--- author: TED date: '2026-02-13' guest: '' layout: post.njk source: https://www.youtube.com/watch?v=zQY0zf9-WXI speaker: TED tags: - ai-for-climate - environmental-tech - innovation-strategy - ai-ethics title: AI赋能气候行动：Bezos Earth Fund的愿景与挑战 summary: 本次访谈聚焦人工智能（AI）如何成为应对气候变化和自然保护的强大工具。嘉宾Amen Ra Mashariki分享了他从计算机科学背景转向关注实际问题，并加入Bezos Earth Fund的历程。他阐述了基金会以问题为导向，利用现代AI技术寻找和规模化解决方案的策略。访谈深入探讨了AI的创新潜力，特别是‘move 37’所代表的创造性突破，并以Meta的DINOv3模型追踪树木生长为例，说明AI如何驱动‘发明’与‘发现’，解锁新的融资模式。同时，嘉宾也回应了AI对环境的潜在负面影响和‘漂绿’质疑，强调了透明度、精确度以及技术向更节能方向发展的重要性，并展望了AI在‘后果深远的十年’与‘决定性的十年’交汇之际，成为推动全球社区积极变革的关键力量。 insight: '' draft: true series: '' category: ai-ml area: tech-engineering project: [] people: [] companies_orgs: - Bezos Earth Fund - Meta - WRI - NVIDIA products_models: - DINOv3 - ChatGPT media_books: [] status: evergreen --- ### 嘉宾介绍与背景 **Manoush Zomorodi**: 好的。Amen，我只介绍了你履历中最简短的部分。但请给我们讲讲你如何开始与**Bezos Earth Fund**合作，以及你走到今天这一步的轨迹。
Original English **Manoush Zomorodi**: OK. So Amen, I gave this shortest bit of your bio. But tell us the story of how you got to be working with Bezos, your sort of trajectory to being here.
**Amen Ra Mashariki**: 是的。你还是让我脸红了，不过说真的。你问这个问题很有意思，因为我通往**Bezos Earth Fund**的道路，几乎与我们通常认为的，通过采用和使用**AI**来加速**气候和自然解决方案**的路径截然相反。我会用几个要点来解释原因。我——本科、硕士、博士，**计算机科学**，计算机科学家，研究实验室——我经历了这一切。我曾是那种坚信**计算机科学**、你知道的，**算法优化**的计算机科学家之一。但由于几件个人事情的发生，我意识到那只是我实现其他目标的一种机制，那就是产生影响。所以，我开始追逐你刚才提到的问题。我曾是**纽约市的首席分析官**。我们如何在这里解决问题？然后，你知道的，来到**Bezos Earth Fund**，我们如何使用**AI**、**计算机科学**来解决气候和自然问题？所以，我曾是那个“AI在寻找一个问题”的人。而在**Bezos Earth Fund**，我们思考的是先从一个问题入手，理解这个问题，然后寻找利用现代**AI**的方法，以在这个领域扩展解决方案。
Original English **ARM**: Yeah. You still have me blushing, nonetheless. It's really interesting that you asked that question, because my pathway to the Bezos Earth Fund is almost polar opposite to how we think about our pathway to adopting and using AI to accelerate climate and nature solutions. And I'll explain why, really, in some quick points. I -- undergrad, master's, doctorate, computer science, computer scientist, research labs -- did the whole thing. I was one of those computer scientists that believed in computer science, you know, algorithm optimization. Through a couple of personal things that took place, I realized that that was only a mechanism by which I could do other things, which is have an impact. So then I began to chase problems you mentioned here. I was the chief analytics officer for the City of New York. How do we solve problems here? And then, you know, coming to the Bezos Earth Fund, how do we use AI, computer science to solve climate and nature problems? And so I was AI in search of a problem. At the Bezos Earth Fund, we think about starting with a problem first and understanding that problem, and then looking for ways to use modern AI in order to scale solutions in that space.
### AI的创新与发现之路 **Manoush Zomorodi**: 好的，那我们深入探讨一下。你们是如何看待市面上不同的项目的？你们用哪些宏大的想法来引导你们寻找想要资助的对象？
Original English **MZ**: OK, so let's go deeper into that. How are you looking at different projects that are out there? What are sort of the big ideas that you're using to sort of lead you to find what you want to fund?
