Like, OK, I can make a solar cell without using silicon.

比如，好吧，我可以不用硅來製造太陽能電池。

Or I can grow food very efficiently in a laboratory using fungi or some other approach. So as AI gets into the basic science thing, that it goes beyond just kind of a super smart tuning where you save 10% here, 15% there, to helping you with that fundamental design of the green product.

或者，我可以在實驗室裡利用真菌或其他方法非常高效地種植食物。是以，隨著人工智能進入基礎科學領域，它將不僅僅是一種超級智能調整，讓你在這裡節省 10%，在那裡節省 15%，而是幫助你完成綠色產品的基本設計。

And how concerned should we be about, we're here talking about energy, the extra energy demand that's going to come from the AI boom?

我們在這裡討論的是能源問題，我們應該如何關注人工智能熱潮帶來的額外能源需求？

Is it worth the extra emissions just for the intellectual power that AI can bring to bear on this? Yeah, so the additional electric demand from electric cars as we change that over, or electric heat pumps as we change that over, or steel manufacturing, all of those dwarf even this amazing demand for data centers.

僅僅為了人工智能所能帶來的智慧力量而增加排放量，值得嗎？是的，隨著我們的改變，電動汽車帶來的額外電力需求，或電熱泵帶來的額外電力需求，或鋼鐵製造業帶來的額外電力需求，所有這些都使數據中心的驚人需求相形見絀。

Now, there's lots of ways that we're trying to make the AI computations more efficient.

現在，我們有很多方法來提高人工智能計算的效率。

So we're not using as much energy. So the exact path of does it end up being 3% of electric use or 6% of electric use, it's not going to go above 10%.

是以，我們不會使用那麼多能源。是以，最終是使用 3% 的電力還是使用 6% 的電力，其具體路徑不會超過 10%。

So yeah, it's got to fit in.

所以，是的，它必須適合。

It's got to pay the price.

它必須付出代價。

And those tech companies are probably sensitive to wanting to even pay a bit extra to use green energy of any electrical customers in the country.

而這些科技公司可能會很敏感，甚至願意多付一點錢來使用全國任何電力用戶的綠色能源。

So they'll help push the green technologies forward.

是以，它們將有助於推動綠色技術的發展。

But they're willing to pay somewhat of a premium to get in and be able to say that it's all done without greenhouse gas emissions. So you think on balance, when it comes to emissions, AI will pay for itself?

但是，他們願意支付一定的溢價來參與其中，並且可以說這一切都是在沒有溫室氣體排放的情況下完成的。所以你認為，總的來說，在排放方面，人工智能會為自己買單嗎？

Absolutely. Now, speaking of AI, you've obviously been in this industry for a long, long time.

當然。現在，說到人工智能，你顯然已經在這個行業摸爬滾打了很長時間。

You've seen lots of ups and downs in the tech space.

你在科技領域經歷了很多起伏。

Right now, we are seeing, of course, a tidal wave of money going into AI.

當然，我們現在看到的是一股投入人工智能的資金浪潮。

NVIDIA, for example, recently became the world's most valuable company, albeit briefly.

例如，英偉達（NVIDIA）公司最近成為全球最有價值的公司，儘管時間很短。

When you look at market caps like this, do you worry that we're seeing bubble valuations? I'm not a buyer and seller of tech stocks on a daily basis or anything.

當你看到這樣的市值時，你是否擔心我們看到的是保麗龍估值？我不是每天都買賣科技股的人。

These multiples aren't as high as they were, say, during the internet bubble.

這些倍數並不像互聯網保麗龍時期那麼高。

And the growth is real.

增長是實實在在的。

AI is not pets.com.

人工智能不是 pets.com。

This is something very, very fundamental.

這是非常非常基本的東西。

So don't take my view on any particular stock.

所以，不要把我的觀點用在任何特定的股票上。

But the growth potential, there will be some big winners in this AI space, which is why you see all the leading tech companies, including Microsoft, putting tens of billions of dollars into not just the back end capacity, but re-engineering their applications so that you're far more productive.

但從增長潛力來看，人工智能領域會有一些大贏家，這也是為什麼你會看到包括微軟在內的所有領先科技公司投入數百億美元，不僅用於後端能力，還重新設計了它們的應用程序，使你的工作效率大大提高。