Open Climate Fix

www.openclimatefix.org

Open Climate Fix is a non-profit research and development lab, totally focused on reducing greenhouse gas emissions as rapidly as possible. Every part of the organisation is designed to maximise climate impact, such as our open and collaborative approach, our rapid prototyping, and our attention on finding scalable & practical solutions. By using an open-source approach, we can draw upon a much larger pool of knowledge and skills than any individual company, so combining existing islands of knowledge and accelerating progress. Our approach is to: 1. Search for ML (Machine Learning) problems where, if we solve a well-defined ML task, then there's likely to be a large climate impact. Then, for each of these challenges, we'll: 2. Collate & release data, and write software tools to make it super-easy for people to consume this data. 3. Run a collaborative 'global research project' where everyone from 16-year-olds to PhD students to corporate research labs can help solve the ML task (and, over the last 6 weeks, I've received over 300 emails from people who'd love to get involved). 4. Once the community has developed good solutions, help to put those into production, so we can be reducing emissions ASAP. Our first area of focus: Solar Photovoltaics (PV). The uncertainty of solar PV generation generates significant unnecessary carbon emissions to ensure system security. Firstly OCF plans to build better PV nowcasts by tracking clouds from satellite images and 'rolling' those images forwards in time using a combination of conventional numerical weather predictions and machine learning. Through optimising generation, this has the potential to save hundreds of thousands of tons of carbon emissions in UK alone, and many times that globally. Secondly we will support the Open Street Map community in better mapping the location and size of PV panels in the UK.

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Open Climate Fix is a non-profit research and development lab, totally focused on reducing greenhouse gas emissions as rapidly as possible. Every part of the organisation is designed to maximise climate impact, such as our open and collaborative approach, our rapid prototyping, and our attention on finding scalable & practical solutions. By using an open-source approach, we can draw upon a much larger pool of knowledge and skills than any individual company, so combining existing islands of knowledge and accelerating progress. Our approach is to: 1. Search for ML (Machine Learning) problems where, if we solve a well-defined ML task, then there's likely to be a large climate impact. Then, for each of these challenges, we'll: 2. Collate & release data, and write software tools to make it super-easy for people to consume this data. 3. Run a collaborative 'global research project' where everyone from 16-year-olds to PhD students to corporate research labs can help solve the ML task (and, over the last 6 weeks, I've received over 300 emails from people who'd love to get involved). 4. Once the community has developed good solutions, help to put those into production, so we can be reducing emissions ASAP. Our first area of focus: Solar Photovoltaics (PV). The uncertainty of solar PV generation generates significant unnecessary carbon emissions to ensure system security. Firstly OCF plans to build better PV nowcasts by tracking clouds from satellite images and 'rolling' those images forwards in time using a combination of conventional numerical weather predictions and machine learning. Through optimising generation, this has the potential to save hundreds of thousands of tons of carbon emissions in UK alone, and many times that globally. Secondly we will support the Open Street Map community in better mapping the location and size of PV panels in the UK.

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City (Headquarters)

London

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Employees

1-10

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Founded

2018

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Potential Decision Makers

  • Co - Founder

    Email ****** @****.com
    Phone (***) ****-****
  • Co - Founder

    Email ****** @****.com
    Phone (***) ****-****
  • Machine Learning Research Engineer

    Email ****** @****.com
    Phone (***) ****-****

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