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المحتوى المقدم من K Fund. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة K Fund أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
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#211 - Alejandro Marti (Mitiga): using machine learning to understand climate risk

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Manage episode 396312230 series 2573235
المحتوى المقدم من K Fund. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة K Fund أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

This week we welcomed Mitiga SolutionsAlex (Alejandro) Marti to the Kfund Podkast.

Alex has had a highly varied career covering the intersection between climate risk and artificial intelligence - as CEO and co-founder of Mitiga, Chairman of the UN-ITU Focus Group on AI for Natural Hazards, a researcher within the Barcelona Supercomputing Centre (from which Mitiga was spun out), as well as as a climate researcher at the UK’s Met Office, data lead at the State of New Jersey’s Research department, and a research fellow at Rutgers University.

We were fascinated to discuss how Mitiga brings a data heavy, physics led approach to climate risk, moving from traditional stochastic models to probabilistic models using machine learning, and the vital role of transition risk analysis will play in the coming years for businesses across sectors.

The discussion also covered the functioning of the Barcelona Supercomputing Centre and how it manages tech transfer into spin-out ventures, what Alejandro has learned about bringing in and retaining world class scientific talent in a commercial enterprise (+50% of the Mitiga team hold PhDs), the growth of the data-led risk analysis space, as well as Mitiga’s journey raising funding rounds and traversing the venture capital landscape over the past half decade as a deep-tech climate business.

A highly insightful hour - big thanks to Alejandro for taking the time to speak with us.

You can view and listen to our podKasts on:

  continue reading

234 حلقات

Artwork
iconمشاركة
 
Manage episode 396312230 series 2573235
المحتوى المقدم من K Fund. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة K Fund أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

This week we welcomed Mitiga SolutionsAlex (Alejandro) Marti to the Kfund Podkast.

Alex has had a highly varied career covering the intersection between climate risk and artificial intelligence - as CEO and co-founder of Mitiga, Chairman of the UN-ITU Focus Group on AI for Natural Hazards, a researcher within the Barcelona Supercomputing Centre (from which Mitiga was spun out), as well as as a climate researcher at the UK’s Met Office, data lead at the State of New Jersey’s Research department, and a research fellow at Rutgers University.

We were fascinated to discuss how Mitiga brings a data heavy, physics led approach to climate risk, moving from traditional stochastic models to probabilistic models using machine learning, and the vital role of transition risk analysis will play in the coming years for businesses across sectors.

The discussion also covered the functioning of the Barcelona Supercomputing Centre and how it manages tech transfer into spin-out ventures, what Alejandro has learned about bringing in and retaining world class scientific talent in a commercial enterprise (+50% of the Mitiga team hold PhDs), the growth of the data-led risk analysis space, as well as Mitiga’s journey raising funding rounds and traversing the venture capital landscape over the past half decade as a deep-tech climate business.

A highly insightful hour - big thanks to Alejandro for taking the time to speak with us.

You can view and listen to our podKasts on:

  continue reading

234 حلقات

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