KEY TAKEAWAY - Rogati highlights the overwhelming noise around the “current AI hype” and how everyone wants to get involved - but if an AI is fed garbage, the output will be the same:
People try to plug in data that’s dirty & full of gaps, that spans years while changing in format and meaning, that’s not understood yet, that’s structured in ways that don’t make sense, and (then) expect those tools to magically handle it.
So do AI developers need a marketplace to get better data?
🛍 Philip Keys, from IoT data marketplace provider Intertrust
, reiterates that how “without data, AI ends up as an empty vessel, a group of algorithms churning without producing anything of interest
”. Keys references the growing trend of “data monetisation” or “data marketplaces” - which offers AI researchers (or “at least those whose organisations have the cash to pay for it”) the opportunity to access previously unavailable anonymised data
– Keys predicts that a large proportion of data on data marketplaces will be from IoT devices. 💡 However, Carlos Ariza, BI & Analytics Expert at PA Consulting Group
, points out that the best next-gen analytics platforms
will be “cloud-based, collaborative, and multi-entity” and - crucially - will “aggregate data from inside and outside sources”.
This suggests the need for a wide range of data types
to be available in these marketplaces. 🚀
It requires an astonishingly small amount of browsing information to identify an individual out of an anonymous dataset of 3 million people. Since everyone’s browsing habits are unique, it only takes about 10 website visits to create a “fingerprint” for an individual based on which websites they are visiting and when.