“Every moment in business happens only once. The next Bill Gates will not build an operating system. The next Larry Page or Sergey Brin won’t make a search engine. And the next Mark Zuckerberg won’t create a social network. If you are copying these guys, you aren’t learning from them.”

“业务中的每时每刻只发生一次。 下一个比尔·盖茨将不会构建操作系统。 下一个Larry Page或Sergey Brin将不会成为搜索引擎。 下一位马克·扎克伯格(Mark Zuckerberg)将不会创建社交网络。 如果您要复制这些人，那么您就不会向他们学习。”

— Peter Thiel, Zero to One

—彼得·泰尔(Peter Thiel)，从零到一

Thiel is saying that Microsoft, Google and Facebook all made something new. They went from nothing to something, from zero to one.

泰尔(Thiel)表示，微软，谷歌和Facebook都做出了新的尝试。 他们从无到有，从零到一。

Now that we have an index of the internet, operating systems and social networks, that moment has passed. The next phase of innovations will not come from building on top of what they have built.

现在我们有了Internet，操作系统和社交网络的索引，这一时刻过去了。 下一阶段的创新不会来自于已建立的基础之上。

It will come from building something new.

这将来自构建新的东西。

Innovation comes from questioning the conventional wisdom of “how things are done”. Contrarian thinking leads to world-changing startups.

创新来自对“事情如何完成”这一传统智慧的质疑。 反向思维导致了改变世界的初创公司。

There’s a new wave of startups who are going against one of the most pervasive assumptions of our time: that we should look to technology for solutions to our most pressing issues.

Ť这里是一个初创企业的新一波谁是逆着我们这个时代最普遍的假设之一：我们应该着眼于技术，我们最紧迫的问题的解决方案。

These are the startups based on biomimicry. Biomimicry is an approach to innovation that looks for solutions to human challenges in nature’s vast library of strategies and patterns.

这些是基于仿生学的初创公司。 仿生是 一种创新方法，可在自然界庞大的战略和模式库中寻找解决人类挑战的方法。

Biomimicry startups are asking nature how to design smart AI, build sustainable houses and, ultimately, address the most pressing issues of our time.

仿生创业公司正在向自然界询问如何设计智能AI，建造可持续房屋以及最终解决当今时代最紧迫的问题。

鸟脑人工智能 (Bird-Brained Artificial Intelligence)

Unanimous AI is a biomimicry startup you might have heard of.

一致认可的AI是您可能听说过的仿生创业公司。

It’s known for successfully predicting the last 3 years of Oscar winners, Time’s Person of the Year and Donald Trump’s 100-day approval rating (which it got down to the exact point).

它以成功预测奥斯卡奖获得者的最近3年，《时代》杂志年度人物和唐纳德·特朗普的100天支持率而闻名( 准确到这一点 )。

But Unanimous is not your normal deep-learning AI. It’s “swarm AI”, based on how birds, fish and bees make decisions together in a swarm.

但是，一致不是您通常的深度学习AI。 它是“群居AI”，基于鸟类，鱼类和蜜蜂如何共同做出决定。

Taken individually, these creatures aren’t renowned for their brainpower. But when they come together in flocks, schools and swarms, a collective intelligence emerges that is greater than just the sum of its (not particularly intelligent) parts.

单独来看，这些生物并没有以脑力着称。 但是，当他们聚集在羊群，学校和大群中时，就会出现一种集体智慧，这一智慧不仅仅是其各个部分(不是特别聪明)的总和。

As company founder Louis Rosenberg explains:

正如公司创始人Louis Rosenberg 解释的那样 ：

“Nature has spent millions of years trying to optimize how living things operate together, because they can solve very complicated problems together, and ultimately are able to survive by thinking as a system.”

“自然已经花费了数百万年的时间来尝试优化生物如何共同运行，因为它们可以共同解决非常复杂的问题，并最终能够通过系统思考生存。”

In a swarm, survival depends on deciding where to go to find food or avoid predators. But swarms have no single leader to make a final decision and no language for discussion. Nature’s solution is to pool the knowledge and intuition of the swarm as a whole.

一群人的生存取决于决定去哪里寻找食物或避免掠食者。 但是，一群人无法做出最终决定，也没有讨论的语言。 大自然的解决方案是集中整个群体的知识和直觉。

As individuals start to move, they exert a pull on the direction the group will take. Some individuals will agree, and pull in the same direction. Others will have different knowledge of the situation or a different gut feeling. They’ll tug in a different direction. As these pulls and tugs play out in real-time, a decision emerges that optimizes the inputs of every participant and the swarm moves in the best direction.

