All 31 Semiconductors posts we have indexed from venture capital blogs and newsletters, plus the highest-scoring pieces of the past year and the people who write about it most.
Venture capital is shifting from software to physical technologies as AI collapses software development costs and the SaaS model loses defensibility; the strongest opportunities now lie at the intersection of AI-accelerated atoms—chips, energy, robotics, biotech—where capital intensity and technical moats remain defensible.
Bell Labs achieved epochal breakthroughs because it combined patient capital from AT&T's monopoly rents, a concrete mission with bottomless technical depth, and direct manufacturing scale—conditions that modern antitrust, capital markets, and VC structures have made illegal. Recreating such institutions requires "synthetic rent" without the predatory monopoly, a structural puzzle we've largely abandoned.
As AI inference demands explode while power grows scarce, specialized hardware architectures are resurging after decades of general-purpose CPU dominance—enabled by new software tools, easier chip development, and heterogeneous workload requirements that favor tailored designs over one-size-fits-all solutions.
GPU inference economics show healthy unit economics at scale—SpaceX achieves $2.44/card-hour realized revenue with <1-year paybacks—but face pressure from token price deflation outpacing hardware costs and emerging on-device inference reducing cloud demand.
With $1.4T in AI CapEx expected by 2027–28, cloud vendors need $600B+ in annual revenue by late 2027 and $1T+ by 2028 to become self-sustaining; the article maps supply-chain constraints and identifies what must go right—frontier performance, adoption speed, and high-value workloads—for the buildout to pay off.
AI systems now generate large bodies of work—papers, code, robot policies—but verification, security, and physical deployment have become the scarce parts of the stack. The frontier shifts from model capability to operationalization.
Google's Chief Technologist for AI Infrastructure argues that AI economics are shifting from optimizing individual chips to optimizing entire systems—models, software, networking, power, and reliability—with 'goodput' (useful computation delivered) replacing peak FLOPS as the metric that matters.
A climate-tech insider attends Yotta 2026 to examine whether the $11 trillion AI infrastructure buildout can drive grid modernization and decarbonization—and grapples with growing public backlash, regulatory friction, and whether the gold-rush mentality will actually enable the clean-grid outcomes she hoped for.
A16Z (6) · Tomasz Tunguz (5) · Investing in AI (4) · Saastr (3) · Saanya Ojha (3) · Eclipse (2) · Not Boring (2) · Newcomer (2) · Chamath Palihapitiya (2) · Guru Chahal (2)
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