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This is not a tech focused article, it's a business / investor article. It doesn't care about the definition of AI from a tech or software perspective - it care

This is not a tech focused article, it's a business / investor article. It doesn't care about the definition of AI from a tech or software perspective - it cares about classifying types of companies (SaaS vs AI) so that it can make reasonable assumptions about expected performance of those categories and create boundaries / guidelines for how to think about investment strategy.

TeMPOraL 7y ago
> it cares about classifying types of companies (SaaS vs AI) Investor-focused or not, that seems like a category error.
- AndrewKemendo 7y ago
  This is exactly my point, it is a category error in the worst sense as it's creating a category "AI company" that would be charitably described as poorly defined.
  - spyckie2 7y ago
    My point is that it's poorly defined from a technical perspective but well defined from a business perspective. If you define AI company from what AI means from a tech perspective, then yes, it's a useless categorization. But if you define AI company as any company that makes money through offering optimization through data as a service, then I think that's a useful definition, in that you can lump many companies together and make sensible generalizations about their business models, which the article does: Saas business model - 80% margins, exponential scaling, 0 marginal costs, competitive moats through tech AI business model - 30-50% margins, linear scaling, higher marginal costs, data isn't a great moat Under the hood it could be deep learning or basic statistics, but it doesn't matter what technology they employ, the method of making money for these types of companies is the same. (In large/mature markets though, it matters a lot what tech you use since these methods can be copied by your competitors and improved upon - you can't use basic statistics to beat top of the line models forever, so most if not all data companies can be treated as eventual AI companies. I suspect this is why they use the term AI company rather than data company).

TeMPOraL 7y ago

> it cares about classifying types of companies (SaaS vs AI) Investor-focused or not, that seems like a category error.

AndrewKemendo 7y ago
This is exactly my point, it is a category error in the worst sense as it's creating a category "AI company" that would be charitably described as poorly defined.
- spyckie2 7y ago
  My point is that it's poorly defined from a technical perspective but well defined from a business perspective. If you define AI company from what AI means from a tech perspective, then yes, it's a useless categorization. But if you define AI company as any company that makes money through offering optimization through data as a service, then I think that's a useful definition, in that you can lump many companies together and make sensible generalizations about their business models, which the article does: Saas business model - 80% margins, exponential scaling, 0 marginal costs, competitive moats through tech AI business model - 30-50% margins, linear scaling, higher marginal costs, data isn't a great moat Under the hood it could be deep learning or basic statistics, but it doesn't matter what technology they employ, the method of making money for these types of companies is the same. (In large/mature markets though, it matters a lot what tech you use since these methods can be copied by your competitors and improved upon - you can't use basic statistics to beat top of the line models forever, so most if not all data companies can be treated as eventual AI companies. I suspect this is why they use the term AI company rather than data company).