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Data-Driven Charging: Jamie Schiel’s Vision for Smarter EV Infrastructure
Manage episode 435668973 series 3594431
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To beat fossil fuels for energy density and portability, EV charging has to be fast and ubiquitous. But the infrastructure to deliver charging is expensive, both in the chargers themselves and the power infrastructure to deliver the electricity. Companies delivering charging infrastructure are thus cautious, wanting to be sure they’ll make back their investment.
But this isn’t somewhere we can afford to be timid. Stable Auto employs machine learning algorithms to build a cloud based SaaS product that can run deep analytics to determine optimal locations for EV charging. This lowers the risk for infrastructure investment, making it easier for businesses to justify capital investment and hastening the EV revolution. Higher profitability will inevitably also lead to more entrants in the market driving prices down for consumers and accelerating the adoption curve.
Rising energy costs and thoughtful legislation have created a landscape where work like Stable’s can enhance ROI for the companies capable of delivering the infrastructure while simultaneously benefiting consumers by increasing the density of EV charging options. It’s a fantastic example of capitalism driving climate impact. Jamie spoke with us about Stable’s machine learning approach, the state of the US energy industry, and the truly shocking amount of electricity that’ll be necessary to fully switch to EVs.
And, you can work for Stable! They’re hiring for all roles.
Our guest, Jamie Schiel
Jamie Schiel is the Co-Founder and CTO of Stable. Before co-founding Stable, Jamie helped pioneer the use of drones by electrical utilities in New Zealand before landing at MIT Media Lab, where he built a billion frames-per-second camera for automotive and medical sensing. His contributions to clean transportation and energy earned him a spot on the Forbes 30 Under 30 list.
https://www.linkedin.com/in/jamieschiel/
Stable Auto: https://stable.auto/
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