Why a16z Launched the Machine Age Fund | Jen Kha
Andreessen Horowitz launched a $1.1 billion Machine Age Fund to invest in physical AI infrastructure—chips, networking, data centers, and robotics—addressing a massive supply-side bottleneck as AI demand accelerates globally. The fund represents venture capital's return to hardware after 30 years of focusing on software, with a16z seeing hardware pitches rise from near-zero to over 20% of all submissions.
Summary
Jen Kha, managing partner and head of global partnerships at a16z, discusses the newly launched $1.1 billion Machine Age Fund, which invests in the physical infrastructure layer beneath AI software. This fund represents a significant strategic shift, as venture capital has largely abandoned hardware investing for three decades in favor of software and SaaS. However, AI's computational demands have rendered existing infrastructure obsolete—data centers, chips, networking, cooling systems, and memory were all designed for prior technology eras and are now severely bottlenecked.
Kha explains the fund's structure and rationale. Rather than deploying capital through existing funds, a16z created a separate vehicle to signal commitment to the space and maximize ownership at early stages (seed and Series A) where companies can receive $25-35 million investments for substantial equity stakes. This contrasts with late-stage investing where large checks buy smaller ownership percentages. Examples include investments in Unconventional (Naveen Rao's company redesigning chips for AI from first principles) and Next Hop (AI-first high-performance networking).
The capital-raising context reveals strong LP demand. A16z raised over 23% of all venture capital this year, driven by several factors: most AI value accrual has occurred on the private side (not public markets), public data center supply chain stocks (SK Hynix, Samsung, NVIDIA) have surged due to supply constraints, and upcoming public offerings of major AI companies (SpaceX, Anthropic, OpenAI) signal a shift toward private companies generating trillion-dollar valuations.
Kha emphasizes that the infrastructure race has become a geopolitical priority. Countries now view AI adoption as a national imperative, comparable to historical industrialization races. South Korea is providing premium AI as a public utility; El Salvador has implemented Grok in schools and deployed AI doctors; Singapore and the UAE are rapidly adopting AI infrastructure. This global competition creates both opportunities and risks—political headwinds around US data centers (based on surveillance concerns Kha characterizes as "falsehoods") may drive infrastructure buildout overseas, including Elon Musk's space-based data centers.
The fund's thesis encompasses everything below the software stack guided by computer science: accelerators, CPUs, custom silicon, memory, storage, liquid cooling, and robotics within data centers. Kha notes that demand drivers include agents consuming five times more tokens than humans and agents now outnumbering humans online, with AI still representing less than 5% of total usage. On the supply side, infrastructure faces multiple bottlenecks: most data centers aren't built for DC-powered chips (the future standard), less than 2% of US electricians are trained in dangerous DC electrical work, and modern infrastructure requires rebuilding from scratch rather than retrofitting legacy systems.
Regarding public backlash against data centers, Kha argues the narrative has diverged from reality. Modern data centers built by tech companies (AWS, Meta, Switch) incorporate environmental and technical safeguards—Switch contributes power back to the grid, uses minimal water, and is designed for future fluidic cooling. However, data centers painted with broad criticism represent a small percentage of bad actors.
The diligence process differs significantly from traditional software VC deals. The fund's team includes Martin Casado (former Nicera CEO, acquired by VMware), Raghu Raghuram (former VMware CEO), and Guido Appenheiser (former Intel CTO)—individuals with deep data center expertise from prior eras who are returning to hardware. Founders in this space tend to be experienced professionals spinning out from incumbents (e.g., Next Hop's founders from Arista) rather than university graduates, as the category requires relationships with hyperscalers, customer understanding, and deep technical knowledge accumulated over decades.
About this episode
a16z Managing Partner and Head of Global Partnerships Jen Kha joins MTS hosts Theo Jaffee and Sophia Dew to discuss a16z's Machine Age Fund and the investment thesis behind rebuilding the physical infrastructure that powers AI. Jen explains why chips, networking, memory, cooling, data centers, and other parts of the physical computing stack are becoming investable again after decades in which software captured much of the industry's attention. As AI demand pushes existing infrastructure to its limits, she explains why a16z created a dedicated fund and why hardware founders are increasingly rethinking the stack from first principles. They also discuss the global race to adopt AI, what hardware startups need beyond capital, the backlash against data centers in the U.S., and why experienced systems builders are returning to entrepreneurship as a new generation of infrastructure gets built.
Key Insights
- Jen Kha argues that AI has made the existing internet-era infrastructure obsolete because AI workloads are mathematically and computationally intensive in fundamentally different ways than SaaS applications, requiring complete infrastructure redesign rather than incremental improvements to legacy systems.
- A16z observed hardware pitches increasing from near-zero to over 20% of total submissions, signaling a major entrepreneurial pivot toward infrastructure building driven by recognized inefficiencies in how current infrastructure serves AI demands.
- Kha contends that countries viewing AI adoption as a national priority comparable to historical industrialization races—with examples like South Korea's universal AI utility and El Salvador's school implementation—may accelerate infrastructure development overseas faster than in the US due to regulatory and political headwinds.
- Kha claims that modern data centers built by technology companies (versus real estate companies) are actually environmentally and technically sophisticated, contradicting broad public criticism, but acknowledges that political sentiment around data centers may drive supply chain buildout internationally regardless.
- The fund's investment team comprises experienced professionals (former NVIDIA, VMware, and Intel executives) who are returning to hardware after being pulled into software, suggesting that solving AI infrastructure requires founders with 10-15 years of data center relationships and domain expertise rather than novel entrepreneurial approaches.
Topics
Transcript
South Korea, by the way, just announced that they're giving premium AI to every citizen as sort of a public utility thing. So, very, very topical. But by the way, it's not just them. It's El Salvador. They implemented Grok in their schools, for example, for free. And they're utilizing AI doctors, for example. And you see these different examples around the world where they're accelerating their AI development and adoption way faster than in the US. We might also see the influx of a lot of this data center supply chain build-up happen overseas because of this sentiment in the US as well. For decades, venture capital moved further and further away from hardware. AI is pulling it back.…
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