If Amazon wanted to stimulate creativity among its developers, it shouldn’t try to guess what kind of services they might want; such guesses would be based on patterns of the past. Instead, it should be creating primitives — the building blocks of computing — and then getting out of the way.
.. GOOGLE IS A PRODUCT COMPANY
Google, meanwhile, has never really been a platform company; in fact, while Google is often cast as Apple’s opposite — the latter is called a product company, and the former a services one — that only makes sense if you presume that only hardware can be a product. A more expansive definition of “product” — a fully realized solution presented to end users — would show the two companies are in fact quite similar.
.. this is the exact opposite of the model employed by not just Amazon but also Microsoft, the pre-eminent platform company of the IT era: instead of integrating pieces to deliver a product AWS went in the opposite direction, breaking down all of the pieces that go into building back-end services into fully modular parts; Microsoft did the same with its Win32 API. Yes, this meant that Windows was by design a worse platform in terms of the end user experience than, say, Mac OS, but it was far more powerful and extensible, an approach that paid off with millions of line of business apps that even today keep Windows at the center of business. AWS has done the exact same thing for back-end services, and the flexibility and modularity of AWS is the chief reason why it crushed Google’s initial cloud offering, Google App Engine, which launched back in 2008. Using App Engine entailed accepting a lot of decisions that Google made on your behalf; AWS let you build exactly what you needed.
.. Where Kubernetes differs from Borg is that it is fully portable: it runs on AWS, it runs on Azure, it runs on the Google Cloud Platform, it runs on on-premise infrastructure, you can even run it in your house.
.. the potential impact of Kubernetes specifically and container-based development broadly is to make irrelevant which infrastructure provider you use. No wonder it is one of the fastest growing open-source projects of all time: there is no lock-in.
.. its reliance on links instead of simply page content — meant that as the web got bigger Google, unlike its competitors, got better.
.. when you can access any service, whether that be news or car-sharing or hotels or video or search etc., the one that is the best will not only win initially but will see its advantages compound.
.. Kubernetes was Google’s attempt to effectively build a browser on top of cloud infrastructure and thus decrease switching costs
.. superior machine learning offerings can not only be a differentiator but a sustainable one: being better will attract more customers and thus more data, and data is the fuel by which machine learning improvement comes about. And it is because of data that Google is AWS’ biggest threat in the cloud.
.. in TensorFlow and Monetizing Intellectual Property Google’s willingness to share its approach was an implicit admission that its superior data and processing infrastructure was a sustainable advantage.
.. the creation of the Google Cloud Machine Learning group .. they are tasked with productizing Google’s machine learning capabilities.
.. it’s often easier to change the rules of competition than to change your fundamental nature as a company.
.. a new business model — sales versus ads — and build up the sort of organization that is necessary for not just sales but also enterprise support.
.. Microsoft is likely to prove particularly formidable in this regard: not only has the company engaged in years of research, but the company also has experience productizing technology for business specifically; Google’s longstanding consumer focus may at times be a handicap. And as popular as Kubernetes may be broadly, it’s concerning that Google is not yet eating its own dog food.
In Thrall to Scarcity
(open source, or whatever you want to call it): the economics of it, like anything else, are rooted in scarcity, and if you don’t have a bit of that scarcity yourself, you have a lot less leverage
.. Market economies work via the exchange of scarce goods and services. If you have nothing to trade, you have nothing. Now, free software is worth something. Worth a great deal – that is beyond the shadow of a doubt. But since anyone can make a copy, there is no scarcity – once it’s out there, you can’t trade for it.
.. If you’re writing free code that will simply become a cog in their proprietary system, the actual money comes from the scarcity they have created, so while you may be writing free software, in one sense, you’re simply offloading the burden of creating scarcity to someone else, who is then able to pay you for your time. The other possibility is that your client works in the “real world” of scarcity directly – they sell books or beer or cars or something else where the product is, by its nature inherently scarse.
.. to make money at something in the long run, you are going to have to find and sell a product that people cannot effortlessly get for free.
Fat Protocols
by replicating and storing user data across an open and decentralized network rather than individual applications controlling access to disparate silos of information, we reduce the barriers to entry for new players and create a more vibrant and competitive ecosystem of products and services on top. As a concrete example, consider how easy it is to switch from Poloniex to GDAX, or to any of the dozens of cryptocurrency exchanges out there, and vice-versa in large part because they all have equal and free access to the underlying data, blockchain transactions. Here you have several competing, non-cooperating services which are interoperable with each other by virtue of building their services on top of the same open protocols.
.. the market cap of the protocol always grows faster than the combined value of the applications built on top, since the success of the application layer drives further speculation at the protocol layer
.. The combination of shared open data with an incentive system that prevents “winner-take-all” markets changes the game at the application layer and creates an entire new category of companies with fundamentally different business models at the protocol layer. Many of the established rules about building businesses and investing in innovation don’t apply to this new model and today we probably have more questions than answers.
‘In the Eye of a Tornado’: Views on Innovation from China
[Xiaomi uses flash sales to gage demand for their product. Consumers get a ticket for the right to purchase their phone. Xiaomi then goes to Shenzhen and gets a bulk rate.]
.. No matter how one views Xiaomi — and there are many ways to view it, for better or worse — one thing is clear: It, and other such companies (like WeChat and Alibaba), indicate a broader trend around innovation coming from China.
Companies and countries that were once positioned as copycats or followers are becoming leaders, and in unexpected, non-obvious ways. For example, through scale, distribution, logistics, infrastructure, O2O, a different kind of ecommerce, mobile marketing, even design… But of a very different kind than iconic examples like, say, SpaceX. Or Apple, which arguably could damage the U.S. if single-mindedly regarded as “our official most innovative company”.
Or so argue the guests on this podcast, which include a16z partner Connie Chan and author/long-time observer of internet and social media culture Clay Shirky, who is currently based at NYU Shanghai, wrote the popular book Here Comes Everybody, and most recently authored Little Rice on “smartphones, Xiaomi, and the Chinese Dream”.