we'll see an object in front of us.

我們會看到一個物體在我們面前。

We need to tell whether she is a human,

我們需要判斷她是否是人。

a pile of bricks, or a chair.

一堆磚頭，或者一把椅子。

And even if you tell it is a human,

而且就算你告訴它是人。

we must think, 'What is a human going to do next?'

我們必須思考，'人類接下來要做什麼？

Are you going to turn left?

你要向左轉嗎？

Are you gonna turn right?

你要向右轉嗎？

Going to jump in front of us?

要跳到我們前面去嗎？

[Robot] Hi, so sorry, but you're in my way.

嗨，對不起，你擋住我的路了

Could you please move?

你能不能讓開？

LionsBot, we make professional cleaning robots

LionsBot，我們做專業的清潔機器人

so the cleaners don't have to work so hard.

這樣清潔工就不用那麼辛苦了。

Singapore is the Lion City,

新加坡是獅城。

so the lion is the emblem of Singapore.

所以獅子是新加坡的標誌。

Hence, our robots are LionsBot,

是以，我們的機器人是LionsBot。

and at the heart of every robot,

並且是每個機器人的核心。

there is one grain of sand from Singapore,

有一粒沙子來自新加坡。

and it brings the love and the technology of Singapore

它帶來了新加坡的愛和技術。

to the rest of the world.

向世界其他地方。

We have multiple sensors, each feeding in information

我們有多個傳感器，每個傳感器都能提供資訊

multiple times a second.

一秒鐘多次。

In robots, anyone can put in a lot of sonars,

在機器人中，任何人都可以放很多聲納。

a lot of sensors, but it is how we use them,

很多傳感器，但關鍵在於我們如何使用它們。

how we make intelligent decisions

我們如何做出明智的決定

with that information that counts.

有了這些資訊，才是最重要的。

[Laurence Liew] Where you are is our AI Singapore office.

你所在的地方是我們的人工智能新加坡辦公室。

Singapore has a long history of willing to spend money

新加坡歷史悠久，肯花錢的人很多

to get its citizens to re-skill, deep-skill,

以使其公民重新掌握技能，深。

or upgrade their skills.

或提升自己的技能。

Our mission, really, is to promote the use of AI,

我們的使命，其實就是促進人工智能的應用。

get more researchers to embark on a career in AI,

讓更多的研究人員開始從事人工智能事業。

to do AI research.

來做人工智能研究。

We have one very popular program.

我們有一個非常受歡迎的項目。

We call the AI for everyone,

我們叫大家的人工智能。

and the intent is to demystify AI for the man in the street,

並意圖為大街上的人解開人工智能的神祕面紗。

for everyone in that sense.

從這個意義上講，對大家來說。

When the audience walked out of the auditorium,

當觀眾走出禮堂。

they say, 'Ah, OK, AI is not so scary.'

他們說："啊，好吧，人工智能沒那麼可怕。

AI is actually nothing more than just another piece of code,

人工智能其實不過是另一段代碼而已。

obviously very sophisticated code,

顯然是非常複雜的代碼。

but it is just another IT system or infrastructure.

但它只是另一個IT系統或基礎設施。

[Annabelle Kwok] Hi, I'm Annabelle.

嗨，我是Annabelle。

I founded NeuralBay, which is a software AI company

我創立了NeuralBay，這是一家軟件AI公司。

that looks into image and video processing.

研究影像和視頻處理的。

So I was very lucky to be in Singapore

所以我很幸運地來到了新加坡

where the hackathon scene was slowly starting,

在那裡，黑客馬拉松的場景正在慢慢開始。

and it was still kind of ahead of its time.

而且它還是一種超前的時代。

So when this whole field of image processing came up,

所以當整個圖像處理這個領域出現的時候。

I think that opened a lot of doors for opportunities

我想這為我們打開了很多機會之門。

to not just analyze still photos

不僅僅是分析靜態照片

but also to look at real-life events.

