Andrew Feldman

Andrew Feldman × Will Marshall × Brad Gerstner × Chamath Palihapitiya × Jason Calacanis × David Sacks × David Friedberg

The IPO pendulum is shifting toward companies listing at $1 billion to $5 billion, with Planet creating roughly 90% of its post-SPAC value in years three and four.Cerebras’s $18.50 IPO followed a difficult 9.5 years, while its chip targets 15–18-times faster OpenAI workloads; orbital data centers offer a potential two-to-three-year cost catalyst, but distributed clustering remains unresolved.

Peter Diamandis × Salim Ismail × Dave Blundin × Dr. Alexander Wissner-Gross × Andrew Feldman

Google’s AI comeback is a distribution-and-infrastructure thesis: Gemini reached 900 million monthly users, AI Mode exceeded 1 billion, and projected CapEx is $180–190 billion as Spark and Search embed agents in defaults and commerce.Cerebras’ 68% IPO surge to a stated $95 billion market cap validates wafer-scale inference, but the more-than-$20 billion OpenAI deal and decades-long domestic-fab constraints leave demand and supply to monitor.

Elad Gil × Sarah Guo × Andrew Feldman

Cerebras says useful AI in 2025 made inference latency a daily constraint, with systems running 15, 18, 20x faster than GPUs.G42’s $1 billion order enabled cluster testing, while an OpenAI agreement Feldman says exceeds $20 billion and an AWS deployment raise the stakes for a 10x manufacturing increase this year.Delivery and governance now matter as much as contrarian architecture.

Harry Stebbings × Andrew Feldman

Cerebras raised $1bn at a record valuation because it had margins while rivals had negative ones, despite still intending to go public; UAE orders may have represented 75-80% of revenue and consumed manufacturing capacity.Feldman argues two-year chip depreciation is empirically wrong and Nvidia’s pre-announcements and OpenAI investment signal defensive demand capture, while power sits in the wrong places; investors should watch utilization, customer concentration, permitting, and whether AI adoption delivers productivity.

Harry Stebbings × Andrew Feldman

Cerebras argues that GPU off-chip HBM is a fundamental inference bottleneck, while wafer-scale SRAM could challenge NVIDIA’s near-total market share.Feldman sees inference demand exceeding 100 times today’s market within five years, with chip providers potentially worth more than model companies, though G42’s 87% revenue concentration remains a key risk.