**Amen Ra Mashariki**: 嗯，在内部，我们有一个**心智模型**来真正实现这一点。我们思考的是**发明与发现**之间的区别。你可以这样理解：望远镜是一种发明，而通过望远镜注意到木星有卫星，这就是发现，对吧？所以对我们来说，当我们审视它时，关键在于我们如何识别出那些宏大、宏大的创新，能够产生影响的创新，从而带来能够影响气候和自然的发现。因此，我们寻找那些能够跨越这个心智模型的项目和努力。
Original English **ARM**: So, internally, we have a mental model that we use to really get there. We think about this difference between inventions and discoveries. And the way you want to think about that is a telescope is an invention, looking through the telescope to notice that Jupiter has moons is the discovery, right? And so for us, when we look at it, it's how do we identify big, big innovations, grand innovations that have an impact such that you can have discoveries that then have an impact in climate and nature. And so we look for projects and efforts that sort of go across that mental model.
### AI的现状与未来愿景 **Manoush Zomorodi**: 那么，在我们进入‘发现’部分之前，我们来谈谈工具。**AI**目前处于什么阶段？我知道有些人可能会想，“什么意思？我们已经到了**ChatGPT 5**了。”但从你的角度来看，这可能大不相同，你认为我们现在处于什么阶段？
Original English **MZ**: So before we get into the discovery part, let's talk about the tool. Where are we when it comes to AI? I know there are some people who might think, "What do you mean? We're at ChatGPT 5." But like from your perspective, much different, where do you think we are?
**Amen Ra Mashariki**: 我可以花好几个小时来谈论数字孪生、地球观测模型、边缘**AI**等等。但有一件事一直让我产生共鸣，那就是一个叫做**Move 37**的概念。**Move 37**是**AlphaGo**在与围棋冠军对弈时，在棋局早期，它的第37步，走了一步让所有专家都觉得反直觉的棋。任何围棋专家都无法理解这一步，但它最终赢得了比赛。所以，**AI**的现状体现在这两个地方。目前，它处于一个根据已知信息回答问题的阶段，对吧？它会取现实的平均值，然后给你答案。而**Move 37**则展现了**AI**如何能够变得有创造力，并实际想出一个从未有人想过的、反直觉的招数。所以，我们真正希望达到的目标是，在气候和自然领域，**AI**能够提供解决方案，那些即使是世界上最顶尖的专家也觉得反直觉，但实际上却非常强大的创造性解决方案。
Original English **ARM**: So I could spend hours talking about digital twins, Earth observation models, edge AI and all of those things. But one of the things that have resonated with me is this concept called move 37. So move 37 was this move that AlphaGo, when playing against Go champion, early on in the game, in its 37th move, did a move that was counterintuitive to all experts. It made no sense to any Go expert, but it was the move that ultimately won the game. And so where AI is, is these two places. Right now, it's at a place where it answers questions based on what it knows, right? It takes an average of reality and then gives you answers. Move 37 was this view into how AI can be creative and actually come up with a move that no one has ever thought of, and it was counterintuitive to use. And so we really want to get to a place where in climate and nature, AI is actually offering solutions, creative solutions that even the world's greatest experts find counterintuitive, but are actually really powerful.
### AI在气候行动中的应用实例 **Manoush Zomorodi**: 你能举一个已经发生并能证明这一点的例子吗？
Original English **MZ**: Do you have an example of something that's maybe happening already that demonstrates that?
