The achilles heel of AI in the power system: data

There are many forces that could hold back AI in the power system: computing infrastructure, power availability, regulation, and corporate inertia.

The biggest one? Good data. 

Utilities and grid operators are awash in data. But getting access to it – or making sense of it – is very difficult. 

For a better understanding of how to change that, we turn to someone who spends a lot of his time in the so-called data cloud: Tititaan Palazzi, the head of power and utilities at Snowflake.

“Data naturally ends up in different boxes, in different silos. And when you then want to ask questions of the data, it becomes really hard. You can't ask questions across the enterprise,” he explained.

In 2018, Palazzi co-founded Myst AI with Pieter Verhoeven, an engineer who built critical demand response applications for the Nest Thermostat. Myst was focused on AI-driven time-series forecasting for the grid. 

“In the energy industry, there is a lot of time-series data coming from the grid. At the same time, using AI for forecasting is quite challenging because every time you need to create a new prediction, you need to have the latest data. And so from an engineering perspective, it was quite complicated to do,” said Palazzi.

Palazzi and Verhoeven arrived at Snowflake after Myst was acquired by the company last year. 

This week, we feature a conversation with Snowflake's Titiaan Palazzi on busting data silos, some early wins for AI in the power sector, and what phase of the transition we're in. 

This episode is brought to you by The Big Switch. In a new 5-episode season, we’re digging into the ways batteries are made and asking: what gets mined, traded, and consumed on the road to decarbonization? Listen on Apple podcasts, Spotify, or wherever you get your shows.