当个人开始行动时，他们会在小组采取的方向上施加拉力。 有些人会同意，并朝着同一方向前进。 其他人将对情况有不同的了解或不同的直觉。 他们将向不同的方向拖拉。 随着这些拉力和拖船实时进行，出现了一个决策，该决策优化了每个参与者的输入，并且群体朝着最佳方向移动。

Unanimous’ Swarm AI works in the same way. A group of individuals is asked a question. They then interact in real-time to exert a pull towards what they think is the best answer. Together, the swarm makes a decision.

一致的Swarm AI以相同的方式工作。 一群人被问一个问题。 然后，他们进行实时互动，以发挥他们认为是最佳答案的吸引力。 一群人共同做出决定。

You can see this process applied to the question of Democratic Party policy during the 2016 election.

您可以看到此过程适用于2016年大选期间的民主党政策问题。

一致AI与深度学习AI与人类 (Unanimous AI vs Deep Learning AI vs Humans)

Unanimous’ Swarm AI has already been tested against deep-learning AI and human experts in the diagnosis of pneumonia.

一致的Swarm AI在肺炎的诊断中已经针对深度学习的AI和人类专家进行了测试。

In a paper published in Nature, Unanimous AI unsurprisingly outperformed individual radiologists. It also outperformed groups of radiologists debating and voting on diagnoses.

在《 自然》杂志上发表的一篇论文中， 一致 毫不奇怪，人工智能的表现胜过放射线医师。 它也胜过许多放射科医生，他们对诊断进行辩论和投票。

When pitted against CheXNet, a deep-learning AI trained to diagnose pneumonia, the results are a little murkier.

当与训练有素的诊断肺炎的深度学习AI CheXNet对抗时，结果有点模糊。

When facing off against CheXNet, Unanimous AI made better diagnoses. But when CheXNet was retrained with a bigger and better dataset, it started to outperform Unanimous in some areas.

当面对CheXNet时，一致的AI可以做出更好的诊断。 但是，当对CheXNet进行更大，更好的数据集再培训时，它在某些领域的表现开始优于Un一致。

The researchers concluded that deep-learning AI was great where it had high degrees of certainty. For less certain cases, a group of radiologists assisted by Unanimous AI produced the best diagnoses possible.

研究人员得出结论，在具有高度确定性的地方，深度学习AI很棒。 对于不太确定的情况，一组放射线医生在一致AI的协助下做出了可能最好的诊断。

一致使人类与AI时代息息相关 (Unanimous keeps humans relevant in the age of AI)

That’s where the significance of Unanimous AI really comes to the fore. The development of artificial intelligence is often framed as a competition between humans and the algorithms we program. When the algorithms get better than us at any given task, we become irrelevant.

这就是一致AI真正重要的地方。 人工智能的发展通常被认为是人类与我们编写的算法之间的竞争。 当算法在任何给定任务上比我们更好时，我们就变得无关紧要。

Unanimous AI goes against the assumption that deep-learning AI is going to be smarter than a group of human intelligence. Looking to nature’s swarms provided the inspiration to challenge that assumption.

一致认可的AI违背了这样的假设：深度学习AI将比一群人类智能更聪明。 展望大自然，为挑战这一假设提供了灵感。

Biomimicry has led Unanimous to reassert the importance of people in the age of artificial intelligence. In doing so, they are copying nature to address one of the most pressing issues of our time.

仿生学使一致一致重申人工智能时代人们的重要性。 通过这样做，他们正在复制自然，以解决我们这个时代最紧迫的问题之一。

不仅仅是雄辩的工程 (More than just eloquent engineering)

“Positively shaping the development of artificial intelligence” is one of the most urgent issues we face as a species, according to 80,000 Hours, the non-profit that identifies mankind’s most pressing problems and figures out how best you can work to solve them.

根据80,000 Hours的说法， “积极塑造人工智能的发展”是我们作为一个物种面临的最紧迫的问题之一。该组织是非营利组织， 致力于确定人类最紧迫的问题并弄清楚如何才能最好地解决这些问题。

Unsurprisingly, climate change is also on that list. We urgently need to answer the question of how we sustain our society while staying within the ecological limits of the Earth.