但也要看看現實生活中的事件。

So for example, in traffic flow management in crowded areas,

所以，比如在人流密集區的交通流管理中。

you can help to better direct human traffic.

你可以幫助更好地引導人流。

So we're in our office, and we have a lot

所以，我們在我們的辦公室，我們有很多。

of people walking around.

的人走來走去。

So what we can do with this software is that we can count

所以我們可以用這個軟件做的是，我們可以算出

the number of people in this area,

這方面的人數。

as well as to track their movements.

以及跟蹤他們的行動。

So in recognizing people, it's a very tough problem

所以在認識人的時候，這是一個非常棘手的問題

because when they look away,

因為當他們看走眼時，

can you still recognize that it's the same person?

你還能認出是同一個人嗎？

So Zeldon, if you can just turn around very gracefully.

所以Zeldon 如果你能很優雅地轉過身來的話

So you can see that in this software,

所以你可以在這個軟件中看到。

it still tracks that Zeldon is the same person.

它仍然跟蹤Zeldon是同一個人。

[Laurence] I think when we design AI systems

我認為當我們設計人工智能系統時

or any smart city technology,

或任何智慧城市技術。

ultimately the question to ask is

歸根結底，要問的是

how will it affect the citizen in the country?

它將如何影響國內的公民？

We do have several healthcare related AI projects

我們確實有幾個醫療相關的人工智能項目

that are undergoing, and I think there's lots

正在進行的，我認為有很多的。

of interesting areas where AI could be used in education.

的有趣領域，人工智能在教育中的應用。

When we launched AI for Everyone,

當我們推出AI for Everyone時。

the original target was 10,000 Singaporeans

原定目標是1萬名新加坡人

to be trained in three years.

將在三年內接受培訓。

1-1/2 years down the road, we are already at 7,000.

1年半下來，我們已經達到了7000人。

I told my team can we do 100,000?

我跟我的團隊說我們能不能做到10萬？

Let's go from 10 to 100, all right?

讓我們從10到100，好嗎？

Training the people, the apprentice,

培養人，徒弟。

they again, at eight or nine months,

他們又在八九個月時。

they will go out to the industry.

他們將走出去的行業。

There is an economic implication in that.

這裡面有經濟上的含義。

[Dylan] Singapore has a wide pool of talented engineers.

[Dylan]新加坡有大量的天才工程師。

The government has spent a lot of money developing

政府花了很多錢開發

and training these engineers,

並培訓這些工程師。

so with such a big latency pool of people

所以，在這麼大的延遲池的人。

that we can tap on, why not build in Singapore?

我們可以利用的，為什麼不在新加坡建設？

[Annabelle] In terms of the software,

[安娜貝爾]在軟件方面：

I think the next step would be accessibility to more data

我認為下一步將是獲取更多數據的能力

and also the diversity of data available.

以及現有數據的多樣性。

Most of the open-source data is from the West

大部分的開源數據都來自於西

and not necessarily from Southeast Asia

不一定是東南亞人

because Southeast Asian countries may not necessarily

因為東南亞國家不一定

have the infrastructure to capture that data.

具備獲取這些數據的基礎設施；

So recognizing a woman of color within Southeast Asia,

所以在東南亞範圍內認識到一個有色人種的女性。

the confidence interval might not be as high

信心區間可能沒有那麼高

as recognizing one from the West.

作為承認一個來自西方的。

By doing it and making it available

通過做和提供

for the small enterprises, hopefully that might help correct

為小企業服務，希望這可能有助於糾正錯誤。

some of the cultural bias in technology.

技術中的一些文化偏見。

We don't always have to give back

我們不一定要回報

in terms of time and money,

在時間和金錢方面。

but we can also give back in terms of knowledge and skills.

但我們也可以用知識和技能來回饋。

As for myself, I'm good at building things,

至於我自己，我很擅長造東西。

so why not build things to help people?

那為什麼不造東西來幫助人們呢？