[科技業的護城河]

這篇是講矽谷投資人, 是如何在一堆的新秀中, 挑選可以投資的創新公司.

裡面有提到護城河.不過有些跟"尋找投資護城河"一書提的不太一樣.

我也認為, 研究個股, 尤其是科技相關類股, 除了要看它有沒有先行者優勢(first mover advantage), 也需要注意公司有沒有自己的生態系統, 以及它在更大的生態圈/供應鏈中扮演了甚麼角色.

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(中文譯稿見此:https://36kr.com/p/5141901)

常見的護城河至少有以上六種：

技術。更好的基礎技術當然是一種護城河。在極端情況下，能夠為客戶帶來利益的新技術可以演化為一種行業標準，你也可以把它理解為一種壟斷，就像英特爾一樣。

生態系統。 YouTube 從內容生產者、分發渠道到內容的託管、保存，建立起了一整套生態系統。類似的，蘋果的 App Store 也有自己的生態。

網絡效應。社交網絡現在已經很好理解了。此外，如果某種按需服務具備了一定的流動性，並且與消費者建立了親密關係，或者是基本控制了需求或供應方其中一方，也可以算作網絡效應。

產品領導者。像 Salesforce，Workday 和 ServiceNow 這樣的雲服務提供商，搭建了一套完整的解決方案，而且創新速度夠快，產品功能完善，成為其細分行業的領導者，當然也算是一種護城河。

渠道。尤其是對於 to B 產品來說，能不能在一個企業內部流通，既是一個挑戰，也是一種優勢
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原文寫的比較仔細, 轉貼在下方: https://news.greylock.com/what-do-i-look-for-in-a-pitch-866355bddb3

We love to talk about “network effects” in Silicon Valley, but many believe that starts and end with the social, viral growth of Facebook. But network effects can build many kinds of moats that defend them against copycats and price erosion.

I don’t describe every kind of moat here (e.g., regulatory) and many great companies will have new types of moats — ones yet to be invented. No moat is absolute or permanent or I’d be out of a job! Still, having a thesis on your defensibility is essential, even at the Series A.

--Tech. We continue to believe in new and better fundamental technology as a moat — not so much patents or legal protection, but products that are hard to build well or take advantage of a fundamentally new approach. In extreme cases, a technology advantage that translates into a customer benefit can turn into a standard — an effective monopoly — as in the case of Intel. In most cases, even a great technology moat only gets you far enough to become a market leader, buying you the right to work closely with customers and enabling you to define the market.

--Ecosystem moats come in many flavors — from becoming the default hosting site for user-generated video content (YouTube), to the rapid, developer-driven free adoption of container technologies and growth of associated tooling (Docker), to the developers that now make >$20B a year through the Apple app store.

--Networks. Social networks are now pretty well-understood. Marketplaces and on-demand businesses reach a liquidity point (even a local one) and build mindshare with consumers that becomes hard to displace. Often, marketplaces have some advantaged acquisition strategy for at least one side (demand or supply) — they’ve built a community, offered a compelling new service, have organic or viral spread.

--Product leaders. In the enterprise, cloud pioneers like Salesforce, Workday and ServiceNow built complete, core workflow solutions with a new architecture. Their faster-innovating products, (at that time novel) SaaS consumption model, and dominant go-to-market machines have made them category leaders. Each is now expanding their initial moats to become platforms for other applications and workflows.

--Distribution represents a new generation of user-adopted SaaS products. End-user engagement within organizations is often a weak spot for enterprise software incumbents. Deploying software is a challenge for most organizations, and consumers who are using more software in their own lives expect better choice and usability. Simplicity and quality of design has become a moat, especially when coupled with product features that encourage adoption within an organization, or new layers of value for incremental users within an organization. Is it better for me if my team also uses a tool? What about my manager?

Capturing a unique dataset is also emerging as a moat in the age of AI-powered products. If your workflow product or MVP is useful on its own, and you can use it to collect unique data, you can then learn from that data to build a better and smarter product, improving the user experience — driving a new virtuous cycle.

【GCP 快報】
現在開始，你可以在 VM 上佈署 Docker Containers！
這項功能能帶來什麼好處呢? 它可以讓您在控制 Compute Engine 的基礎架構時，同時簡化應用程式的佈署。
這篇文章將教一步步教你如何完成操作。
(https://cloud.google.com/…/…/containers/deploying-containers)

想瞭解更多 GCP 的應用，歡迎來看看我們的中文技術部落格(https://blog.gcp.expert/)，裡面有更多像是機器學習、TensorFlow、Load Balancing 的教學文章喔！