毫不奇怪，气候变化也在该清单上。 我们迫切需要回答一个问题，即我们如何在维持地球生态极限的同时维持我们的社会。

It might be tempting to break this challenge down into a series of individual engineering problems, like how we produce energy without emissions, or chemicals without fossil fuels.

将这一挑战分解为一系列单独的工程问题可能很诱人，例如我们如何生产无排放的能源或无化石燃料的化学品。

But the most innovative new biomimicry startups are not just copying nature to solve engineering problems. They’re copying nature’s systems to address mankind’s systemic problems.

但是，最具创新性的新型仿生创业公司不仅仅是模仿自然界来解决工程问题。 他们正在复制自然界的系统来解决人类的系统性问题。

One example is UK based startup Biohm. Biohm’s product has its roots in nature — literally. They grow sustainable construction materials out of mycelium, the tendrilous, root-like part of mushrooms.

一个例子是英国的初创公司Biohm 。 从字面上看，Biohm的产品起源于自然。 他们从菌丝体(蘑菇的根状部分)中生长出可持续的建筑材料。

Like Unanimous AI, Biohm’s product is based on nature. And just like Unanimous AI, Biohm’s innovations have implications far beyond solving an engineering or design problem.

像一致的AI一样，Biohm的产品基于自然。 与一致的AI一样，Biohm的创新所带来的影响远不止解决工程或设计问题。

To make construction more sustainable, they are mimicking nature on a systematic level to address an underlying assumption of our society: waste.

为了使建筑更具可持续性，他们正在系统地模仿自然，以解决我们社会的基本假设：浪费。

大自然知道如何可持续地开展业务 (Nature knows how to do business sustainably)

We might be shocked by the scale of our waste mountains. But even if we recycle, we generally accept the concept of waste. How many times have you told yourself that “some things you just can’t recycle”?

我们可能对我们荒山的规模感到震惊。 但是，即使我们进行回收，我们也普遍接受废物的概念。 您有多少次告诉自己“有些东西您无法回收利用”？

Waste, it would seem, is simply the end of the line. We extract raw materials, we turn them into something new, we use them and then we throw them away when we’re done. The garbage heap is the place where a lot of our products naturally end up.

看来浪费只是行的结尾。 我们提取原材料，将它们变成新的东西，使用它们，然后在完成后将它们扔掉。 垃圾堆是我们许多产品自然地最终产出的地方。

Nature has a different modus operandi. In natural systems, nothing is wasted. When a tree reaches the end of its life, for example, it dies and falls over. But it’s not wasted. Fungus and microbes break it down into humus, the nutrient rich soil where the next generation of trees lay their roots. New growth takes up valuable organic compounds from their decayed forest forebears.

大自然有不同的作案手法 。 在自然系统中，没有浪费。 例如，当一棵树到达生命的尽头时，它就会死去并倒下。 但这并没有浪费。 真菌和微生物将其分解为腐殖质，腐殖质是营养丰富的土壤，下一代树木可在此生根。 新的生长吸收了其腐烂的森林前辈中有价值的有机化合物。

You’ve heard of this before. It’s the circle of life. When the same logic is applied to the waste, it’s called the circular economy. In the circular economy, when products reach the end of their useful lives, someone steps in to turn them into something new.

您之前已经听说过。 这是生活的圈子。 将相同的逻辑应用于废物时，称为循环经济。 在循环经济中，当产品使用寿命到期时，有人会介入以将其转变为新产品。

But there’s more to the circular economy than just eliminating waste. It’s a different way of thinking that is offering biomimicry startups a systematically different way to do business.

但是，循环经济不仅仅是消除浪费。 为仿生创业公司提供系统上不同的经商方式是另一种思维方式。

As Biohm founder Ehab Sayed explains in Biohm’s Google Talk:

正如Biohm的创始人Ehab Sayed在Biohm的Google Talk中解释的那样：

The circular economy is not simply about recycling resources, but it’s about adding as much value as possible at every stage of the way so that the resource that you’re using is not depleting in value at all, it’s either maintaining the same value or increasing in value.

循环经济不仅涉及资源的循环利用，而且还涉及在每个阶段尽可能多地增加价值，以便您所使用的资源根本不会耗尽​​价值，而是维持不变的价值或增加价值。价值。

The approach of adding value at every stage has led Biohm to conceive of their products a little differently. Instead of offering materials that can only be used once (like concrete), Biohm’s can be taken apart and reassembled. They also offer ongoing servicing of their buildings and end-of-life deconstruction.

