定禁止合成器。不是限制，是禁止。他们的担忧很简单：一台键盘就能听起来像一整个弦乐组，而一个弦乐组意味着 40 个工作岗位。

I spent most of my life working in music, so please bear with me for one more minute. In 1982, a branch of the Musicians Union voted to ban the synthesizer. Not limit it, ban it. Their worry was simple. One keyboard could sound like a string section, and a string section was 40 jobs.

压垮他们的最后一根稻草是 Barry Manilow，他走在了时代前面。报道说 Barry Manilow 正在英国巡演，但这次他没有带上一次买下的那支管弦乐队。所以这个乐队的想法本身是荒唐的，但底下的恐惧并非毫无道理。

What tipped them over was Barry Manilow, who was ahead of his time. It said Barry Manilow was touring Britain but since instead the orchestra he'd bought the time before. So the idea of the band was madness but the fear underneath it wasn't.

他们对机器的判断错了。合成器模仿小提琴一塌糊涂，却能出色地发出前所未闻的声音。整个 80 年代的声音就由此而来。他们对音乐家的判断没错。有些乐手此后再也没接到工作，另一些人则安然无恙。当时没人能告诉你谁会是哪一种。

They were wrong about the machine. Synths were hopeless at sounding like violins and brilliant at sounding like something never heard before. And the whole sound of the 80s came out of that. They weren't wrong about the musicians. Some of these players never worked again. Others were fine. Nobody could tell you at the time which could be which.

这值得记住。事物在变。有时我们抗拒，有时我们拥抱。有时我们要多年后回望，才明白它们意味着什么。但总有少数人，似乎比我们更早明白什么才重要，并帮助我们看清它。

And that's worth remembering. Things change. Sometimes we resist them and sometimes we embrace them. And sometimes we only understand what they meant years later looking back. But there are a few people who seem to know what matters before the rest of us do and who help us see it.

这就说到了今年的奖章得主，Demis Hassabis 爵士。如果你想让自己自惭形秽，那就听好了。13 岁成为国际象棋大师。17 岁写出一款卖出数百万份的电脑游戏。剑桥毕业，随后拿到研究大脑记忆机制的博士学位。然后他创办了 DeepMind，而 DeepMind 造出了那台造出世界最强围棋选手的机器。

Which brings me to this year's medal recipient, Sir Demis Hassabis. Now, if you want to feel really bad about yourself, listen up. Chess master at 13. Wrote a computer game at 17 that sold millions. Cambridge, then a doctorate in how memory works in the brain. Then he started DeepMind, and DeepMind built the machine that built the best Go player in the world.

他自 2009 年起就是本学会的会士。后来他被授予「皇家工业设计师」，这是英国设计师的最高荣誉。2016 年，他就站在这个房间，向我们讲述人工智能。当时在座没有人能告诉你哪些部分会成真。

He's been a fellow of this society since 2009. He was later made a Royal Designer for Industry, the highest honor for designers in this country. He stood in this room in 2016 and talked to us about artificial intelligence. No one sitting here could have told you which bits would come true.

自那以后，诺贝尔化学奖、爵士头衔、拉斯克奖、突破奖、盖尔德纳奖。医学界三项最重要的奖项，一个接一个。而他实际做的是这件事：你的身体由蛋白质驱动，这些微小的机器数以百万计，承担着各种工作——消化你的晚餐，抵御感冒。而每一个蛋白质的功能都取决于它的形状。

Since then, the Nobel Prize in Chemistry, the knighthood, the Lasker, the Breakthrough, the Gairdner. Three of the biggest prizes in medicine, one after another. And here's what he actually did. Your body is run by proteins, tiny machines, millions of them, doing every job going, digesting your dinner, fighting off a cold. And what each one depends on is its shape.

所以，如果你想理解一种疾病或研发一种药物，你就需要知道这个形状。这就是全部关键。而解析一个蛋白质的形状——仅仅一个——就可能耗费科学家数年，有时是一整个职业生涯。AlphaFold 如今已经完成了 2.62 亿个，而他把每一个都免费送给了地球上每一位研究者。

So if you want to understand a disease or build a drug, you need the shape. That's the whole game. And getting the shape of one protein, just one, could take a scientist years, sometimes a whole career. AlphaFold has now done 262 million of them and he gave every single one away free to every researcher on earth.

Rowland Hill 会认得出这种精神。人们用同样的方法攻这个问题攻了 50 年，而改变发生的原因，是有人换了个角度看它。这就是为公共利益而进行的创造性行动。

Rowland Hill would have recognized that. People had gone at that problem the same way for 50 years and what changed was somebody looking at it differently. That's a creative act for the common good.

他的父亲是一位创作型歌手，一直很崇拜 Bob Dylan，退休后还创作并上演了一部音乐剧。所以那个家庭无论做了什么，都真的很管用。他举重若轻地承载着这一切，我想这正是你能看出他是一位英国科学家的地方。

His dad is a singer-songwriter who's always admired Bob Dylan, and in retirement he's composed and staged a musical. So whatever that house was doing, it was really working. He carries all of this lightly, which I think is how you can tell he's a British scientist.

这枚奖章太重要了，不能草率地交出去。我们认为颁奖的人应该真正了解获奖者。所以我问 Demis 的团队，是否有人愿意说几句话。他们大约一秒钟就回复了：Hannah Fry 教授。

Now, this medal matters too much to hand it over carelessly. We think whoever presents it should know the recipient properly. So I asked Demis' team whether someone might say a few words. It took them about a second to come back with Professor Hannah Fry.

我得声明一个私人渊源。Hannah 曾在电视上用洗甲水溶解了一张银行卡，展示里面隐藏的细铜线。我们在家试了，现在每次在餐厅买单，桌上总有人要提一句那根铜线。我很喜欢这一点。

I should declare a personal interest. Hannah once dissolved a bank card in nail varnish remover on television to show the thin copper wire hidden inside it. We tried it at home and now every time we pay the bill in a restaurant, someone at the table has to mention the wire. And I love that.

这是 Hannah 最了不起的地方之一。她拿出你口袋里装了 20 年的东西，让你看见里面的那个想法。这正是今晚我们在这里的原因。不是发明本身，而是有人想到它的那一刻。请大家热烈欢迎 Hannah Fry 教授。

That's one of the most remarkable things about Hannah. She takes something you've carried in your pocket for 20 years and shows you the idea inside it. And that's why we're here tonight. Not the invention, the moment somebody thought of it. Please give a very warm welcome to Professor Hannah Fry.

非常感谢，David。好。好。

Thank you very much, David. Okay. Okay.

大卫已经带我们回顾了德米斯取得的一些重大成就，这很有用，因为我觉得要是把他完整的履历念一遍，恐怕得念到明天早上。不过，我在这里是想让大家更了解坐在我们面前的这个人。2017 年我第一次采访德米斯时，我翻看他那份简直离谱的成就清单——那些成就是在我们大多数人还没搞清楚自己擅长什么之前就取得的：国际象棋神童、游戏设计师、剑桥毕业生、世界级神经科学家。我厚着脸皮问他：“德米斯，你就不能稍微再努力一点吗？”德米斯没有一笑置之，而是给我讲了一个不可思议的故事：他小时候，他爸爸给过他完全一样的建议——你做得多好并不重要，只要你尽了最大努力。但德米斯当时大约九岁，他并没有把这当作安慰，而是把它听成了一个哲学难题，因为你到底怎么知道自己已经尽了最大努力？你怎么能在不把自己逼死的情况下，把努力这件事优化到极致？因为这里有个逻辑：如果你最后还活着，那你肯定还能再多付出一点。DeepMind 联合创始人肖恩·莱格说得很到位：德米斯没有 50% 模式，甚至连 99% 模式都没有，只有 100%。作为一个和德米斯玩过 Bananagrams 的人，我可以确认这话有多准确。顺便给个建议，如果你有得选，别跟他玩，对你的自尊心没好处。我觉得德米斯小时候那个故事里还有一点很值得注意，因为德米斯让我印象最深的是，他好像一辈子都在问一些表面上很不合理的问题。不只是“我怎么才能把棋下得更好”，而是“我大脑里发生了什么？我下棋时大脑到底在做什么？”不只是“我怎么做一个电脑游戏”，而是“现实有多少可以被模拟捕捉？”不只是“AI 能不能在游戏里打败我们”，而是“AI 能不能帮我们解决科学里最难的问题，同时帮助人类？”最后这一点，我觉得才是真正重要的。因为在德米斯身上，我亲眼看到，对人类福祉的关切并不是事后附加的东西，而是贯穿在他思考过程的每一个阶段。他的雄心当然巨大，但与之相伴的，还有德米斯那种非凡的责任感。我觉得正是这种组合——非凡的雄心、不懈的好奇心，以及对这一切最终走向何方的真诚关切——让德米斯如此特别。这也是为什么包括我在内的很多人，因为知道德米斯在塑造未来中扮演如此关键的角色，而对未来更加乐观。所有这些，我觉得都特别契合阿尔伯特奖章，这个奖表彰非凡的创造力，同时也表彰把这种创造力用于真正改变世界。德米斯，你这一生都非常非常努力，可能努力得有点不太理智。我非常荣幸能为你颁发 RSA 的阿尔伯特奖章。

Well, David has already taken us through some of the biggest achievements that Demis has made, which is useful because I think reading out Demis' entire CV would take us through to next morning. But I'm here instead to give you a little bit more of a picture of the person who's sitting in front of us. When I very first got to interview Demis back in 2017, I was going through the frankly absurd list of things that he'd achieved before most of us have even worked out what we're good at: chess prodigy, games designer, Cambridge graduate, world-class neuroscientist. And I cheekily decided to ask him, "Demis, could you not have tried a bit harder?" And rather than just laugh it off, Demis told me this incredible story about when he was a kid and his dad had offered him the exact same piece of advice: it doesn't matter how well you do as long as you try your hardest. Now, rather than hearing that as reassurance, Demis, who by the way was aged about nine at this point, heard it instead as a philosophical problem, because how do you actually know that you've tried your hardest? How do you manage to optimize for effort without dying? Because the thing is, there is a logic to it: if you are alive at the end of it, then surely you could have had a bit more to give. Now, the DeepMind co-founder Shane Legg puts it really well. He says there is no 50% mode in Demis. There isn't even a 99% mode. There is only 100%. And as somebody who has played Bananagrams with Demis, can I just confirm how accurate that is. By the way, word of advice, if you get that option, don't take it. It's not good for your ego. Now I think there is something else in that story about when Demis was a child that is really worth noting, because the thing that strikes me about Demis is that he appears to have spent his entire life asking, on the surface, unreasonable questions. Not just how do I get better at chess, but what is it in my brain? What is my brain actually doing when I am playing chess? Not just how do I build a computer game, but how much of reality could be captured by simulation? Not just can AI beat us at games, but can AI help us to solve some of the hardest problems in science and help humanity while we're at it? And that last bit, that's the bit I think that really matters here. Because with Demis, I've seen firsthand how the concern for humanity isn't just something that gets tacked on afterwards. It is right there at every single stage of his thought process. The ambition is enormous, of course, but so is Demis' extraordinary sense of responsibility that comes with it. And I think that's the combination: extraordinary ambition, relentless curiosity, and a genuine concern for where it all leads that really makes Demis quite so special. It's also why so many people, myself included, feel so much more optimistic about the future, knowing that Demis is such a key part of shaping it. And all of that I think feels particularly fitting for the Albert Medal, which is an award that celebrates extraordinary ingenuity, but also put to work in a way that makes a real difference to the world. Now, Demis, you have spent your life trying very, very hard. Possibly harder than is entirely sensible. And it is an absolutely enormous pleasure for me to get to present you with the RSA's Albert Medal.

