lior susan

Lior Susan argues 85% of global GDP resides in physical industries (manufacturing, semiconductors, defense) now undergoing AI-driven automation and autonomy convergence; Eclipse's portfolio across compute, energy, robotics and defense is scaling rapidly, with IPOs like Cerebras and SpaceX proving the thesis and attracting LP capital for the reindustrialization opportunity.

The 85% of global GDP in physical industries (manufacturing, semiconductors, defense) is being transformed by AI-driven automation and autonomy, creating a generational opportunity for startups and investors in robotics, specialized compute, and energy infrastructure.

85% of world GDP is physical industries (manufacturing, semiconductors, defense); AI-driven automation and autonomy meeting in these sectors creates unprecedented opportunity for US reindustrialization, with compute, energy, defense, and robotics companies becoming large businesses.

Lior Susan argues the convergence of AI, automation, and autonomy across physical industries represents a generational opportunity to reindustrialize the US, with Eclipse's portfolio spanning semiconductors, robotics, and energy infrastructure.

Early-stage funds focused on physical AI (compute, energy, defense, manufacturing) are generating strong realized returns as portfolio companies reach public markets, attracting LP capital despite broader venture slowdown.

Lior Susan argues the industry must proactively share jobs, lower power costs, and profits with local communities to avoid NIMBYism and regulatory delays that could slow the AI infrastructure buildout.

Local opposition to data centers (NIMBYism) threatens buildout timelines; the industry needs to proactively share jobs, lower power costs, and profits with host communities rather than letting social media drive negative narratives.

Lior Susan acknowledges data center opposition stems from poor communication of benefits; argues operators must proactively share economic gains (jobs, lower power costs, profit-sharing) with local communities rather than ceding narrative to social media, and engage regulators early to avoid growth-slowing regulation — a prerequisite for sustained AI infrastructure buildout.