在每个阶段增加价值的方法使Biohm对其产品的构思有所不同。 代替提供只能使用一次的材料(例如混凝土)，可以将Biohm拆开并重新组装。 他们还提供建筑物的持续维护和报废解构。

Biohm is also growing new strains of fungus that can eat up waste plastic to grow construction materials and even food.

百奥还正在种植新的真菌菌株，这些真菌可以吃掉废塑料，从而种植建筑材料甚至食物。

12.7 million tons of plastic waste was entering the oceans in 2015, and researchers expect this to rise “by an order of magnitude” before 2025. Given the scale of plastic pollution, it’s critical that we find a way to overturn our assumptions that “waste” plastic need only be disposed of. Nature is showing us both the solution, both on the systematic level and the engineering level.

2015年，有1,270万吨的塑料废物进入海洋，研究人员预计，到2025年，这将“上升一个数量级 ” 。鉴于塑料污染的规模，我们必须找到一种方法来推翻“废物”的假设，这一点至关重要。塑料只需处置。 大自然在系统层面和工程层面上都向我们展示了解决方案。

Biohm represents a very different way to think about the construction industry. Overall, it’s a more environmentally sustainable business model. It doesn’t rely on extraction, processing and disposal, but on recycling, recreating and reusing.

比奥姆代表了一种非常不同的方式来思考建筑业。 总体而言，这是一种在环境方面更具可持续性的商业模式。 它不依赖于提取，加工和处置，而是依赖于回收，重新创建和再利用。

The results are impressive: a truly sustainable company that can insulate an ice cream from a thousand degrees of heat by using mushrooms.

结果令人印象深刻：一家真正可持续的公司，可以通过使用蘑菇使冰淇淋与一千度的高温隔绝。

要求自然创新 (Asking Nature for innovation)

For both Anonymous AI and Biohm, the implications of biomimicry go far beyond just the product they are making.

对于匿名AI和Biohm而言，仿生学的意义远远超出了他们正在生产的产品。

Biomimicry is starting to show its potential to address the most pressing issues of our time on a systematic level. Startups are already making headway, and there’s more where that came from.

仿生学开始显示其在系统水平上解决当今最紧迫问题的潜力。 初创公司已经取得了进展，而且还有更多的来源。

There is now a growing library of nature-inspired solutions to all kinds of problems. It’s called AskNature. Many of the solutions documented in this library relate to what 80,000 Hours identify as the most pressing questions for our survival and prosperity as a species.

现在，有一个不断增长的以自然为灵感的解决方案库，可以解决各种问题。 称为AskNature 。 该库中记录的许多解决方案都与80,000小时被确定为我们作为一个物种的生存和繁荣最紧迫的问题有关。

Beyond positively shaping the development of AI and the extreme risks of climate change, 80,000 Hours also considers “reducing global catastrophic biological risks” and “improving institutional decision making” to be priorities.

除了积极塑造AI的发展和气候变化的极端风险外，80,000小时还认为“ 降低全球灾难性生物风险 ”和“ 改善机构决策 ”是当务之急。

Nature’s ready-made solutions leap off the page for their potential.

Nature的现成解决方案因其潜力而脱颖而出。

Will the bacteria that constantly evolve to defeat new fungal invaders help protect us from ever more powerful biological risks? And if not, then what of the 85 research-backed solutions already in the library under the category of “Protect from living threats > Microbes”?

不断进化以击败新的真菌入侵者的细菌会帮助保护我们免受更强大的生物风险吗？ 如果不是，那么，图书馆中已有“基于生命威胁的防护>微生物”类别的85种由研究支持的解决方案中的什么？

If “improving institutional decision making” is one of the most impactful areas you can work on, what is the potential of any of the 214 ways the natural world has found to cooperate, coordinate and provide for one and other?

如果“ 改善机构决策 ”是您可以从事的最具影响力的领域之一，那么自然界发现的214种合作，协调和相互支持的方式中，有214种潜力是什么？

There are many barriers between an idea and a successful startup. Innovation carries a high risk of failure. But for the most crucial challenges of our time we will need to overturn assumptions and innovate.

一个想法与成功启动之间有许多障碍。 创新带来很高的失败风险。 但是对于我们这个时代最关键的挑战，我们将需要推翻假设并进行创新。

Nature is ready to show us the way. We just need to ask.

大自然已准备向我们展示道路。 我们只需要问。