感谢大家今晚前来，也感谢大卫和汉娜精彩的介绍和开场致辞，你们太客气了。每次来 RSA 我都非常高兴，尤其是能在这个房间里，他们提醒我，10 年前我在这里做过一次演讲。感觉比那近多了，但这里真是个鼓舞人心的空间，这个房间里发生过那么多了不起的事，还有我们看到的那些精彩艺术。获得阿尔伯特奖章是巨大的荣誉，尤其是我翻看历届获奖者名单时，看到所有这些了不起的人，我特别喜欢的是这个奖所表彰和认可的那种跨学科性质。这也正是我一生努力践行的方式，经营我职业生涯的方式：不把创造力和科学之间划出界限。事实上恰恰相反。我从一开始就一直工作在技术与创造力的交叉点上。大卫提到我早期的游戏生涯，设计和编程电子游戏，主要是在 90 年代，游戏产业的早期阶段。我当时对游戏产业如此着迷，因为它真正在运用创造力，这个想法就是为数百万人创造某种有趣或好玩的东西来互动。但那个目标，那个创造性的目标，推动了所有这些惊人的技术进步。当时是在发明 3D 图形。我用它来尝试把 AI 推到前沿。事实上，当时超越学术界正在发生的事情，实际上是游戏产业在推动很多 AI 理念，甚至硬件。所以我们今天使用的硬件，我们用于 AI 的 GPU，最初当然是为 3D 图形发明的。结果发现，一切都是矩阵乘法。所以，也许在宇宙中也是如此，但我们可以晚宴或喝酒时再聊这个。但不可思议的是，不仅是你直接想做的事情，这些附带的好处也会出现。这是我在整个职业生涯中学到的教训之一：你为一个目标本身而追求它，然后如果这个目标足够大、足够有雄心，并且以足够跨学科的方式去做，其他你当时无法想象的奇妙事情就会发生，并被它促成。我觉得这样的例子太多了。我想我成长在一个家庭里，大卫提到了我爸爸、我妈妈，还有我哥哥和姐姐。他们都偏向创造性的一面，比如音乐。我姐姐是职业音乐家和作曲家。玩游戏和艺术，真的是我整个家庭、我的基因、我的成长环境所围绕的。但对我来说有趣的是，我最初是通过国际象棋训练，然后是计算机，然后是科学。我所有的正规训练都在科学和逻辑这一边。但在我内心，我认为自己是被创造力、直觉，实际上是情感所引导的，这也许是你没想到会从一位科学家口中听到的。但我认为这也正是帮助我做科学的原因。

Well, thank you all of you for coming this evening and thank you David and Hannah for those amazing introductions and opening remarks. So generous of you. It's always an enormous pleasure for me to come and visit the RSA and especially be in this room, as they reminded me I gave a talk about it 10 years ago here. It felt much more recent than that, but it's just such an inspiring space and all of the amazing things that have happened in this room, the amazing art that we see. And it's a huge honor to be awarded the Albert Medal, especially as I was looking back through all the previous recipients and all these amazing people, and what I really love about it is the interdisciplinary nature of what it celebrates and recognizes. And that's the way I've tried to live my whole life and run my career: not really seeing any boundaries between creativity and science. In fact, much the opposite. I've always worked at the intersection of technology and creativity right from the very beginning. David mentioned my early games career, designing and programming video games, mostly in the 90s, in the early stages of the games industry. And I was so fascinated by the games industry at that time because it was really using creativity, this idea of making something fun or interesting for millions of people to interact with. But that goal, the creative goal, was driving all of this amazing technology advancements. At the time it was inventing 3D graphics. I was using it to try and push AI at the forefront of what was going on. And in fact beyond what was happening in academia at that time, it was actually the game industry that was pushing forward a lot of AI ideas and then even the hardware. So the hardware we use today, the GPUs that we use for AI, were originally of course invented for 3D graphics. And it turns out that everything is a matrix multiplication, it turns out. So, maybe in the universe, but we can maybe talk about that later at dinner, or at the drinks. But it's kind of incredible that not only the direct things that you were trying to do, but these sort of ancillary benefits appear. And that's been one of the lessons I've taken throughout my career: you pursue a goal for its own sake, and then if it's a big enough, ambitious enough goal, in a multidisciplinary enough way, other amazing things will happen and be facilitated by that that you couldn't have imagined at the time. And I think there's just so many examples of that. And I guess I was brought up in a household and David mentioned my dad, my mom, and actually my brother and sister. They're all on the creative side of things, you know, music. And my sister's a professional musician and composer. And games playing and the arts is really where my whole family, I guess my genetics, my kind of upbringing is about that. But the interesting thing for me is I trained first through chess, then computers, and then the sciences. My whole formal training has all been on the scientific logical side. But at my heart, I think of myself as being led creatively, intuitively, and emotionally actually, which is maybe you wouldn't expect to hear that from a scientist. But I think that's also what's helped me in my science.

我认为，区分优秀科学家和伟大科学家的关键在于创造力。所有优秀的专业科学家、教授等等，从定义上讲，他们在技术上都已经是出类拔萃的。否则，他们不可能达到那个水平。但真正带来重大突破的，我认为是创造力的一面和直觉的飞跃。如果你再看看那些被提及的人，阿尔伯特奖章和其他大奖的获得者，基本上正是他们的直觉飞跃常常引领他们取得重大突破，而这些突破又建立在他们的技术能力之上。

I think what separates the good scientists from the great scientists is creativity. All good professional scientists, professors, and so on, are already by definition brilliant technically at what they do. Otherwise, they wouldn't have reached that level. But then it's the creative side and intuitive leaps that I think have yielded the big breakthroughs. If you look again at some of the people that were mentioned, recipients of the Albert Medal and the other big prizes, it's basically their leaps of intuition often that lead them to their big breakthroughs, underpinned by their technical capabilities.

所以，当我们现在展望 AI 时，这——你们可能都听过我关于这个的演讲——我整个职业生涯都在以某种形式研究 AI，因为我认为它将成为人类有史以来最深刻的技术之一。我认为它将带来一场像电力那样的革命。电话、互联网、移动——我认为它至少会和所有这些一样大，甚至可能更大。也许影响是工业革命的 10 倍，而额外的挑战是它可能发生得快 10 倍，所以是在十年内展开，而不是一个世纪。

So I think again as we look forward now to AI, this is a — you've all probably heard me give talks about this — and I've spent my whole career working on AI in one form or another because I think it's going to be one of the most profound technologies humanity will ever invent. And I think it will be a revolution in the way that electricity was. Telephone, we've heard the internet, mobile — I think it'll be at least as big but perhaps bigger than all of those. Maybe something like 10 times the impact of the industrial revolution, and the additional challenge is that it's probably going to happen 10 times faster, so unfolding over a decade instead of a century.

工业革命带来了许多惊人的事物：现代医学、儿童死亡率下降，最终带来了所有这些不可思议的东西。但它也带来了我们熟知的挑战，事实上需要新的机构、新的方法来应对工业化的弊端以及对环境的影响等等。

The industrial revolution brought many amazing things: modern medicine, child mortality went down, all of these incredible things in the end that it brought. But it also came with challenges that we all knew, and in fact new institutions, new approaches were needed to deal with the downsides of industrialization and the effect on the environment and so on.

我认为 AI 带来了难以置信的机遇。我一生致力于 AI 的主要原因和动机之一是推动科学和医学的进步。这就是为什么我个人从事 AlphaFold 以及现在我们的分拆公司 Isomorphic 来加速药物发现。我一直说，我认为 AI 可以应用的第一件事是改善人类健康，我现在仍然相信这一点。我认为最终它可能是推进我们对周围世界理解的最神奇的工具。这就是我所梦想的，也是我正在努力推动的。我认为这就是社会需要从这些新技术中得到的东西。

And I think again with AI there's just unbelievable opportunity. One of the main reasons and motivations for me to work on AI my whole life is to advance science and medicine. That's why I personally work on things like AlphaFold and now our spin-out Isomorphic to accelerate drug discovery. I've always said that the number one thing I think we can apply AI to is improving human health, and I still believe that now. And I think ultimately it could be the most amazing tool for advancing our understanding of the world around us. That's what I'm dreaming about and that's what I'm pushing really hard on. And I think that's what society needs from these new technologies.

但当然，这不仅仅是技术的问题，还关乎我们该做什么，我们作为一个社会想用它做什么。技术只是开启了所有这些机会、所有这些可能性、所有这些路径，这就是我作为技术专家、工程师和科学家所看到的。但它并没有定义我们应该用它做什么，什么对社会有益，它应该如何塑造人类的下一个时代。我认为这属于艺术、人文和社会科学，以及 RSA 和这个房间里许多人代表的那些方面，来塑造和引导人类进入下一个时代，以对所有人都有益的方式。我认为这实际上几乎是一个哲学问题。

But of course it's not just about the technology, it's also about what do we do, what do we want as a society to do with it. The technology just enables all these opportunities, all these possibilities, all these paths, and that's what I see as a technologist and an engineer and a scientist. But it doesn't define what we should do with it all, what is beneficial for society, how should it shape the next era of humanity. And I think that's for the arts and humanities and social sciences and those aspects that are represented by the RSA and many of the people in this room about shaping that and guiding humanity into that next era in a way that is going to be beneficial for everyone. And I think that's almost a philosophical problem actually.

