Who Will Decide the Future of Work? - #SFTechWeek
Photos from "Who Will Decide the Future of Work?" — a SFTechWeek panel exploring how AI, Gen Z, and new work models are reshaping careers and success.
Photos from "Who Will Decide the Future of Work?" — a SFTechWeek panel exploring how AI, Gen Z, and new work models are reshaping careers and success.
A powerful discussion on the future of work unfolded during SFTechWeek at WeWork San Francisco, hosted by The AI Collective and LifeSpark Labs.
Leaders from tech, law, and education came together to rethink what “successful employment” means in the age of AI, automation, and shifting social values.
From Gen Z to executives, everyone shared how technology, purpose, and human skills are redefining careers.
Browse the gallery below and relive the memorable moments.
Huge thanks to all speakers and guests for an inspiring evening of ideas, connection, and vision for the future of work.

























































































PhysicsX, a London-based AI engineering startup, has raised $300M at a $2.4B valuation to scale its physics simulation platform across industries like aerospace, semiconductors, and automotive.
Suno raised $400 million at a $5.4 billion valuation—more than doubling its worth in seven months—despite facing copyright lawsuits from Universal Music Group and Sony alleging unauthorized use of over 61,000 copyrighted works in its AI training data.
OpenAI expanded Codex with six role-specific plugins for jobs like sales and investment banking, a Sites feature for sharing work as hosted interactive webpages, and inline Annotations for targeted edits, as non-developer users grow three times faster than developers on the platform.
Inherent emerged from stealth with a $50M seed round co-led by Index Ventures and Radical Ventures to develop Faraday, an AI system designed to reimagine scientific discovery by enabling open-ended human-AI collaboration on unsolved research problems.
XCENA raised $135 million at a $570 million valuation to commercialize its MX1 chip, which places compute capabilities directly inside memory modules to eliminate the costly data relay between CPUs, GPUs, and DRAM that bottlenecks every AI inference request.
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