Innovative AI technologies are paving the way for more efficient and impactful environmental monitoring. Joining me today to discuss remote monitoring and water forecasting is Marshall Moutenot, the co-founder and CEO of Upstream Tech. From using satellite imagery to monitor conservation projects to employing machine learning for accurate water flow predictions, Upstream Tech is at the forefront of leveraging technology to address environmental challenges.

In our conversation, Marshall shares his journey from a tech-savvy childhood to co-founding a company with a mission to make environmental monitoring scalable and cost-effective. He delves into the development of Upstream Tech's two primary products: Lens, for remote monitoring of climate solutions, and HydroForecast, which uses AI to predict water flow, aiding in hydropower management. Marshall also underscores the need for integrating domain knowledge with machine learning to create reliable models before offering practical insights for AI startups. Tune in to learn more about how AI can revolutionize environmental conservation!

Key Points:

The details of Marshall’s tech-savvy childhood and entrepreneurial journey.
An overview of Upstream Tech’s mission to improve environmental monitoring.
How they use AI and satellite imagery for scalable, cost-effective monitoring.
The development of their Lens product for remote monitoring of climate solutions.
Why remote monitoring is so challenging at scale and their approach to solving it.
Their product, HydroForecast, and its role in predicting water flow using machine learning.
How integrating new inputs like satellite imagery creates reliable, adaptable models.
Success stories, including outperforming traditional models in a major competition.
Challenges Upstream Tech faces in acquiring and integrating geospatial data.
Best practices for ensuring model reliability and effectiveness over time.
Their team's approach to developing a new machine learning product or feature.
Marshall’s advice for AI startups: don’t get too attached to the tools!
His vision for Upstream Tech’s impact on environmental conservation.

Quotes:
"What these new machine learning models that we're employing allow us to do is to provide enough data to the model to create [equations] to describe physical interactions." — Marshall Moutenot

“[The] adaptability of these models is something that is really exciting for the field overall." — Marshall Moutenot

"We train a single model on a wide diversity, which forces the model to learn the common rules across all of them.” — Marshall Moutenot

“As an organization, one of [Upstream Tech’s] purposes is to see the 100% renewable grid become a reality. We want to continue to contribute to that and to build forecasts that enable that future.” — Marshall Moutenot

Links:

Marshall Moutenot on LinkedIn

Marshall’s Blog

Upstream Tech

Upstream Tech on LinkedIn

Upstream Tech on X

Upstream Tech on YouTube

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