我经常谈到，在这个时刻，当我们处于边缘，在——我喜欢称之为奇点的山脚下——距离完全 AGI 还有几年。我们需要现在就开始思考这个问题。我认为社会还没有为即将到来的事情做好准备。我们将重视什么？目的是什么？我们将如何利用这些工具来增强人类的创造力而不是取代它？在 AI 的世界里，工艺和创意作品的灵魂之间的区别将是什么？这些非常引人入胜的问题，我认为技术专家实际上并不是最适合回答的。我认为这必须来自艺术和人文学科来定义下一个时代。

And I've often talked about the need for, at this juncture when we're on the cusp, on the eve of — the foothills of the singularity I like to call it — a few years away from full AGI. We need to start thinking about that now. I don't think society's ready yet for what's coming. What are we going to value? What is purpose? How are we going to use these tools to enhance human creativity not replace it? What is the difference between craft and the soul of a creative piece going to be in the world of AI? Really fascinating questions that I think the technologists are not best placed to answer actually. I think that's got to come from the arts and the humanities to define that next era.

我真正希望的是，像这样的地方可以成为跨越科学和艺术的讨论的汇聚点。我认为在 AI 的新时代，这比以往任何时候都更重要。比如，作为人类，以及我们创造和珍视的事物，将意味着什么？

And what I really hope is that places like this can be a convening point for that discussion across the sciences and the arts. And I think that's more important than ever in this new era of AI. Like what is it going to mean to be human and the things that we create and then value?

我毫不怀疑——我乐观的一面是我毫不怀疑我们将能够应对这个新时代并适应它，因为我真的相信人类创造力的力量，再次由这个房间所代表。我认为朱迪·丹奇女爵士提到的——我们用创造性的头脑已经创造出的东西难道不令人惊叹吗？当我乘坐跨大西洋航班时，我常常停下来惊叹，我们是如何用进化来在苔原上狩猎采集的大脑做到这一点的。我们是如何设法创造出所有这些艺术和这种美，以及这个现代——我们所谓的现代文明，包括我们所有的技术，比如乘坐 747 飞越大洋。如果你想一想，这简直是奇迹。

And I've no doubt — so the optimistic part of me is I've no doubt we will be able to deal with this new era and adapt to it because I really believe in the power of human ingenuity, again represented by this room. And I think what Dame Judi Dench mentioned about — isn't it amazing what we've already created with our creative minds. I often stop and marvel when I go on a transatlantic flight of how did we do this with our brains that were evolved for hunter-gathering out in the tundra. How have we managed to create all of this art and this beauty and this modern — what we call modern civilization, including all of our technologies like flying on a 747 across the ocean. It's just miraculous if you think about it.

所以，如果我们设法做到了这一点并适应了这里，我毫不怀疑我们和下一代将弄清楚下一步该做什么。但我们需要认真对待。我们需要昨天就开始这场辩论，因为我认为这正非常快速地朝我们走来。但我相信我们会解决它，我们会走出另一边，迎来一个光明的新未来，我希望那几乎是一场新的文艺复兴，科学和艺术的新的融合，也许自文艺复兴以来从未发生过。我认为我们再次迎来了这样的机会，也许它将开启一个科学发现和奇迹的新黄金时代。非常感谢。

So if we manage to do that and adapt to here, I've got no doubt we and the next generation will figure out what to do next. But we need to take it seriously. We need to start that debate yesterday, because I think this is coming very fast towards us. But I'm sure we will work through it and we'll come out the other side in a bright new future and what I hope will be almost a new renaissance, a new coming together of science and the arts maybe that hasn't happened since the Renaissance. I think we're due that again and perhaps it will unleash a new golden era of scientific discovery and wonder. Thank you very much.

我的意思是，你在那里结束评论时谈到了文艺复兴。我一直认为非常值得注意的是，多年来你在 DeepMind 的办公室以达芬奇命名。为什么是达芬奇？达芬奇的什么特质如此启发你？

I mean you ended your comments there talking about the Renaissance. I always thought it was really notable that for a number of years your office at DeepMind was named after Da Vinci. Why Da Vinci? What is it about Da Vinci that inspired you so much?

我有大概三四个最喜欢的——我想你可以称他们为科学英雄——有史以来，达芬奇是其中之一，亚里士多德是另一个，因为他们的全才。你可以说达芬奇，你知道，他有着令人难以置信的艺术天赋，比如《蒙娜丽莎》和《最后的晚餐》等等。然后你看看他的医学和工程图纸，他画了这些精美绝伦的心脏和肺部以及大量生物学的图画。如果他在艺术方面不杰出，他就不可能达到那种科学上的精确度。所以我只是觉得他迷人。我很想再次看到那种时代，我认为 AI 也许能帮助实现这一点。所以他一直是我最大的灵感来源。

So I have sort of three or four favorite — I guess you can call them scientific heroes — of all time, and Da Vinci is one of them, and Aristotle is the other, because of their all-roundedness. You could say Da Vinci, you know, he had incredible artistic talents, like the Mona Lisa and The Last Supper and so on. And then you look at his medical and engineering drawings, and he painted these exquisitely beautiful drawings of the heart and the lungs and lots of biology. And he wouldn't have been able to do that to the scientific level of accuracy if he wasn't brilliant from the artistic side. So I just find him fascinating. And I'd love to see that type of era again and I think AI could maybe help with that. So he's always been my big inspiration for me.

他简直就是跨学科的终极典范。

He's like the ultimate interdisciplinarian.

是的，没错。我觉得如果你读他的传记，会发现他根本不觉得自己的能力有什么界限。我不认为他会想“我现在在做艺术，我现在在做科学”。他就是画。他就是做令人惊叹的事，创造令人惊叹的东西。

Yes. Exactly. And I think if you read biographies of him, he just didn't see any boundaries between what he was able to do. I don't think he thought about it as 'I'm doing art now. I'm doing science now.' He just drew. He just did amazing things, produced amazing things.

说到这些界限，大卫谈到了你的家庭背景，你全家都是艺术家。你成长过程中有没有感觉到某种界限？你觉得自己是异类，还是觉得你只是在做……

In terms of those boundaries, I mean, David was talking about your family background, you know, the fact that all of your family are artists. Did you feel a boundary as it were when you were growing up? Did you feel like the odd one out or did it just feel like you were doing...

不，我小时候没有这种感觉。嗯，后来我才意识到，大概是在我快 30 岁的时候。我把我父母描述为波西米亚式的人，意思是说我们没钱，但总是充满创造力。嗯，我觉得我父亲鼓励不循规蹈矩，这么说吧。我父母从来没有过正常的朝九晚五的工作，他们也不相信那种生活。所以我想这给了我们所有孩子一种许可，去做不寻常的事，追随你的热情。嗯，然后我妈妈一直更偏向精神和艺术方面。所以我一直有那种输入，人文方面的，如果你愿意这么叫的话。嗯，然后我觉得这和我喜欢国际象棋、计算机这些东西形成了很好的组合，而必须在这些方面变得更好，又鼓励我提升自己逻辑和科学的那部分思维。我觉得我真正热爱计算机和国际象棋这些东西的地方在于创造性的产出。所以，你知道，设计游戏或者下精彩的棋局。这些其实都是艺术性的追求和产出，但你必须非常技术化才能产出配得上这个名号的成果。所以你必须在数学和科学方面都变得出色。然后对我来说，从小到大的驱动力、北极星，就是试图回答那些大问题，我们周围世界的重大谜团。嗯，为此我认为你需要艺术和科学两方面才能真正理解很多这些问题。意识的本质、创造力、做梦、时间，你提到了，我一直对时间感兴趣。所以，你知道，在我看来有太多迷人的东西值得探究。这就是最终让我很快走向 AI 的原因，因为我觉得我们需要一个元工具来帮助我们，帮助我在相对短暂的一生中尽可能多地回答这些问题。

No, when I was young, it didn't. Um, I mean later I realized it, sort of in my maybe my late 20s or something. But I sort of described my parents as bohemian in the sense of like we had no money, but it was always just sort of being creative. Uh, and I think my dad encouraged not being conventional, let's put it that way. So my parents have never had sort of normal 9-to-5 jobs and they didn't really believe in that. So I guess that gave all of us kids the sort of permission to be kind of unconventional, follow your passions. Um and then my mom was always more on the kind of spiritual and arts side. So I've always had that kind of input, the humanities if you want to call it, coming through that. Uh, and then I think it was just a great combination with me loving chess and computers and sort of those and then having to get better at those things encouraged me to improve my logical scientific part of my mind. I think what I really loved about computers and chess and all those things was the creative output. So, you know, designing games or playing great games of chess. These are kind of artistic pursuits really and outputs, but you have to be very technical to produce outputs worthy of the name. So you sort of have to get good at all of the mathematics and the sciences. And then really for me where all the drive, the north star for me from since I was a kid is trying to answer the big questions and the big mysteries of the world around us. Um, and for that I think you need both the art side and the scientific side to really truly understand a lot of these questions. The nature of consciousness, creativity, dreaming, time, you mentioned it, I've been interested in it. So, you know, there's so many fascinating things in my opinion to look into. That's what led me to AI in the end pretty quickly because I felt we needed a meta tool to help us and help me with answering as many of those questions as one can in what is a relatively short lifetime.

嗯，我想你 16 岁时的第二职业——游戏设计师——很好地说明了这一点。你知道，一方面它是创造性的追求，但另一方面它也是你第一次真正涉足 AI，对吧？跟我们讲讲你在那里做的事情怎么就成了 DeepMind 的最初起点。

Well, I guess your second career by 16 as a games designer is sort of a good illustration of that point. You know, it's kind of a creative pursuit on one level, but it was also your first foray into AI really, right? Tell us how what you were doing there ended up being the very beginnings of what happened with DeepMind.

