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What we look for in AI companies (and why they are different)
Another issue is low tech defensibility. In the AI world tech defensibility is harder to achieve because new/revolutionary models are being developed mostly in open, academic settings and so are available in open source.
Matilde Giglio • What we look for in AI companies (and why they are different)
For example they have lower gross margins. Anecdotally, we have seen gross margins of ML companies at around 50/60% vs 60–80% of comparable SaaS businesses. This is due to two factors. Firstly, the hidden cost of the cloud infrastructure. Training a single ML model costs thousands of dollars in computing resources. Secondly, many applications requi... See more
Matilde Giglio • What we look for in AI companies (and why they are different)
The first thing to realise is that ML businesses just don’t have the same units economics of software businesses. ‘Sometimes, they look more like traditional service companies’.
Matilde Giglio • What we look for in AI companies (and why they are different)
The one I’m personally most excited about is companies which are extending capabilities to new market participants. AI massively reduces the cost of serving a mass market, allowing everybody to enjoy a premium service. A very good example of this is 24/7 security guards. It would cost you a lot of money to hire a security guard to control your hous... See more
Matilde Giglio • What we look for in AI companies (and why they are different)
When it comes to platform vs tools, we prefer companies that start as a tool and then develop as a platform. These are startups that solve a complete business problem. They figure out how to get the data and then how to build a loop to learn from that data and create a user experience that solves a specific business problem.
Matilde Giglio • What we look for in AI companies (and why they are different)
We also tend to be more excited by enterprise focused solutions. Big companies like Facebook, Amazon and Google are concentrated on solving large consumer problems and have all the data in the world to do that really well, so it’s harder for startups to compete.
Matilde Giglio • What we look for in AI companies (and why they are different)
We are more excited by startups that go vertical. We think ML techniques are built to go vertical. The model needs to recognise a very specific set of signal data in a massive, noisy dataset. To get accuracy, you need the same type of data that is relevant to the problem you are trying to solve.
Matilde Giglio • What we look for in AI companies (and why they are different)
“Programmes that can perform a defined task based on training data”.
Matilde Giglio • What we look for in AI companies (and why they are different)
There are a lot of different definitions out there, but the one that I like to use internally is: