​Ripple Hosts

​Terhi Vapola

​Greencode Ventures

​Andrew Parish

​WakeUp Capital

​TL;DR

​Ever increasing AI usage will multifold the energy consumption, and it will become the fifth “dirty” sector (after energy, transport, buildings, and heavy industrial sectors). This session will dive deeper to approaches how we can tackle this by making everything from chips to code more energy efficient.

​Topic overview

​Why is the topic relevant?

​The AI boom is here — but its emissions are booming too. As large models grow in complexity and demand, they also grow in carbon cost. The session digs into how we green the AI stack, from semiconductor innovation to software efficiencies and low-carbon data infrastructure. We'll explore the climate cost of training and running AI models, advances in chip architectures, software optimization and green computing architectures, and ultimately, where startups and investors are placing their bets to decarbonize AI.

​What’s up for discussion?

• ​How to reduce the climate impact of AI itself — from hardware and infrastructure to software and systems?

​Dream outcome

​Participants gain clarity on where startups and investors are actively placing bets to decarbonize AI — from hardware innovation to software efficiency and green infrastructure. The session also provides realistic practices that can help reduce AI’s footprint at scale, setting the stage for broader ecosystem adoption.

​Who should attend?

​Founders building green infra, computing innovations & software improvements reducing AI's footrprint, VCs investing in this space, AI researchers