嗯，因为总的来说时间不够。所以我一直处于这种匆忙之中，因为有太多事情，太多令人惊叹的事情要去发现、创造和体验，也因为有很多有趣的事情可做，我通常喜欢做一件事有不止一个理由。所以，至少至少四个理由，如果可能的话。所以，游戏就是一个很好的例子。所以我热爱游戏。嗯，我喜欢设计和玩游戏。我能看到人们从中获得的乐趣。但我也把它当作一个特洛伊木马，尤其是用我自己的公司 Elixir Studios，来设法获得一些 AI 研究的资金，否则你根本拿不到。我们说的是 90 年代初，对吧？用其他方式根本不可能拿到资金。但我会尝试偷偷塞进一些 AI 研究，和像 Dave Silver 这样的人一起，表面上是为了做我们的游戏，嗯，控制那些小人或者游戏底层的模拟。然后那会变得成功，然后就能资助下一个 AI 想法。所以我在学习所有这些，也在学习如何管理初创公司，还有创意工程团队。所以我从那里带到 DeepMind 的东西是：你如何把前沿工程和创意目标结合起来。所以在这个案例中就是“什么时候会好玩？”如果你想真正吓到一个设计师，游戏设计师，你只要问他们这个问题。所以，这个游戏什么时候会好玩，你知道，是三个月还是六个月后？然后就像，嗯，我不知道，因为但显然你的发行商，他们付钱，他们就会说，你知道，现在好玩吗？不，还不好。嗯，但它会的，这有点让我想起后来我做博士时的那种感觉，就像，嗯，这个突破什么时候会发生？你知道，你想要因为研究，如果你已经知道答案，那就不叫研究了。如果你能保证它会好玩，那你建造的东西就不叫创意了，对吧。所以实际上我意识到，在创意部分，这种未知，非常类似，它需要很多品味、直觉和对所做之事的一种信念，我意识到做科学和游戏设计非常相似，游戏设计师和游戏中的艺术家，最好的那些，在我看来，他们做的事情和我见过的最好的科学家非常相似，然后支撑这一切的是与伟大工程和技术能力的结合，以及如何把它们融合在一起？所以我们在游戏中曾经遇到的困难是，你有所有这些工程在进行，它试图支持和拦截一个实际上是开放式的创意问题。这在科学中有点类似，我们必须建造所有这些技术，尤其是在 AI 中支持像 AlphaFold 这样的东西。你并不确切知道它什么时候会完成，但你知道，你大致知道你需要建造哪些类型的东西，这是一个迭代的过程。这就是为什么我喜欢建立多学科团队。它们必须相互滋养。工程为研究提供信息，研究为下一部分工程提供信息，这就是为什么 AlphaFold 和 AlphaGo 这样的项目成功了。

Well, because there's not enough time in general. So, I've always been in this rush because there's so many things, so many amazing things to discover and create and experience and also because there's so many interesting things to do I like doing things for more than one reason generally. So, at least at least four reasons if possible. So, games, you know, was a great one. So, I love games. Uh, I loved designing and playing games. I could see the enjoyment people would get from them. But I also used as a bit of a Trojan horse, especially with my own company, Elixir Studios, to get some AI research funded somehow, which you couldn't get funded any other. We're talking about early '90s here, right? It was impossible to get it funded any other way. But I would try and sneak in some AI research with people like Dave Silver, like ostensibly to do our games, uh, and to control the, you know, the little people or the simulation under the game. and then that would become successful and then could fund the next ideas in AI. So I was learning about all of that and also learning how to manage startups but also creative engineering teams. So the something I took with me from that to DeepMind was how do you combine cutting edge engineering with something that's a creative objective. So in this case it was when is it going to be fun? If you want to really scare a designer, game designer, you could just ask them that question. So, when is this game going to be fun, you know, and is it gonna be in three months or six months? And it's like, well, I don't know because but obviously your publishers who are paying for it, they're just like, you know, is it fun now? No, not yet. Um, but it will be and that's a little bit it reminded me of then when I did my PhD of like the sort of like, well, when is this breakthrough going to happen? You know, that you want to because research if if you knew the answer already, then it wouldn't be research. If you knew could guarantee it was going to be fun then it wouldn't be creative what you were building right so actually I realized there was it was very analogous in terms of the creative part of it this unknown it needed a lot of taste and intuition and kind of faith in what you're doing and I realized doing science and game design that was quite similar the games designers and artists in the games the best ones to me felt quite similar in what they were doing to the best scientists that I'd met and then underpinning that was this combination with great engineering and technical ability and sort of like how do you mix that together? And and so the the difficulty we used to have in games is you've got all this engineering going on and it's trying to support and intercept what is effectively an open-ended creative question. And that's a little bit like the same in science is like we got to build all these technologies especially in AI supporting something like AlphaFold. You don't exactly know when it will be done, but you know what the the the you kind of know the types of things you've got to build and it's an iterative thing. That's why I love building multi-disciplinary teams. They've got to feed into each other. The engineering informs the research and the research informs the next part of the engineering and that's why things like AlphaFold and AlphaGo were successful.

你提到了你的博士。我们可能也应该谈谈这个，因为从表面上看，从游戏设计师到神经科学家，尤其是研究大脑中的想象力，这看起来是一个相当大的急转弯，但对你来说，这是同一个拼图的另一块。

I mean you mentioned your PhD there. We should probably talk about this as well because I mean this was quite a corner turn from from the surface looking at it from games designer to neuroscientist especially looking at imagination in in the brain and that sort of feels like quite a big sharp change in direction but but for you it was another piece of the same puzzle.

是的。

Yeah.

对我来说，这只是从不同角度切入。如果你没意识到我当时是在试图打造 DeepMind 和 AGI，那看起来会有点奇怪，对吧？我当时在做游戏设计。我在剑桥读的本科是计算机科学。为什么会转向神经科学？嗯，是因为我想从所有可能的角度来看这个问题。比如，什么是智能？支撑智能的能力有哪些？然后读博士也是同样的考虑。所以我觉得在我的游戏生涯中，二十出头的时候，我已经把当时已知的 AI 知识推到了极限。那是 90 年代中期，在神经网络革命等等之前。所以我在寻找一种，你知道，在 2000 年代初期，一种正交的信息来源，关于智能如何运作，思考、规划，以及所有我们视为智能的事情。那还有什么地方比大脑更好呢？当然，fMRI 机器刚刚变得主流。所以有这些新的不可思议的工具可用。你知道，我们可以窥视大脑内部。如果你想想 fMRI 机器，那本身就很了不起。我们现在都做，你知道，例行公事地用于体检。但在 2000 年代初期，那是一种不可思议的东西。什么？你要用这些巨大的磁铁窥视大脑内部，看看当你思考时哪些部分会亮起来。我的意思是，对我来说这简直无法抗拒，老实说，你能在关于思考等重大问题上取得一些进展。然后我选择了记忆和想象力，因为首先它们是迷人的话题，但想象力特别是像为未来做规划。那是我在游戏和国际象棋生涯中经常做的事情，你知道，实际上在国际象棋中，你就像在向前规划，你想将死某人或达到一个获胜位置，你必须规划，你想象那个，然后你向后规划，你可视化那个，然后从那里向后规划。所以我不知道你们是否都看过《女王的棋局》这部剧，很棒的剧，它非常准确，因为加里·卡斯帕罗夫，你知道，是那部剧的顾问。你知道，当她睡觉时梦见那些棋局，它们在她脑海中，那就是顶级棋手实际的感觉。所以我在做所有这些，你知道，所以我经历了所有这些，然后在游戏设计中我也重新使用了它，就像，好吧，回答这个问题：什么时候会好玩？你想象有人在玩它，他们会遇到什么困难，他们什么时候会感到无聊，界面如何工作，所有那些事情，你知道，你是在本能地想象它。所以我觉得，所以我对大脑如何做到这一点非常着迷，几乎没有人研究过想象力这个问题。他们研究了记忆，但没有研究想象力。然后还有，我们对 AI 如何做到这一点一无所知。所以这是一种似乎对我们创造、规划和推理的方式至关重要的能力，但当时我们对 AI 如何做到这一点一无所知。所以出于多个原因，这似乎是一个值得研究的好东西。作为第三个原因，我想在世界顶尖大学，向最优秀的教授学习，研究是如何运作的，在知识前沿发现新事物，那感觉如何？它令人兴奋，所以，它很棒，但也有一个完整的过程，我认为我的许多技术同事不理解，因为它不同于工程，实际做研究。

So for me it was just different angles. I think if you didn't realize I was trying to build DeepMind and AGI, then it would look a bit strange, right? So I was doing game design. I did computer science as my undergraduate at Cambridge. Why would you switch to neuroscience? Well, it's because I was trying to look at the question from every angle possible. Like, what is intelligence? What are the capabilities that underly intelligence? And again with my PhD. So I felt during my games career, my early 20s, I'd pushed AI knowledge as far as it could go as it was known then. So this was the mid-90s before the neural network revolution and so on. So I was looking for a kind of, you know, in the early 2000s, an orthogonal source of information about how does intelligence work and thinking and planning and all the things that we regard as being intelligent. So what better place to look than the brain? And of course fMRI machines had just become kind of mainstream. So there was all these new incredible tools to use. You know, we could look inside the brain. If you think about an fMRI machine, that's kind of amazing as well. We all do it, you know, use it for our medical exams, you know, routinely now. But back in the early 2000s, it was sort of kind of this incredible thing. You what? You're going to look inside the brain and with these massive magnets and see where what bits light up when you think. I mean, it was kind of irresistible to me to be honest that you could make some progress there about some of the big questions about thinking and so on. And then I picked memory and imagination because firstly they're fascinating topics, but imagination specifically like planning for the future. That was what I was doing a lot in my games and chess career was, you know, effectively in chess you're like planning forward to some, you know, you want to checkmate someone or get to a winning position and you got to plan, you imagine that and then you plan back, you visualize that and you plan back from there. So I don't know if you've all seen Queen's Gambit, the series, amazing series, it's very accurate because Garry Kasparov, you know, was consulting on that. And you know, when she's dreaming about the positions when she's sleeping and you know, they're kind of in her mind, that is how it actually feels when you're the top chess player. So I was doing all, you know, so I'd experienced all of that and then same in game design I reused that as like, okay, so answering this question of when it's going to be fun, you know, you imagine someone playing it and what are the difficulties they're going to have, you know, when are they going to get bored and how does the interface going to work and all of those things, you know, you're kind of viscerally imagining it. So I felt, so I was very fascinated by how the brain does it and almost no one had looked at this question of imagination. They looked at memory but not imagination. And then also it was something we had no idea how to do with AI. So it was a capability that seemed fundamental to the way we create and plan and reason, but we had no idea how to do with AI at that time. So for multiple reasons again, that seemed like a good thing to look at. And as a third reason, I wanted to understand at, you know, some of the top universities in the world, learning from some of the best professors, how does research work and how does discovering new things at the coalface of, you know, the frontier of knowledge, how does that feel? And it's exhilarating, so, and it's amazing, but there's a whole process to it too that I think a lot of my technologist sort of colleagues don't understand because it's different from engineering, actually doing research.

我的意思是，当你把它们这样放在一起时，确实感觉好像一直都是同一个问题。你知道，大脑有点像模拟引擎，游戏也是模拟引擎。我的意思是，甚至在某种程度上，国际象棋、文学和音乐，你都在构建这个版本的现实，你可以去花一点时间沉浸其中。这真的是同一个问题，不是吗？

I mean when you put them together like that it does sort of feel as though it has all been the same question all along. You know you've got the brain is sort of a simulation engine, the like games are a simulation engine. I mean even in a way chess and literature and music you're sort of constructing this version of reality that you get to sort of go and spend a little bit of time in. It is the same question really isn't it?

