Community capitalism: launching the Machine Commons

Updated: Oct 8, 2020

Hello everybody, this post varies to all that precede it because it is about us, our mission and the problem we’re trying to solve in the market - so no interviewee today!


First, I’d like to thank you for your continued support over the last two years. None of this would have been possible without the countless individuals who have taken part in this journey, to the interviewees in being open to give their time for free to this passion project and to the regular readership who returns for interesting perspectives.



I’ve frequently mentioned the ideas of ‘cross-pollination’ and ‘community capitalism’ as the underlying ethos, pathos and logos that has inspired this community, its mind, heart and soul.


I’ve said it before: the barriers between businesses are blurring.



It’s no longer possible to operate in isolation of the other businesses in your ecosystem; my heart tells me it’s wrong to anyway and my soul has faith that this world will adapt accordingly.



So much of modern business is through word of mouth. Such as how people leave jobs, pop up elsewhere and bring old service providers with them. That’s an efficient way of avoiding media costs, but not as effective as it could be.


Traditional methods of marketing have subsided to the tidal wave that is social networking (aka ‘networking’); however, this comes with its own brand of problems. LinkedIn has become a fundamental instrument in any marketing strategy.


It is crucial to pay huge respect to - to obey - the algorithms that rule us.

I’m not sure about you, but I don’t like what Facebook has done to social structures and I’m certain LinkedIn is insidiously installing itself as the infrastructure of business. Too much power to one, algorithmic platform.



Why did you go bust? Oh, the computer said no...



Did you notice the LinkedIn algorithm change? Now posts that link externally are valued less. We’ve all signed a social contract that agreed to this - do you remember signing? ...Do I post the link to my new business in the comments? I did that once, but it seems disingenuous to me.


Maybe I should start playing these algorithm games but, in truth dear reader, I hate it so much I can’t bring myself to do it. Like hashtagging #likeforlike in Instagram.



Take a machine learning engineer, what are their options in the business world today?


1. Join a firm, be over-worked, under-paid, under supported and be managed by people who often don’t have the faintest clue about what you do. Not a recipe for job satisfaction or clear career progression.


2. Freelance independently, source your own clients, constantly manage your reputation and spend ridiculous amounts of time ploughing your network for that next uncertain, unstable and temporary role. Have you tried balancing seasonal clumping with paying your bills?


3. Start a business, call it a ‘Machine Learning Consultancy’, learn about marketing, branding, sales pipelines, managing staff, media channels, ... attend networking events, conferences,... the list is endless and engineers are already tired keeping up with their own field of expertise.


There are now literally hundreds - thousands - of machine learning consultancies and no one is trained to tell the difference between them.


More and more, due to the lack of start up costs and to the fact that anyone with knowledge and a computer can harness the power of Google’s tensorflow, AWS or Microsoft alternatives, or even setting up Nvidia power in their garage... suddenly, as I’ve mentioned before: David now has the power of Goliath.


4. Don’t worry, there’s a fourth option. That’s where the Machine Commons Services Hub comes in.



I’ve talked with some of the best minds in the business, with some of the biggest consultancies and some of the smallest. What have I noticed?


Large ML consultancies promise the world, but can’t deliver because they can’t attract the best talent. They pump vast amounts of money into shiny brands, plays on the word AI, build colossal content strategies and get everyone over excited about the promise of “artificial”-“intelligence”.


There’s a reason AI keeps meeting a wintry fate: expectation management.

Clients are strung along by “Acquisition“ and “Client Service“ teams. Projects get extended, and extended, and extended, then don’t quite execute on the original promise. Wait a second, why are we here again? A chat bot that breeds it’s own problems? I thought we were building an omnipotent doctor. Never mind.



On the other hand, small ML consultancies are too small to perform all of these business functions successfully. There’s no economy of scale in their content and media strategy, let alone the years of experience it takes to perform these tasks in a coordinated and successful manner. No wonder our markets are oligopolising (oh quiet, oligopolising can be a word).



Machine Learning professionals are being trained (ha) to rely heavily on algorithms to surface their brand to the right people (for the right price, of course, with the right persistence).



There are so many intensely intelligent groups of technical people now trying to achieve communication objectives, reducing their focus on their existing work and often adding to their already heavy work hours.



It’s time small consultancies had the power of a big brand. A collective brand.


So. What’s option 4, what is the new chapter for the Machine Commons?



I’m very proud to launch Machine Commons Services, an umbrella brand to represent the best agencies per industry niche, so communication and sales can be done by communication and sales professionals.


With the ultimate aim of:

  1. Being a stable sales channel for SMEs, so they don’t have to sell out to larger organisations (or go bust trying), helping engineers be engineers, marketers to be marketers.

  2. Creating a unified Machine Learning Services portal of certified providers to make machine learning buying decisions easier for clients.

  3. Cross-pollinating insight and resources between non-competing smaller entities.

  4. Ensuring the highest level of accountability, of transparency and of ethical, sustainable business practices.


Now the many can be one.


Join us on our mission.

https://www.machinecommons.org/mission

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