in the way science is done.

在科學完成的方式。

Not only tackling the problem of climate change

不僅要解決氣候變化的問題

and trying to find solutions,

並試圖找到解決方案。

but also actually trying to understand the system itself.

但實際上也在努力瞭解這個系統本身。

So some of the technological advances that we might be able to use

是以，我們可能能夠使用的一些技術進步

to combat climate change involve the ability

應對氣候變化的能力包括

to generate energy in sustainable ways.

以可持續的方式產生能源。

The question today is can we make solar panels or other materials

今天的問題是，我們能否使太陽能板或其他材料

that are capable of generating energy in useful ways?

能夠以有用的方式產生能量的？

In the past, scientists and engineers have developed new materials,

在過去，科學家和工程師已經開發了新材料。

but in rather a haphazard way.

但是以一種相當草率的方式。

Thomas Edison created the lightbulb

托馬斯-愛迪生創造了電燈泡

but he developed the original filament

但他開發了原始長絲

by testing thousands of materials to find eventually the one that worked.

通過測試數以千計的材料，最終找到一個有效的材料。

Today we can use machine learning and artificial intelligence

今天，我們可以利用機器學習和人工智能

in our search for new materials.

在我們尋找新材料的過程中。

The reason that we can do it better in the computer

我們之所以能在計算機中做得更好，是因為

is that the computer allows millions of potential solutions

是，計算機允許數以百萬計的潛在解決方案

to be searched in ways that you couldn't do in the lab.

以你在實驗室裡做不到的方式進行搜索。

The reason that AI is important in the development of our understanding

人工智能在我們的理解發展中很重要的原因是

of the Earth's system is that we're getting more and more data

地球的系統是，我們正在獲得越來越多的數據

about the Earth as time goes on.

隨著時間的推移，關於地球。

So today we collect satellite data,

所以今天我們收集衛星數據。

remote sensing observations allow us now

遙感觀測使我們現在能夠

to look at the patterns of landslides.

來觀察山體滑坡的模式。

As climate is changing, as weather patterns change,

隨著氣候的變化，隨著天氣模式的變化。

is the land being more destabilised by excess water?

過量的水是否使土地更加不穩定？

Or are the erosion patterns in the mountains

還是山區的侵蝕模式？

changing as climate changes?

隨著氣候的變化而變化？

Extreme weather events as a result of climate change

氣候變化導致的極端天氣事件

do appear to be on the increase.

看起來確實在增加。

But there's another aspect of this - cities are getting bigger,

但這還有另一個方面--城市正在變得更大。

areas that have always been vulnerable to natural hazards.

一直以來都很容易受到自然災害影響的地區。

With so many people potentially at risk,

有如此多的人可能面臨風險。

it becomes important to understand the system very quickly.

迅速瞭解這個系統變得非常重要。

Examples include understanding the ways in which

例子包括瞭解以下方式

to respond to a situation.

以應對某種情況。

Where to send the first responders.

將第一反應者送到哪裡。

Which hospital is put on high alert.

哪家醫院被置於高度警戒狀態。

Where to send relief supplies, who needs tents.

在哪裡發送救援物資，誰需要帳篷。

So all of these sorts of disaster relief processes

是以，所有這類救災過程

depend upon information.

取決於資訊。

And we know, as we travel around congested cities,

而且我們知道，當我們在擁擠的城市中旅行時。

that we spend a lot of time sitting in traffic,

我們花了很多時間坐在交通上。

burning energy, getting nowhere.

燃燒能量，毫無進展。

Autonomous vehicles provide routes

自主車輛提供路線

to making transport systems more effective, more efficient,

使運輸系統更有效、更高效。

so that you don't have these waves of static traffic on a motorway.

這樣，你就不會在高速公路上出現這些靜態的交通浪潮了。

That everything is moving at the right speed

一切都在以正確的速度發展

and gets from one place to another in the most effective way,

並以最有效的方式從一個地方到另一個地方。

the most efficient way.

最有效的方式。

That's not something that, as individuals,

這不是什麼，作為個人。

we're very good at planning for ourselves.

我們非常善於為自己計劃。

So if we want to reduce, recycle, reuse, can AI help us?

是以，如果我們想減少、回收、再利用，人工智能能幫助我們嗎？

Well maybe. But it depends upon our motivation.

嗯，也許吧。但這取決於我們的動機。

AI is a tool, it's not a master, and so our responses ultimately

人工智能是一種工具，它不是主人，是以我們的反應最終是

will depend upon our own personal motivations,

將取決於我們自己的個人動機。

and those of the society that we're part of.

和我們所處的社會的人。

But AI and machine learning can help us move in the right direction.

但人工智能和機器學習可以幫助我們朝著正確的方向前進。