是的。确实如此。我的意思是，我认为我有两个紧密相连的着迷点。我一生中很幸运，能够找到很多我非常热衷的事情，然后我能够把这些事情连接成一个更宏大的目标。如果你想想核心，就是两件事：AI 和智能，它是什么，我们如何利用它来在其他方面取得进步。然后第二件事是模拟，使用那些精确的、构建精确的模拟器。最初我是为游戏手工做这些，但它们很小，你知道，是我后来要做的事情的小缩影。所以，你知道，甚至我的第一个游戏《主题公园》，大卫提到的，就是一个小型的迪士尼世界的模拟。在 1993、94 年尝试这样做是闻所未闻的。我惊讶于你能走多远，你知道，以至于 1000 万人会喜欢与那个相当基本的主题公园模拟互动。当然，这引出了更大的问题：这里发生了什么？我并不认同某种基本的模拟理论，但人们确实必须从计算和物理的角度来思考，我和很多物理学家谈过这个，到底是什么真正支撑着现实的本质，在我看来这是终极问题，所以是的，对我来说所有道路都通向那个问题。

It is. It is really. I mean so I think that the two fast twin fascinations I've had, I mean I've been lucky in my life I've been able to find a lot of things I'm very passionate about and then I've been able to connect those things together into the kind of a kind of grander goal. And if you think of the heart of it, it's the two things is AI and intelligence, what is it, how can we harness it to advance in other ways. And then the second thing is simulations and using those accurate building accurate simulators. Originally I was doing them by hand for games, but they were little, you know, little microcosms of what I would go on to do. So, you know, even my first game Theme Park that David mentioned was a little simulation of a Disney World. And it was unheard of to try and do that in this was 1993 94. And I was amazed by how far you could get, you know, to the extent where 10 million people would enjoy interacting with that fairly basic simulation of a theme park. And of course that leads me to the bigger question of like well what's going on here? I'm not subscribing to some basic kind of simulation theory but one does have to sort of think through you know computationally and and from a physics point of view and I talked to a lot of physicists about this what is really underpinning the nature of reality which in my opinion is the ultimate question and so yeah all for me all the paths lead to that to that question.

让我问你一点关于 AI 和创造力的问题，因为我认为你知道我们已经看到了艺术家和他们的工具方面的巨大变化。你认为随着我们向前发展，新的创作过程会是什么样子？

Let me ask you a bit about AI and creativity because I think you know we've already seen so much change in the way that sort of the artist and their tools as it were. What do you think the new creative process will look like as we go forwards in the future?

嗯，这很有趣，我想我一直在观察。我们尝试构建工具。所以我们走了一条与一些竞争对手不同的路，我们尝试与顶尖艺术家合作构建工具，这些艺术家是他们领域的佼佼者。这样他们在我们设计这些东西时就能告知我们。他们想要什么？他们需要什么？什么会在他们的创作过程中帮助他们，而不是妨碍他们。所以我们与像达伦·阿罗诺夫斯基这样的人以及来自各个不同创意领域的顶尖音乐家合作，游戏设计师，比如我们与制作《EVE Online》的冰岛公司合作。所以所有不同的创意追求，我们都尝试与这些领域的几位顶尖创作者合作，而且很早就开始，这样我们可以与他们一起定义这些工具最终会做什么。

Well, it's very interesting and I think I've been observing it. We've tried to build tools. So we've gone a different path for some of our other competitors where we've tried to build tools in collaboration with top artists who are the top of what they do. So they can inform us while we're designing these things. What do they want? What do they need? What will help them in their creative process versus get in the way. And so we work with people like Darren Aronofsky and top musicians from every different creative field, games designers like we've partnered with the Icelandic company that builds Eve Online. So all the different creative pursuits we've tried to partner with several top creators in those areas and really early on so that we can work with them to define what these tools are going to end up doing.

我认为到目前为止，就像任何技术一样，它们可以用于真正提升人类的事物，但也可以用于不太好的事物。我想我们在 AI 上又看到了这种情况，对吧？所以有 AI 垃圾内容这个概念，它只是有点创意平庸或创意上不有趣，但它的存在是为了在几秒钟内吸引观众。我认为我们真的不想朝那个方向发展，理想情况下，尽管你知道，也许作为轻娱乐还可以。但另一方面，你有惊人的工具可以用于原型设计。所以我看到伟大的艺术家现在可以经历、迭代比以往更多的想法，并在投入太多资源之前尽早测试它们，以找到他们真正想要支持或投入的想法。所以我认为这对已经处于顶尖水平的人来说很棒。所以他们喜欢这方面，这也使他们能够做事情，因为也许更便宜或更快。这可以让他们做一些否则无法承担的创意项目。他们本来不会获得资金或资源来做。但另一个令人兴奋的事情是，你知道，下一代崭露头角的艺术家，他们能够更快地取得突破进入专业世界，因为他们可以，比如，不只是，你知道，整理一个关于你可能想拍什么电影的幻灯片，你实际上可以，你知道，创建一个原型，或者，你知道，甚至一个短预告片来展示你试图做的事情。所以，我认为这仍然有待塑造，我能看到积极和消极的一面，我认为这取决于我们和创意社区尝试将其推向积极方向。但我也认为我们将不得不回答，未来我们会欣赏什么，这可能会迫使我们更具体地定义我们每天使用的术语，如工艺、直觉、作品灵魂。我相信所有这些概念，但确切地说它们意味着什么？我认为我们将不得不更仔细地定义这些东西，我认为在这个新时代我们将能更好地理解它们。

And I think what I've seen so far, just like any technology, is they can be used for things that are really enhancing to humanity, but they can also be used for things that are not great. And I think we're seeing some of that again with AI, right? So there's this notion of AI slop, which is just sort of, you know, kind of fairly creatively mundane or not interesting creatively, but it's there to kind of hook an audience for a few seconds. And I think we don't really want to be going in that direction, ideally, although, you know, maybe it's fine as kind of light entertainment. But then on the other side of the ledger, you've got amazing tools that you could use for prototyping. So what I've seen great artists do is now they can go through, iterate through many more ideas than before and test them out early before committing too many resources to find the idea that they really want to back or commit to. So I think that's great for the people already at the top of their game. So they love that aspect of it, and it also enables them to do things because maybe it's cheaper or quicker to do. They could enable them to do some creative projects they couldn't have undertaken otherwise. They wouldn't have got the funding or the resource to do. But the other exciting thing is, you know, the next up-and-coming artists, they're able to maybe make breakthroughs quicker into the professional world because they can, like, instead of just, you know, putting together a slide deck about maybe what film you want to make, you could actually, you know, create a prototype or, you know, even a short trailer of what you're trying to do. So, I think there it's still all for that to be shaped, and I can see the positives and negatives, and I think it's up to us and the creative community to try and push it in a positive direction. But I think we're also going to have to answer what is it that we are going to appreciate in the future, and it'll probably force us to be a little bit more specific about terms we use every day like craft, intuition, the soul of a piece. I believe in all those concepts, but what does it mean exactly? And I think we're going to have to more carefully define those things, and I think we'll be able to understand them better in this next era.

嗯，我也认为这其中有些关于我们如何定义自己的东西，你知道，因为我认为在很长一段时间里，我们一直认为人类认为我们自己在这个地球上重要的原因是我们可以解决复杂问题。我们可以有，你知道，独创性。我们可以有创造力。但现在我们看到机器在所有这些追求上越来越好，我想知道人类在未来将如何定义自己。

Well, I also think there's something in this about how we define ourselves, you know, because I think for a really long time, we've thought humans have thought of ourselves as like the thing that makes us, you know, important on this earth is that we can solve complex problems. We can be in, you know, have ingenuity. We can be creative. But now that we're seeing machines getting better and better and better at all of those pursuits, I wonder how humans will define themselves in future.

是的，我认为我们将看到两个时期。所以未来 10 年左右，我认为我们将看到创造力的惊人繁荣，因为我们将拥有这些惊人的工具，最优秀的人类创意科学家或艺术家可以用它们来将他们产出的东西提升 10 倍，对吧？所以我认为这将是下一年。我认为这将非常惊人。但之后，这些工具可能会继续变得更好、更自主。然后问题是，你知道，之后会发生什么？我怀疑，但我认为这又是由社会来塑造的，人类的联系、人类的创造力、人类的工艺和灵魂将比以往任何时候都更重要。这是我猜测将会发生的事情。就像我们，你知道，我们仍然欣赏古代大师和原创艺术，而不是，嗯，你知道，我们今天可以复制它很多次，但我们不，我们不那么欣赏它。问题是，会发生什么？我认为其中一部分是人类的工艺、努力和纪律，这些是成为伟大的钢琴家、伟大的棋手、伟大的数学家、伟大的艺术家所必需的。但如果有一些捷径呢？那么你就不能通过投入的努力来定义它。所以我认为我们需要集体努力，当我真正说我们要重视什么、我们将什么视为美德、我们将欣赏、认可和庆祝什么时，我是认真的。根据这些事情，像这样的庄严社会将引领下一代，你知道，我们的孩子将在这种技术中土生土长，他们将能够做不可思议的事情，但作为社会，我们将鼓励哪些事情作为这些事物发展的正确方向？这适用于我们创造的新的互动体验等一切。我想我们可以，我可以想象一个世界，我们创造真正有益健康的东西，滋养和连接人们，实现正和，而我可以想象如果我们让事情不受约束，我们只是从，你知道，有点上瘾的筒仓开始，对吧？我认为我们在社交媒体上看到了这一点。如果你只是把它留给技术，它就会随着资本主义的发展而发展，资本主义很棒，顺便说一句，显然，它推动进步，但它需要一个覆盖层，你知道，哲学、社会覆盖层，比如，我们真正想要什么？我认为我们需要对这项技术非常有意，我们想要它做什么，因为它可能几乎可以促进任何事情。所以这是好消息。我认为未来真的还没有写定，我不相信任何说它已经写定的人。任何技术专家，他们不知道。我可以告诉你，我们不知道会发生什么。没有人知道，任何告诉你他们知道的人，他们要么在撒谎，要么有不可告人的动机。这仍然有待确定。所以这是好消息，对吧？但我们必须，你们所有人和我们所有人来自不同领域都必须参与进来。认真对待它。它不会回到盒子里。它不会消失。但有许多惊人的事情可以发生，也有一些不太好的事情。我的意思是，从技术上讲，我们必须确保随着它们变得更自主等，它们是安全的。存在技术风险。然后但即使我们技术正确，我们也必须考虑它。我们能否正确处理它的经济学，让每个人都分享其中？我们能否正确处理哲学观点？我认为这影响一切。你知道，我看到托马斯和在座的其他建筑师，从我们的物理世界到我们的艺术世界再到我们的哲学世界。你知道，一切都会改变。但这种改变可能是好的。我，但我们必须有意识地去确保它是好的。