**Amen Ra Mashariki**: 嗯，其中一个真正符合我所说的**心智模型**的项目是**Meta**提出的一个**AI**创新发明，叫做**DINOv3**，这是一个非常强大的计算机视觉模型。然后他们将其与卫星数据相结合。这是一个非常强大的创新。但他们所做的是与**WRI**合作进行恢复工作，使得你能够以**80%的准确率**追踪树木的生长，其成本仅为实地调查的**3%**。这样，你就可以利用这项技术解锁基于绩效的融资。所以，它遵循了宏大创新和发明的**心智模型**，最终带来了能够产生影响的发现。**Move 37**的全部意义在于，我们还没有达到那个阶段，而那正是我们应该努力的方向。目前存在人们正在使用的恢复解决方案。如果你问**AI**，“告诉我一些在这个特定区域进行恢复的最佳方法”，它会识别出现有良好解决方案的平均值或插值。我们想要的是**AI**能够想出一些房间里的任何人都想不出的方法来解决恢复问题，而这正是我们的发展轨迹。
Original English **ARM**: Well, one of the projects that really goes across this mental model that I talked about is Meta really came up with this AI innovation, invention called DINOv3, which is a computer vision model, very powerful computer vision model. And then they matched it with satellite data. And it's really powerful innovation. But what they did was partner with WRI in its restoration efforts, such that you could actually track the growth of trees to an 80 percent accuracy of field surveys at three percent of the cost. And so now you can actually unlock performance-based financing with this technology. So it followed that mental model of grand innovation and invention, and ultimately a discovery that leads to an impact. The move 37, the whole thing about that is we haven't gotten there yet, and that's where we should be going, which is there are restoration solutions that people are using. And if you ask AI, "Tell me some of the best ways to do restoration in this particular area," what it's going to do is identify an average or interpolation of the existing good solutions. What we want is AI to come up with something that no one in the room can come up with when it comes to restoration, and that's the trajectory.
### AI对环境的影响与挑战 **Manoush Zomorodi**: 这方面的时间线看起来如何？我们如何知道何时达到了那个临界点？
Original English **MZ**: What's the timeline look for that? How will we know when we have sort of hit that tipping point?
**Amen Ra Mashariki**: 首先，专家必须信任并使用它，然后还必须有一种机制，让普通人，那些生活在我们关心的地区，在实地工作的人们，也能信任并使用这些工具。没有人能给你一个确切的数字。它知道需要多长时间吗？但这就是我们必须达到的目标，那种跨越多种人群的信任和使用水平。
Original English **ARM**: One, there has to be trust by the experts and the experts are using it, but then also there has to be a mechanism by which everyday people who are living their lives, who are living in these regions that we're concerned about, who are doing the work on the ground, can trust and use these tools as well. There is anyone who gives you an exact number. Does it know the number, how long it's going to take? But that's where we have to get to, that level of trust and that level of use across a number of types of people.
**Manoush Zomorodi**: 我想确保问你这个问题，因为很多人说，推动**AI**发展的那些科技巨头，也对很多环境危害负有责任，而且他们的气候倡议实际上就是“漂绿”。你对此如何回应？
Original English **MZ**: I want to be sure to ask you, because there are many people who say that the same tech giants who are driving AI are also responsible for a lot of the environmental harms, and that their climate initiatives essentially amount to greenwashing. How do you respond to that?
**Amen Ra Mashariki**: 你知道，在**Bezos Earth Fund**，我们相信总的来说，**AI**将是一种向善的力量和工具，也是拯救地球的力量和工具。我们必须承认，**AI**确实会加剧环境的退化和挑战。许多公司、许多非政府组织、许多学术机构和许多政府都在这个领域应用了大量的解决方案。而我们**Bezos Earth Fund**将继续支持这类努力，以便我们能够有意识地实现那个广泛的论断，即**AI**总体上将对地球产生积极影响。
Original English **ARM**: You know, at the Bezos Earth Fund, we believe that on balance, AI is going to be a tool and a force for good and a tool and a force for saving the planet. We have to acknowledge that AI does contribute to degradation and challenges when it comes to the environment. There are many, many solutions that a lot of these companies, a lot of NGOs, a lot of academic institutions, and a lot of governments are applying in this space. And we will continue as the Bezos Earth Fund to support those type of efforts, such that we are deliberate in meeting that broad statement that AI, on balance, will have a positive impact on the planet.
**Manoush Zomorodi**: 我的意思是，这让我感到紧张，因为这有点像是“让我们祈祷它会奏效”的感觉。我们前进的道路上需要关注哪些里程碑？
Original English **MZ**: I mean, it makes me nervous because it’s like, “Let’s hope it works” a little bit. What are some of the sort of milestones that we need to be looking for as we go forward?
