All-In with Chamath, Jason, Sacks & Friedberg

The IPO Comeback: Why Tech Giants Are Finally Going Public | All-In Liquidity IPO Panel

Brief

The panel brought two strands together: the IPO experience and the technological frontiers in AI silicon and space-based compute. Speakers included Will Marshall (Planet Labs) and Andrew Feldman (Cerebrus/Cerebras), plus investors and hosts who reflected on liquidity and timing. The conversation opened with practical notes about going public: Feldman emphasized that, aside from more cash and new stakeholders, day‑to‑day execution largely stays the same and the IPO process itself is cumbersome. An investor on the panel (Brad Gersner) walked through Cerebrus’s recent public debut—pricing at $185, opening near $320 and trading around $230 shortly afterward—while noting the company had navigated political/ownership scrutiny on the way to market. The room also contrasted different public-market trajectories: Planet’s stock climbed roughly 10x over a year (from about $5 to $50), illustrating how significant appreciation can occur after listing if investors hold through.

The technical half pivoted to why both space and silicon are entering new, intersecting phases. Marshall laid out Planet’s product and market: ~200 daily-imaging satellites, wide utility across agriculture, energy, civil gov’t and a revenue base now dominated (~60%) by security and government contracts. He argued that falling launch costs and satellite miniaturization are catalyzing an Earth-data economy ($75–100B near-term) and that space compute will become economical once launch costs reach roughly $200–$300/kg—on the projection that Starship-like vehicles could get costs there in 2–3 years. Planet is already testing GPUs in orbit and planning TPU experiments with Google. Feldman described a competing trend in silicon: domain-specific architectures that minimize data movement by putting high-speed memory next to compute on a very large die, yielding 15–18x faster inference for major LLM workloads versus GPUs. The two agreed AI plus real‑time Earth data will unlock “planetary intelligence,” but differed on timing: Marshall was bullish on near-term orbital compute experiments and cost inflection, while Feldman cautioned that the final engineering thresholds (the hardest last 10%) make wide deployment a longer slog and that terrestrial compute will remain dominant for the foreseeable future. The panel closed on an investor note: earlier public listings and structured lockups (graded 'dribble' releases tied to performance) can broaden participation and still leave ample upside for long-term holders.

Why it matters

Andrew Feldman (Cerebrus/Cerebras) said going public brings more cash and profile but doesn't change core operations—he described the IPO process as full of 'garbage' meetings and commav-level document reviews, and said employees treated the IPO as a big morale event after a decade of work.

Key details

  • Brad Gersner (panelist/investor) noted Cerebrus's IPO priced at $185, opened at ~$320, and traded around ~$230 soon after (implying a market cap near $50–60 billion), and recalled political/ownership complexity during the company’s path to market.
  • Will Marshall (Planet Labs) described Planet's business: ~200 satellites that image the entire Earth every day and a revenue mix today that's roughly 60% security/government; he said Planet's stock went from about $5 to $50 over ~12 months (≈10x) and estimated the Earth-observation market at $75–100 billion.
  • Marshall argued space-based data centers become economically viable when launch costs hit roughly $200–$300/kg (current ~ $1,000/kg), forecasting that with Starship-like reductions that threshold could be reached in 2–3 years; he highlighted the sun-synchronous dawn–dusk orbit advantage for continuous solar power.
  • Andrew Feldman explained Cerebrus’s architectural bet: build a very large, 'dinner-plate' die and put a much faster memory right next to compute; that design yields ~15–18x faster inference for OpenAI workloads versus GPUs by reducing data-movement bottlenecks.
  • Both panelists see AI + space converging: Will emphasized embedding TPUs/GPUs in orbit (Planet already launching GPUs and plans TPU tests with Google) to enable 'large Earth models'; Andrew cautioned the 'last 10%' of building clustered space compute is hard and believes terrestrial compute will dominate for the near term.
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