Yeah, it's, I think there's going to be sort of two periods we're going to see. So the next 10 years or so, I think we're going to see an incredible flourishing of creativity in the sense we'll have these amazing tools that the best human creative scientists or artists can use to 10x what they produce, right? So that I think is going to be the next year. It's going to be pretty amazing, I think. But then after that, these tools might continue to get better and more autonomous. And then the question is what happens, you know, after that? I suspect, but I think again it's for society to shape that the human connection and the human creativity and the human craft and soul will be more important than ever. That's what I'm guessing is going to happen. In the same way that we, you know, we still appreciate the old masters and the original art versus, um, you know, we could copy it many times today, but we don't, we don't appreciate that as much. The question is what's going to happen though? I think part of that is the human craft and effort and discipline that's gone into being a great piano player, a great chess player, a great mathematician, a great artist. But what if there's some shortcut to that? So then you can't define it by the effort that has gone in. So I think we will need to collectively work out what I really mean it when I say what are we going to value, what are we going to consider to be a virtue, what are we going to appreciate and recognize and celebrate. And depending on those things and august societies like this that will then lead the next generation, you know, our kids who are going to be growing up with this technology native, they'll be able to do incredible things, but what sorts of things are we going to encourage as society as the right direction for those things to be built in? And that's true of everything from the new interactive experiences we create. I think we could, I can imagine a world where we create really wholesome things that nurture and connect people and a positive sum, versus I can imagine if we let things go unfettered, we just start with, you know, sort of addictive silos, right? I think we've seen that with social media. If you just leave it to the technology, it will just go with wherever capitalism takes it, and capitalism is amazing, by the way, obviously, it powers progress, but it needs an overlay over it about, you know, philosophical, societal overlay of like, well, what do we actually want intentionally? I think we need to be very intentional about this technology of what do we want it to do, because it could probably facilitate almost anything. So that's the good news. I think the future is really not written, and I don't believe anyone who says it is. Any technologist, they don't know. I can tell you we don't know what is going to happen. Nobody does, and anyone telling you they do, they're lying or they're doing it for ulterior motives. It's still to be determined. So that's the good news, right? But we have to, you all and we all from different parts of have to get involved. Take it seriously. It's not going back in a box. It's not going away. But there are many amazing things that can happen with it, and there are not some, some not so good things. And I mean that technically we got to make sure it's safe as they get more autonomous and and so on. There's technical risks. And then but we got to think about it even if we get the technology right. Are we going to get the economics of it right so everyone shares in it? And are we going to get the philosophical points right? And I think this affects everything. And you know, I see Thomas and other architects in the room from our physical world to our artistic world to our philosophical world. You know, it's all going to change. But that change could be good. I, but we have to be intentional about it to make sure that it is.

正如你所说，站在奇点的山脚下，这种变化确实让人感到相当可怕，对吧？有如此多的潜力和可能性。但我也知道，每次和你交谈后，我都会带着一种新的乐观感离开，觉得事情可能会如何发展。所以，也许在观众提问之前，我的最后一个问题是：给我们描绘一下我们可以追求的目标。未来尚未写就，但它能有多好？

And I think as you say, standing in the foothills of the singularity, that change does feel like quite a scary thing, right? With so much potential and so much possibility. But I also know that every time I get to talk to you, I walk away with a renewed sense of optimism for how things could possibly turn out. So maybe as my last question before we come to the audience, paint us a picture of what we could be aiming for. It's not written yet, but how good could the future be?

嗯，我认为未来最好的版本是我们拥有这些不可思议的新工具，我们谨慎而明智地将它们引入世界，并深思熟虑地这样做，从而在科学和医学领域实现不可思议的新进展。所以我们解决一些可怕的疾病，也许最终解决所有疾病。我们想出更好的材料、新的能源，真正帮助环境，对吧？我们解决核聚变、量子计算机等问题。然后这解决了很多当今重大的社会挑战，从环境到水资源获取，再到一般资源。所以那可能非常了不起。我们将进入一个富足的世界，然后这解锁了诸如真正的太空旅行之类的事情，因为现在真的取决于如何制造燃料，这是一个能源问题。所以很多这些问题可以通过解决特定根节点来解决。然后我们可能进入一个人类最大繁荣的新时代。但我们必须处理好经济和哲学方面，那将是那时最大的挑战。还有目的和价值的观念，以及我今晚提到的一些事情，这些将是更大的挑战。但从艺术的角度来看，我们也可以解锁新的审美判断和精致水平。没有理由——我们开场时讨论过——我们的大脑是为狩猎采集而进化出来的，对吧？然而我们在这里欣赏美术、创作美术、建筑等物理事物以及科学等惊人技术。所以那不是极限。也许有新的艺术形式等待发现，我认为这些工具以正确的方式使用将帮助我们发现那个新世界。这就是为什么我称之为科学发现和奇迹。所以我认为它可能非常了不起。而且我认为即使在那里，最好的蓝图来自艺术，来自一些惊人的科幻小说。在座的任何科幻作家或编剧，你们知道我们需要更多好的北极星例子，这些例子基于科学、硬科学。所以它们是合理的、可能可行的，但它们是好的北极星。对我来说，在我成长过程中，是阿西莫夫的《基地》系列。是伊恩·班克斯的《文化》系列真正启发了我认为人类可以达到的惊人世界或宇宙。

Well, I think the best version of the future would be one where we have these incredible new tools that we carefully and sensibly steward into the world and thoughtfully do that, that enable incredible new advances in science and in medicine. So we solve some terrible diseases, maybe all of them eventually. We come up with better materials, new energy sources, so we really help with the environment, right? We solve fusion, other things, quantum computers. Then that resolves a lot of things that are big societal challenges today, from the environment to water access to resources in general. And so that could be amazing. So we'll enter a world of abundance, and then that unlocks things like proper space travel, because really it's down to how do you create the fuel now, which is an energy problem. So a lot of these things can be fixed with solutions to particular kind of root nodes. And then we potentially enter a new era of maximum human flourishing. But we have to get the economics and the philosophical side right, which will be the biggest challenges at that point. And the idea of purpose and value, and some of the things I mentioned this evening, those are going to be the bigger challenges. But from the arts perspective, we could also unlock new levels of aesthetic judgment and refinement potentially. There's no reason—we sort of open by discussing this—our brain was invented for, evolved for hunter-gathering, right? And yet here we are appreciating fine art and creating fine art and physical things like architecture and amazing technologies like sciences. So that's not the limit. Maybe there are new forms of art to be discovered, and I think these tools used in the right way will help us discover that new world. That's why I call it scientific discovery and wonder. So I think it could be amazing. And I think even there the best blueprints for that come from the arts, from some amazing science fiction. And any of you who are science fiction writers in the room or script writers, you know what we need is more examples of good north stars that are grounded in science, hard science. So they're plausible and potentially doable, but they are good north stars. And for me, when I was growing up, it was Asimov's Foundation series. It was Ian Banks's Culture series that really inspired the sorts of world or universe that I thought could be amazing for humanity to get to.

我的意思是，除了其他一切，Demis，你在展示为什么 RSA 如此重要方面做得非常出色。所以我确信他们为此感谢你。

I mean, you've alongside everything else, Demis, you've done a really great job of demonstrating why the RSA is so important. So I'm sure they thank you for that.

正是。正是。

Exactly. Exactly.

好的，我们有一些观众提问。Kate，你在哪里？这里。

Okay, we have a few questions in the audience. Kate, where are you? Here.

谢谢，Kate Far，国家剧院的联合首席执行官。谢谢。那完全引人入胜。你非常有说服力地谈到了你与艺术家们合作，思考 AI 如何增强创造力而不是取代它。所以我想问一个问题：你认为人类叙事中是否有任何不可计算的元素？如果有，我们如何在急于创新和采用的过程中保护它们？

Thank you, Kate Far, the co-chief exec of the National Theater. Thank you. That was completely fascinating. You talked really convincingly about the work you've been doing with artists to think about the ways that AI can enhance creativity and not replace it. And so I think I'd love to ask a question about how you think or whether you think there are any elements of human storytelling that are non-computable and if so how we could go about protecting them in the rush to innovate and adopt.

是的，好问题。嗯，我认为这实际上是一个开放的科学问题，对吧？所以我会称之为经验性问题，即我们与计算机的极限是什么，大脑可能在做不同的事情。这就是为什么我想研究神经科学的部分原因，因为我对这些差异着迷。我一直相信，构建像 AI 这样的智能人造物，然后将其与人类思维进行比较，将是我们找出人类思维中剩余的特殊或甚至独特之处的最佳方式。这是一个公开的辩论。如果你和罗杰·彭罗斯这样的人交谈，他会谈论大脑中的量子效应和量子意识的概念。如果那是真的，那么经典计算机、今天构建的 AI 机器将无法做到那些事情，对吧？不幸的是，在那一边，我不确定我同意他。所以我认为到目前为止没有证据。我站在艾伦·图灵这一边，即可能我们能够做的大多数事情，即使我们不确定我们如何做，最终将是可计算的，被证明是可计算的。所以如果那是真的，那么也许机器最终能够做其中一些事情，如果给它们足够的输入和数据。这并不一定意味着它会更好，因为什么是更好？所以有些东西像下棋或围棋，你可以衡量——它们比另一个玩家更好吗，它们比人类冠军更好吗等等。但我认为在创意世界中，没有那种线性意义上的更好。所以它们只是不同。然后我认为这归结为对另一个人来说什么更有意义。我在这里总是举的例子是，为什么我们对某些故事费心——无论是电影还是书——有时它像是基于真实故事，对吧？那么如果那个短语没有意义，我们为什么要费心呢？我认为是因为在那些特定的故事中，知道另一个人经历过那件事，实际上经历过那件事，对观众来说更有意义。所以那有一些附加效应，对吧？我假设否则你为什么要提到它是否是真实故事。所以那永远不会适用于 AI 创作的艺术作品，对吧？所以你会与艺术家有那种联系，就像当我看着一幅惊人的梵高或其他作品时，你可以在每一笔刷中看到他的痛苦，对吧？他画作的每一笔。如果 AI 机器人能够做到那样，那还会有意义吗？可能不会。可能对我们作为 fellow 人类来说永远不会。但这是需要在哲学上解开的东西，我认为。

Yeah, great question. Well, I think that's an open scientific question actually, right? So I would call it an empirical question in the sense of what are the limits that we have with computers, that the brain may be doing something different. And that's partly why I wanted to study neuroscience because I was fascinated about the differences. I actually have always believed that building an intelligent artifact like AI and then comparing it to the human mind will be the best way for us to work out what remaining things are special or perhaps even unique about the human mind. This is an open debate. If you talk to someone like Roger Penrose, he will talk about quantum effects in the brain and the idea of quantum consciousness. If that's true, then classical computers, AI machines as they're built today won't be able to do those things, right? Unfortunately, on that side, I'm not sure I agree with him. So I don't think there's any evidence so far. I'm on the side of Alan Turing here, which is that probably most of the things we're able to do, even though we're not sure how we do them, will eventually be computable, shown to be computable. So if that's true, then maybe machines will eventually be able to do some of these things if they're given enough inputs and data. That doesn't necessarily mean it'll be better because what is better? So there are some things like playing chess or go which you can measure—are they better than the other player, are they better than the human champion and so on. But I think in the creative world there isn't that notion of better in some linear fashion. So they'll just be different. And then I think it comes down to what's more meaningful to another human being. And the example I always give here is why do we for some stories bother—whether it's a film or a book—sometimes it's like based on a true story, right? So why would we bother with that phrase if it didn't have some meaning? I think it's because in those particular stories it's more meaningful to the audience to know that another human being went through that, actually went through that. So then that has some additive effect, right? I assume otherwise why would you mention whether it was a true story or not. So that will never be true of an AI created piece of art, right? So you'll have that connection with the artist in the way when I look at an amazing Van Gogh or something, you can see his pain in every brush stroke, right? Every stroke of his paintings. Would that be so meaningful if an AI robot was able to do that? Probably not. Probably never for us as fellow human beings. But this is what needs to be unpacked, I think, philosophically.

