Platforms vs Aggregators

Platforms vs Aggregators in the War for Quantum Computing Supremacy

Erik Huckle
May 16, 2018 · Unlisted

Part three in a four part series which attempts to explain the general concept of quantum computing (QC) and its exciting applications for problems within cryptography, optimization, artificial intelligence and finance. Part 1 explained quantum computing, Part 2 described breaking Bitcoin with QCs. This third post discusses the differences in business models between aggregators and platforms and what these differences mean for the development of quantum computers.

What are the differences between an Aggregator and a Platform?

Both models rely on attracting end users.

Google is an Aggregator. An Aggregator has power over its suppliers because it controls the relationship between the supplier and the consumer. Google monetizing open information by serving the consumer ads.

Microsoft is a Platform. The company has many products they sell, but their legacy product is Window. Windows creates value for the end user by making it easier for developers to create products on top of their platform. Microsoft ultimately wants to empower you by making you more efficient.

Platforms and Aggregators, Both in the Cloud

The biggest names in tech, Microsoft, Amazon, Google and IBM, are all jockeying to be the industry leader for providing cloud services. Public cloud services revenue is forecasted to be over $400B by 2020.

These industry heavyweights are all trying to find the competitive edge in a cloud marketplace that will be increasingly commoditized over time. The seamless integration of artificial intelligence with data in the cloud will be the new standard for companies providing these services in the future.

“A.I. is probably the most important thing humanity has ever worked on. I think of it as something more profound than electricity or fire,” (Google’s CEO Sundar Pichai)

Amazon Web Services pioneered the model of providing Infrastructure-as-a Service through the cloud. More investments in infrastructure allow the company to have more internal capabilities while also providing more services to the customer at a cheaper price. The cloud allows companies to deploy their digital infrastructure investments across an entire customer base. Amazon introduced per-second billing of its AWS tools to make these investments even more accessible to customers. Other companies are now offering this new billing option to bring its powerful capabilities traditionally reserved for big companies to even smaller ventures and entrepreneurs.

Let’s take a look at what the companies I think are representative of the above models are working on and how they will leverage their investments in Quantum Computing.


From Ben Thompson at Stratechery, “…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.” Google is well positioned for the next phase of generating revenue and delighting customers through cloud services. Google has made artificial intelligence a key strategic focus since its inception. I would argue Google’s A.I. isn’t being used to make search better, but they use their search product to make its A.I. better.

Andrew Ng, a renowned artificial intelligence expert, said,

“A.I. is akin to building a rocket ship. You need a huge engine and a lot of fuel. The rocket engine is the learning algorithms but the fuel is the huge amounts of data we can feed to these algorithms.”

Google has a massive amount of fuel.

Some of Google’s initiatives through its X division seem incompatible with Google’s overall strengths. With X, Google has demonstrated they have the intellectual capacity, money and resolve to commit to long-term projects which aren’t guaranteed to ever generate revenue. Waymo, their self driving car venture, was spun out of the division. Morgan Stanley analysts have said that Waymo could be worth around $70B in the near future. Underneath the Waymo hood is a massive investment in A.I. and machine learning. Google had a double win with Waymo as they created a project which will not only generate revenue for Alphabet but will also train the company’s A.I. in a new and innovative way.

Quantum computing is one of those projects where the benefits can be spread over several different products. Google announced the launch of the Quantum Artificial Intelligence Lab in May of 2013. Hartmut Neven, the Director of Engineering of the new group, said its stated goal was, “studying how quantum computing might advance machine learning”.

There exists a powerful ulterior motive to the first movers who are able to build up a market leading share of customers. Companies like Google will be able to use that lead, and that critical time with those customers in its QC development cycle, to train its machine learning algorithms in novel ways which can be deployed across their entire business.

Jeff Dean, the Google Brain Project lead said,

“And then over time, what we discovered is that the same machine-learning techniques and algorithms that solve problems in one area could be used in lots and lots of other product areas and product domains.”

Users are always training Google’s algorithms when they utilize its products like Google Maps, Gmail and Search. Google will continue to build out its strategic moat by adding quantum computing capabilities to each of these products behind the scenes.


“Microsoft 365 helps every organization empower their employees with AI-backed tools that unlock creativity, increase teamwork and fuel innovation, all the while ensuring compliance and protecting data from new cyber threats.” (Microsoft’s CEO Satya Nadella)

Microsoft is leveraging its access to its massive installed user base to upsell them on their Artificial Intelligence tools. This strategy has worked extremely well so far. Chief Information Officers are evaluating their companies use of different cloud offerings based on their:

1. Ease of migrating data

2. Security of the new networks

3. How flexible the new system is for developing and incorporating new developer tools

Microsoft has focused on these three points to sell Azure. In support of #3, Microsoft has introduced their Quantum Development Kit. This is a grouping of enterprise-grade tools which can be used to write, debug, and optimize quantum code. This pairs with their quantum services offered through Azure. Microsoft is enabling their development community to build applications for its Azure ecosystem, which will ultimately make the platform more valuable for the end-users.

Bonus Shoutout, Government

Individual business will need to have a clear path to commercial viability to develop quantum computers. That path does not exist right now. Large government laboratories, like Los Alamos National Laboratory, do not have those same pressures as they are funded specifically to perform this type of basic research. Richard Feynman, a notorious Los Alamos scientist, received the Nobel Prize in Physics for his work in the field of quantum mechanics. He was among the first to recognize the possibilities of using quantum mechanics to solve certain types of computing problems quickly. [1] Public-private partnerships derived from government research dollars strive to reduce the development and utilization cycle for brand new technologies. A cutting edge startup out of New Mexico called Descartes Labs, which use satellite imagery to model complex systems on the planet, is based on artificial intelligence software the company licensed from Los Alamos National Laboratory.

Why Should You Care?

Descartes Labs is just one company which maintains a relatively low overhead by relying on Google Cloud. From a Google Cloud case study,

“By using Google Cloud Platform to analyze and store nearly 15 petabytes of data, Descartes Labs can cost-effectively process years of satellite imagery, helping businesses and governments make accurate predictions about global food supplies and detect early warnings of famine to prevent catastrophes.”

At this point it is hard to tell how a startup like Descartes Labs will utilize quantum computing. It is safe to say that as Google adds the ability to use their quantum computers to the cloud, Descartes will experiment with the new technology to try to unlock different ways to solve problems and create value for their customers. By adding quantum computing to a classical computing system, organizations could be able to work through some types of calculations in seconds which would take classical computers years. As an investor, it is important to keep an eye on new business models and how they can empower or be harnessed by startups in different ways. Quantum computing could be a technology critical to understand for venture capitalists and angel investors looking for the next startup to invest in.

Finally, I need to send out one big shoutout to an author whose writing helped in the creation of this post. I am a big fan of Ben Thompson and his blog “Stratechery”. Some of the key ideas for this post came out of the following posts: “Tech’s Two Philosophies”, “How Google is Challenging AWS”, “Platforms Versus Aggregators, What About Amazon?, Walmart Buys Flipkart”, “T-Mobile to Acquire Sprint, Microsoft’s Earnings” and “Aggregation Theory”.

[1] West, Jacob (June 2003). “The Quantum Computer”(PDF). Archived from the original (PDF) on March 15, 2015. Retrieved September 20, 2009.


Erik Huckle

Written by

Life Long Learner. Currently in startup mode @Hupbeat. Ex-Amazon.

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