**Amen Ra Mashariki**: 所以，我前几天听了一个小组讨论，有人说：“每次你在**ChatGPT**上进行一次查询，就像把一瓶水扔在地上。”他们一说完这句话，就说：“你知道，我不知道这是否属实，但听起来，你知道，可能属实。”我们开始需要做的一件事是，要有精确的准确性和理解力，确切了解**AI**对我们环境的影响，并在各方之间达成共识，这样我们才能做出大家都同意的陈述，从而识别出解决方案。所以第一个里程碑将包括透明度、大量信息和数据，这样我们才能真正就这些挑战是什么达成一致。下一个里程碑是因为，正如我们所说——正如你提到的，我从**NVIDIA**来到**Bezos Earth Fund**——正如我们所说，公司正在改变它们构建技术以支持**AI**的方式。例如，冷却不再是——仅仅是数据中心的冷却已经转变为现在有机制可以在芯片层面进行冷却，这样对水的负担就不那么重了。所以这些就是必须到位的那类里程碑。
Original English **ARM**: So I was listening to a panel the other day, and someone said something along the lines of, "Every time you do a query on ChatGPT, It's like throwing away a bottle of water on the ground." And as soon as they made that statement, they said, "You know, I don't know if that's true, but it sounds, you know, like it might be true." One of the things that we need to begin to do is to have precise accuracy and understanding of exactly the impact that AI is having on our environment and a shared understanding across the board, such that we can make statements that we all agree on, such that we can identify the solutions. So the first milestone, which will include a level of transparency, a lot of information and data, such that we can really get to a place of agreeing on exactly what those challenges are. The next milestone is because, as we speak -- as you mentioned, I came to the Bezos Earth Fund from NVIDIA -- as we speak, companies are shifting how they build technology to support AI. For instance, cooling is no longer -- just cooling at the data center level has shifted to now there are mechanisms where you can cool at the chip level, such that the burden on water is not so great. So these are the types of milestones that would have to be in place.
### 迈向AI赋能的未来 **Manoush Zomorodi**: 所以我想最后说，你知道，这是一个激动人心的时代，也是一个令人恐惧的时代。是什么让你——是什么让你最充满希望？当你每天醒来去寻找解决方案时，你最兴奋的是什么？
Original English **MZ**: So I guess I want to end by saying, you know, it's an exciting time, it's a scary time. What is getting you sort of -- what makes you most hopeful? What are you most excited about when you get up every day to go figure out how we're going to find solutions?
**Amen Ra Mashariki**: 让我这么说吧。我们相信我们正处于一个**后果深远的十年**与**决定性的十年**交汇的时代。所以，如果你以前听过这个词，**后果深远的十年**，这是**AI**从业者用来谈论的，这是我们必须考虑伦理、政策、监管、技术、创新、发明的时期，因为这些决定将决定，这些事情将决定**AI**对全球社区产生什么影响。而且我们都知道这里的**决定性的十年**指的是什么。所以这是一个**后果深远的十年**与**决定性的十年**交汇的地方。因此，这确实需要**全力以赴**。并且需要**AI**领域的社区和气候与自然领域的社区做出承诺。而我们**Bezos Earth Fund**，我们认为自己正处于这个中心，并在这个领域发挥领导作用。
Original English **ARM**: So let me say this. We believe that we are in a space where the consequential decade meets the decisive decade. And so if you've heard that term before, the consequential decade, it's what AI practitioners use to talk about, this is the time in which we have to think about ethics, policy, regulation, technology, innovation, invention, because these are the decisions that are going to decide, these are the things that are going to decide what impact AI has on the global community. And we all know here what the decisive decade reference is. And so this is a place where the consequential decade meets the decisive decade. And so it really has to be all hands on deck. And a commitment from communities in the AI space and communities in the climate and nature space. And the Bezos Earth Fund, we see ourselves as sitting right in the middle and being a leader in that space.
**Manoush Zomorodi**: 好的，我们就谈到这里。Amen Ra Mashariki，非常感谢你。非常感谢。 (掌声)
Original English **MZ**: OK, we'll have to leave it there. Amen Ra Mashariki, thank you so much. Thank you so much. (Applause)