我们有另一个来自 Thomas 的问题。

We have another question from Thomas.

你好。

Hello.

我是 Thomas Heatherwick，我们的设计师、建筑设计师。只想说，看到你这份乐观，以及你身处伦敦——英国的首都，当下这里弥漫着许多不乐观的情绪——真令人振奋。我认为你带来了很多希望和兴奋，而我们根本不够乐观。你决定不把基地设在加州，我认为这对英国来说是极好的，也体现了英国人——我认为是英国最好的一面——那种古怪。而你毫无疑问是个严肃的怪人，而这恰恰是最理性的状态。但我的问题只是：与此同时，那些本可以带你去加州的惊人飞机、卫星和非凡成就，我们在城市方面却没有做出什么了不起的事情。我们在世界各地大规模地制造着真正的灵魂缺失。同时，数字革命的早期阶段在许多方面都令人难以置信，但它也在制造我认为 Noreena Hertz 在她的书中所说的‘孤独世纪’，这种脱节以及人们彼此之间的有毒行为。回到你关于健康的话题，我认为这是一个绝佳的机会，不再把建筑仅仅视为个体艺术品，而是把我们周围的建筑视为公共健康。我很好奇，你如何看待这些——你正在英国、伦敦市中心解锁的——潜力，即我们如何能像你这样对建筑充满热情的人一样，从根本上人性化我们周围的建成世界。

It's Thomas Heatherwick, our designer, architectural designer. Just wanted to say how thrilling it is to have this optimism from you and you existing here in London, in the capital of the UK, where there's a lot of non-optimism at the moment. And you give, I think, a lot of hope and excitement. And I think we're not optimistic enough at all. And your decision to not base yourself over in California has been, I think, brilliant for the UK and reflects British—what I think is the best of British—which is eccentricity. And you are no question a serious eccentric, which is the most rational thing to be. But my question was just: at the same time as the amazing planes that could have taken you to California and satellites and the phenomenal achievements, we have not been doing incredible things with our cities. And we've been making real soullessness at scale everywhere in the world. And at the same time, the earlier part of the digital revolution has been incredible in so many ways, but it's also making what I think Noreena Hertz in her book called 'The Lonely Century' and this disconnection and people's toxic behavior with each other. And back to your thing of health, I think this is a great opportunity to stop thinking of buildings just as individual artworks, but buildings around us as public health. And I'm fascinated as to what you see the potential is with these sorts of—which you are unlocking here in Britain, in the heart of London—for how could we radically humanize the built world around us with someone like you who's passionate about buildings at the same time.

是的。感谢 Thomas 提出这个问题，也感谢我们那些令人惊叹的新建筑。你知道，这非常鼓舞人心，我坚信你的物理空间能激发你下一层次的创造力。所以我一直认为这无比重要。正如我们讨论过的，我认为需要对物理世界和建筑做些事情，尤其是在大城市，让它们鼓舞人心。而我们不知怎么地失去了这一点，你可以说自二战以来。我最喜欢的建筑类型是装饰艺术。但你知道，在伦敦周围你其实可以看到许多乔治亚风格的美丽演变。然后它就好像停止了，这有点奇怪。它不应该是这样的。我认为，进入一个可能更加富足的时代的好处之一是，我们也许不必仅仅把成本作为唯一的衡量标准，对吧？我们之前讨论过：它不应该是你建造什么的唯一衡量标准。我们还应该考虑其他因素，比如人类健康、人类灵感。这些如何被纳入我们下一个议会住宅或类似项目的设计中？正如我们一直在讨论的，我们可能会在诸如数据中心和与新的 AI 革命相关的其他事物上合作——有很多新建筑正在拔地而起。嗯，也许我们应该多花一点钱，让它们变得美丽。你知道，这些是我们正在建造的新类型的资产。为什么我们不应该——你知道，我们也应该考虑它们对物理环境的影响。所以我对此深信不疑，这也是我未来几年想要花些时间思考的事情之一：这些新类型技术的积极影响。但如果没有一些严肃的创造性努力，甚至可能是一场新运动，它就不会发生。就伦敦而言，为什么我一直——你知道，我出生在北伦敦，土生土长的伦敦人，我真的很爱英国和伦敦，部分是因为我在这里长大，我喜欢英国人那种有点低调的特质。但我认为我们也应该——美国人做得好的地方是他们有雄心，并且对自己的雄心感到乐观。我认为在欧洲，我们必须拥抱这一点。否则，我们就会被甩在后面。这就是我试图解释的关于 AI 的事情。不要仅仅把它看作——它是有待塑造的，它会发生什么。它将会发生。所以你应该接受这一点，然后利用你的才能在 global stage 上以积极的方式塑造它。你们都有能力做到这一点。你们都在自己的领域有巨大的影响力。然后你可以争论到天荒地老。但实际上，作为我身上工程师的那部分，你总得在某个时候展示出来，对吧？多年来我一直在和人争论蛋白质折叠问题是否可解之类的。有这些辩论是好事，因为它能锤炼你的想法。甚至当我在 MIT 做博士后、创立 DeepMind 时，我在食堂和一些 MIT 的顶尖教授在一起——我不会点名他们是谁——他们说这永远不会成功。你知道，这种新的学习类型的方法，你知道，它永远不会成功。80 年代在 MIT 试过了，没用。你得用逻辑系统。我仔细听了他们的论点，最终它归结为教条。所以没有理由——所以之后我实际上更受鼓舞了。记住，这些是 AI 领域一些最重量级的教授。这也是我做博士后的原因之一，因为我想在他们的地盘上与他们见面，而在我看来，他们没有好的第一性原理来论证为什么它行不通。所以当时我想，好吧，我不确定它会不会成功，但至少我会以一种新的有趣的方式失败，对吧？那就是——这就是你在科学和研究中能期望的全部，对吧？探索一些可能成功的新事物，如果它不成功，你也在为知识添砖加瓦，你知道，为人类知识的墙添一块砖，对吧？我认为这就是你在研究中能期望的全部。我不会——如果它不成功，它会以一种有趣的新方式不成功。所以，我认为你们都必须这样做并拥抱它。我认为这就是我们作为英国可以带来的部分——为讨论带来一点脚踏实地。你知道，因为它可能会滑向过多的炒作等等，但也要有一些同情和共情，关于我们将用这些技术做什么。我认为这也是欧洲的敏感性。但我们必须拥抱雄心和对这将成功的乐观。就像不要只关注——只关注负面是很容易的，对吧？比如，哦，这可能会出错。这可能会出错。是的，但它可能不会。而且在我看来，从这里会发生什么其实都还是未知数。所以，我们需要更多我们这样的人进入乐观的空间。我认为伦敦特别棒，因为有能力像这样聚集在一起。

Yes. Well, thanks Thomas for that question and also thanks for our amazing new buildings. You know, it is very inspiring and I'm a big believer in your physical spaces inspiring your next level of creativity. So, I've always thought that's unbelievably important. And as we've discussed, I think something needs to be done about the physical world and architecture, especially in big cities, to be inspiring. And we somehow lost that since, you know, you could argue since World War II. And my favorite type of architecture is art deco. But you know you can see many beautiful evolutions of that Georgian all around London actually. And then it's kind of stopped and it's sort of strange why that is. And it shouldn't be like that. And I think one of the benefits of entering maybe an era where there's more abundance is we might not have to just use the cost as the only measure, right? And we've discussed this before: it shouldn't be the only measure of what you build. There should—we should also factor in other factors about human health, human inspiration. How is that being factored into our next design of the next council estate or whatever that is. And as we've been talking about, we'll probably collaborate on things like—there's a lot of new buildings going up like data centers and other things to do with the new AI revolution. Well, maybe we should just spend a little bit more and make them beautiful. You know, these are the new types of assets that we're building. Why should we not—you know, we should be thinking about their effect on the physical environment as well. So I'm a huge believer in that and that's part of what I want to spend some of my next few years thinking about as well: the impact—positively—of these new types of technologies. But it won't happen without some serious creative effort and maybe even a new movement. And just to talk about London and why I've always—you know, I was born in North London and, you know, London born and bred and I just really love the UK and London, but partly because, you know, I grew up here and I like this a little bit of understatedness of Britishness. But I think we should also—the thing the Americans do well is they're ambitious and they're optimistic about their ambition. And we have to embrace that, I think, in Europe. Otherwise, we're just going to get left behind. And this is what I'm trying to explain about the AI thing. Don't just view it as—it's to be shaped, what happens with it. It's going to happen. So you should just make peace with that and then use your talents to shape it in a positive way on the global stage. You're all capable of doing that. You've all got big impacts in your domains. And then you can argue till the cows come home. But actually, and this is the engineer part of me, you just got to show it at some point, right? I was arguing with people for years about is the protein folding problem solvable, whatever. And it's good to have those debates because it hardens your ideas. And you even—when I set up DeepMind, I was doing my postdoc at MIT. I was in the cafeteria with some of the top professors at MIT—I won't name who they were—and they were saying this will never work. And you know, this new learning type of approach, you know, it will never work. It was tried in the 80s at MIT, didn't work. You got to go for logic systems. And I listened very carefully to their arguments and it just boiled down to dogma in the end. So there was no reason for—so I was actually even more encouraged after. And bear in mind these are some of the biggest professors in AI. It's one of the reasons I did my postdoc because I wanted to meet them on their turf and they didn't have good—in my view—first principles arguments why it wouldn't work. So then I was like, well, I wasn't sure it was going to work, but at least I would fail in a new interesting way, right? That—and that's all you can hope for in science and research, right? Explore something new that could work, and if it doesn't work, you're adding to the knowledge, you know, the brick to the wall of human knowledge, right? And that's all you can hope for, I think, in research. I wasn't going to—I was going to fail in—if it was going to not work, it was going to not work in an interesting new way. And so, I think you've all got to do that and embrace that. And I think that's the part that we can bring as the UK is a bit of groundedness to the discussion. There's just, you know, because it can tip over into too much hype and so on, but also some compassion and empathy about what we're going to use these technologies for. I think that's also the European sensibility. But we got to embrace the ambition and the optimism that this will work out. Like just don't only focus—it's very easy to just focus on the negatives, right? Like, oh, this could go wrong. This could go wrong. Yeah, but it might not. And it's actually all up for grabs in my opinion what's going to happen from here. So, we need more of us to get into the optimistic kind of space. And I think London specifically is great because of the ability to gather like this.

