🐰 #34 Deep Analytics, AI in Surfing, AI Business is Different; ThDPTh #34 🐰
What is deep analytics? How AI is used to win Olympic medals, and how to build a proper AI business.
Data will power every piece of our existence in the near future. I collect “Data Points” to help understand & shape this future.
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(1) Deep Analytics
This article’s a bit of an ad for the company, but I like the wording “deep analytics” and I find one point very true: It deserves a name and it is kind of underestimated.
Deep analytics is digging through data, it’s not about dashboards of reports, it’s about true analysis. Whereas most business analysts spend their time creating reports & dashboards, deep analytics is the 20% of their work where they deep dive into the data to prepare an important decision by a decision-maker.
I find the best way to share these deep analyses is by what I still like to call the “story” format. Notebooks are a perfect way to tell analytical stories, a mixture of code, graphics, and text, with some exploratory sliders & buttons. So I still love the hosted notebook server, SQLbook, and other new emerging solutions in this space.
I think a small hosted notebook server is all that is needed for medium-sized companies, but maybe the company behind Joseph Moon has also created something of interest.
The real meaty questions about the business such as: “what contributed…
(2) AI in Surfing
This article is behind the WSJ paywall, but I simply liked it. I know a colleague working in kayaking and machine learning to help teams train to hit the water just at the right angle.
In his example, a trainer usually analyzes 1–2 frames every minute of a video to give advice, the machine can analyze 30–50 frames each minute, and roll that out not just to professional athletes but to anyone.
There is a revolution happening in sports that focuses on just that, rolling out what a good coach can 1–2 each minute for a single professional athlete to a large set of athletes. This article talks about this movement happening in surfing and I absolutely love that AI & machine learning are moving in that direction.
As surfing completes its first-ever Olympic ride, …
🔮🔮🔮 Data Company Corner 🔮🔮🔮
Stuff that might be interesting for anyone at the front line of the data world, inside a data company, inspired by much positive feedback from my article on commercial open source software data companies.
(3) a16z Doing AI Business Right
I remember Steve Jurvetson talking about how back in the time there were “thermodynamics” companies. Nowadays, thermodynamics is simply part of engineering.
Just as that, AI will simply be part of software engineering sometime in the future. So that begs the question, should you even do an “AI company?”. I think the answer is “No”. The commoditization trends are pretty clear in this direction, which means, what you can do is to focus your efforts on parts that will not be commoditized and reduce the complexity on the ones that will (like the model). It means to stop thinking of yourself as an AI company, and start thinking of yourself simply as a company that provides value to customers.
The latter part is exactly the advice given in the article, reduce the model from multiple to one, building the full-stack service, plan for change in the tech stack and focus on old-fashioned ways of doing business and building a competitive advantage.
We have noticed in many cases that AI companies simply don’t have the same economic …
🎄 In Other News & Thanks
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