在美国，如果你做金融，你在纽约。如果你从政，你在华盛顿。如果你做科技，你在旧金山。如果你做娱乐，你在洛杉矶。而在伦敦，我们有一座城市把所有这一切融汇在一起的熔炉。所以如果多学科——如果你认同我关于多学科很重要的想法——我认为伦敦是世界上最跨学科的城市，你可以在同一个地方和科学、建筑、艺术领域的世界顶尖专家交谈。而且我认为，这是 RSA、皇家学会和皇家工程院可以运用的召集力。我不认为在世界其他地方能轻易做到这一点，达到最高水平。

So, in the US, if you're in finance, you're in New York. If you're in government, you're in DC. If you're in tech, you're in San Francisco. And if you're in entertainment, you're in LA. In London, we have a melting pot of one city that has all of that together. So if multidisciplinary, if you believe my thought of like multidisciplinary is important, I think London is the most multidisciplinary city in the world where you can talk to world-leading experts in science, architecture, art all in one place. And again, this is something RSA and the Royal Society and the Royal Academy of Engineering can use as convening power. And I don't think you can do that easily anywhere else in the world at the highest level.

明白我说的意思了吧，跟 Demis 聊天会让你对未来感觉更好。好。我知道你们很多人有大量问题想问 Demis，我可能会让你们留到喝酒时再问。我们有最后一个问题，来自 Usha。你在哪儿？

See what I mean by how talking to Demis makes you feel better about the future. Okay. I know loads of you will have tons of questions that you want to ask Demis, which I may get you to hold off for on the drinks. We have one last question from Usha. Where are you?

我在这儿。我来问。

I'm here. I'll have it.

我是 Usha。我是上议院的独立议员。首先，请允许我衷心感谢你这场非常鼓舞人心、令人振奋且乐观的演讲，我很喜欢你阐述的方式，包括在挑战等方面。但我想问一个比较实际的问题，因为你看到了我们如何以非常积极的方式运用 AI 的潜力，但我担心的是，我们如何确保真正把这种积极的态度融入我们的教育体系，并发挥其潜力，因为有很多关于儿童认知发展会怎样的讨论。但听你讲讲这个框架会非常有用，以及我们现在该怎么做，才能确保真正实现你所说的那种潜力。

I'm Usha. I'm an independent member of the House of Lords. Can I first of all say thank you very much indeed for a very inspiring, encouraging and optimistic talk, and I'd like the way you framed it because in terms of the challenges and so on. But can I ask rather a practical question, because you see the potential of how we can harness AI in a very positive sense, but what I'm concerned about is that how do we ensure that we actually infuse our education system in a way which talks about it very positively and harnesses the potential, because there's a great deal of talk about what is going to the cognitive development of children and so on. But it'd be very useful to hear from you the framing and what do we do now to ensure we actually realize the potential the way you've been talking about it.

是的，这是个非常重要的问题。我不知道你会不会喜欢我的答案，但我认为教育必须发生相当激进的变革。这是第一点。也许它本来就需要变革。我认为，我们谈论的是一个有 50 年历史的战后体系，我认为它无论如何都需要更新。我在 90 年代上学的经历，还有我父母在职业生涯后期也做过一些教学，教那些落后的孩子。他们曾经为学校里落后和超前的孩子上晚间课。而当今学校体系的问题在于，它迎合的是中等水平。所以如果你不在那个水平，你就得不到真正的照顾。聪明的孩子、有天赋的孩子没有被充分推动，然后他们就分心了；而落后的孩子又没有得到足够的帮助。

Yeah, that's a really important question. So I don't know if you're going to like my answer, but I think something pretty radical has to happen with education. That's the first thing. Maybe it needed to anyway. I think, again, we're talking about a 50-year-old post-war system that I think needs updating anyway. My experience of school in the '90s, and my parents did some teaching as well later in their careers, of kids that were behind. So they used to teach evening classes for kids that were behind and ahead at school. And the problem with the school system today is it caters for the medium. So if you're not in that, then you're not really catered for. The smart kids, the talented kids are not pushed enough and then they get distracted, and then the kids behind, they're not helped enough.

所以我认为另一点是，这又回到我对 Thomas 的回答——我们必须——这件事正在发生，AI 革命无法被阻止，对吧？就像潮水一样。它就是要发生。它会奏效。你应该假设如此。但尚未确定的是，它会变成什么样。所以要么我们——你作为一个国家，或者我们作为个人——只能担心那些悲观的事情，试图挡住潮水。你不会成功的。中国和美国无论如何都会做，不管我们这里做什么，首先就是这样。然后它就替我们塑造好了。要么我们可以试着投入进去，按照符合我们信念和价值观的方式去塑造它。我认为这就是每个人都需要进入的心态。这就是我所处的心态。我某种程度上已经接受了。它会很混乱，也不完全是我 20 年前计划的样子，因为它比我预想的更早商业化了。我本会先做更多科学性和 AlphaFold 类型的事情，然后再去做更商业化的聊天机器人。但事情已经发生了，我们会更快地取得进步，但风险也会更快到来。

So I think the other thing is, again, this goes back to my answer to Thomas about we've got to — this is happening, the AI revolution that can't be stopped, right? It's like the tide. It's just going to happen. It's going to work. You should assume that. But what isn't is shaping what it's going to be. So either we — you as a country, or we as individuals — we can just worry about the pessimistic things, try and hold the tide back. You're not going to be successful. China and the US are going to do it whatever we do here, for starters. And then it gets shaped for us. Or we can try and lean in and shape it the way that fits what we believe in and our values. And I think that's what everyone needs to get into that mindset. That's the mindset I'm in. I've kind of made peace with it. It's going to be messy and it's not quite the way I planned it 20 years ago, because it became commercial earlier than I thought. I would have done more scientific and AlphaFold-type things first, and then gone to the more commercial chatbots. But what happened happened, and we're going to get advances more quickly, but also the risks.

所以回到教育这个话题，我认为我们应该接受，在我看来，我们必须训练我们的孩子和下一代，让他们对 AI 天生熟悉。这就像 90 年代不训练他们使用电脑或互联网一样。如果你那样做，他们就会落后于世界其他地方。而这是他们之后能够胜任——拥有工具、具备技能——去塑造未来的唯一途径。但我们不能那样做。我们必须以一种非常有意识的方式去做，同样，这要有助于学习。

So coming to education here again, I think we should accept that we've got to, in my opinion, train our kids and our next generation to be native with AI. It would be like in the '90s not training them on computers or the internet. They would be behind the rest of the world if you do that. And that's the only way they're going to then be fit — have the tools and be equipped with the skills — to shape the future. But we can't do that. We've got to do that in a very intentional way, again, that helps with the learning.

所以我的想法、我的建议是，也许可以翻转课堂。课堂不再以死记硬背为主。你在课外借助 AI 工具来做这些，因为我认为这正是 AI 工具擅长的地方。而且 AI 工具可以做到个性化。所以如果你在代数或其他什么方面需要多一点帮助，因为你发现那个特定的——AI 工具知道这一点，就会给你更多相关的题目。对吧？所以想象一下，每个人都有一位很棒的个人导师。你可以想象，那些非常擅长讲课或制作教学材料的人——你只需看全国最好的数学老师的 YouTube 视频。为什么每个人——我有很多朋友是数学老师，他们每个人都得制作同样的课堂材料。这在我看来毫无道理。对吧？而且这消耗了大量老师的时间。

So my thought would be, recommendation would be, is potentially invert the classroom. So the classroom doesn't become about rote learning anymore. You do that out of class with the help of AI tools, because I think that's exactly what AI tools are good for. And the AI tools could do it personalized. So if you need a bit more help with algebra or whatever it is because you're finding that particular — the AI tool knows that and it gives you more questions on that. Right? So imagine everyone having a great personal tutor. You could imagine people who are really good at lecturing or teaching materials — you just watch YouTube videos of the best math teacher in the country. Why does everyone — I've got lots of friends of mine who are math teachers and each of them are having to produce the same class materials. This doesn't make sense to me. Right? And it's using up a lot of teacher time.

那么你在课堂上做什么呢？那应该更像蒙台梭利、基于项目、以人为本——所有我们认为对未来可能重要的东西：创造力、创业精神、团队协作、领导团队、成为团队的一员。我认为这些事情在学校里做起来会非常棒、非常有趣，而且我觉得老师们可能也会更喜欢这样。就换个完全不同的角度去想——它是一个协作空间和项目空间，就像你在牛津剑桥可能遇到的导师制那样，类似的东西。但把它带进来——或者也许是蒙台梭利学校。我没上过蒙台梭利学校，所以我不知道那具体是什么感觉，但那种方式我认为我们需要去探索。

So then what do you do in the classroom? That should be more like Montessori, project-based, human — all the things we think could be important for the future: creativity, entrepreneurialism, working as a team, leading teams, being part of a team. Those things I think could be really amazing and fun to be done in school, and I think the teachers would prefer that, probably. And just think about it really differently — it's a collaborative space and a project space, like you maybe get in Oxbridge with the supervision system, something like that. But bring that — or maybe Montessori schools. I didn't go to a Montessori school, so I don't know exactly how it feels, but that type of approach I think we need to explore.

好了，女士们先生们，我们超时了几分钟，但我相信没人介意，因为听 Demis 讲话真是太精彩了。请和我一起，最后再给 Demis 一轮掌声——

Well, ladies and gentlemen, we have run over by a few minutes, but I'm sure nobody minds because it has been absolutely fascinating to hear from you, Demis. Please join me in giving one last round of applause for