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17:26ENMatthew Berman on Funding US Open-Weight AI in Competition With ChinaMatthew Berman · Forward FutureBerman argues that open models face a financing problem and proposes public support, hardware-backed development and specialized models.
53:30ENThomas Kurian on Google Cloud’s TPUs, AI Agents and CybersecurityMatthew Berman, Thomas Kurian · Forward FutureThe Google Cloud CEO explains how Google allocates compute between its own models and competitors, designs infrastructure for agents, and approaches security and code review.
47:32ENClaude Code Subscription Changes and the AI Compute CompetitionMatthew Berman, Dario Amodei · Forward FutureMatthew Berman examines a pricing-page test, third-party agent restrictions and competing claims about compute capacity and customer access.
1:41:11ENAnthropic’s Usage Limits, Compute Constraints and Competition: A Livestream DiscussionMatthew Berman, Dario Amodei · Forward FutureMatthew Berman examines Claude Code pricing tests, third-party agent rules and capacity pressures, contrasting Anthropic’s approach with OpenAI and other competitors.
1:15:19ENAnj Midha on Anthropic, Compute Bottlenecks and Building Frontier AIGast: Anjney Midha · Moderation: Harry StebbingsThe AMP founder recounts Anthropic’s early fundraising and explains his investment thesis around scientific feedback, compute coordination and AI infrastructure.
1:08:22ENMark Doss on Production Engineering for High-Stakes TradingMark Doss · Jane StreetWhy every order matters, how event-based monitoring detects unexpected failures, and what a realistic incident reveals about trading operations.
44:01ENA millionth of a penny: Jeremy Allaire on the payment rails of the agentic economyModeration: Sarah Guo, Elad GilCircle's CEO tells No Priors why stablecoins and a purpose-built chain, not the legacy banking stack, are the money layer for software that buys and sells on its own.
13:08ENAnthropic Changes Claude Subscription Access for OpenClaw UsersMatthew Berman · Forward FutureMatthew Berman discusses a 2026 billing change, uncertainty around agent tools and why he favors a multi-model strategy.
25:15ENMatthew Berman on Claude Mythos, Project Glasswing and AI SecurityMatthew Berman · Forward FutureBerman examines Anthropic’s limited cybersecurity preview and its reported capabilities, then weighs the promise and risks of increasingly capable AI systems.
1:50:42ENThe Future Live: Open Models, Compute Markets and the Future of Tech MediaMatthew Berman, Nick Wentz, Ben Pouladian, Wayne Nelms, Jayden Clark · Forward FutureMatthew Berman and Nick Wentz speak with Ben Pouladian, Wayne Nelms and Jayden Clark about AI infrastructure, pricing and OpenAI’s acquisition of TBPN.
1:37:43ENCisco wants two extra network layers so agents can share intentModeration: Nathan LabenzVijoy Pandey of Outshift by Cisco argues that superintelligence has to scale out through networks of agents, not just up through bigger models.
2:25:58ENAGI Is Already Here. Building NVIDIA Is Not.Gast: Jensen Huang · Moderation: Lex FridmanLex Fridman sits down with Jensen Huang for two and a half hours on extreme co-design, CUDA, four scaling laws, and why a $1 billion AI company is easier than a durable one.
44:19ENThe $500-per-Kilogram Line: Why Starcloud Thinks Data Centers Belong in SpaceStarcloud founder Philip Johnston walks through the physics, launch economics, and business model of putting AI compute in orbit.
1:02ENMatthew Berman’s Plans for a GB300 AI Workstation at HomeMatthew Berman · Forward FutureAfter NVIDIA visits with a Dell Pro Max GB300 system, Berman describes his plans for local models, fine-tuning and future AI agents.
40:56ENFour of the Top Five Defense Primes Still Run Hardware Tests on PowerPointNominal’s cofounders argue that hardware never got the last twenty years of software infrastructure, and that physical AI will stall until test data lives in one place.
1:29:32ENDylan Patel on AI Agents, Military Use, Jobs, and the Race for ComputeMatthew Berman, Dylan Patel · Forward FutureThe SemiAnalysis founder discusses how AI agents are changing his business, the controversy over military use, and the economic and geopolitical stakes of frontier models.
1:38:03ENAI Agents, Engineering Jobs and the Future of Software: Augment, NEAR and ModularMatthew Berman, Nick Wentz, Vinay Perneti, Illia Polosukhin, Chris Lattner · Forward FutureMatthew Berman and Nick Wentz discuss coding agents, personal AI and hardware infrastructure with Vinay Perneti, Illia Polosukhin and Chris Lattner.
44:46ENA Single Training Environment Can Cost Millions. Prime Intellect Wants a GitHub for RLWill Brown and Johannes Hagemann argue that the eval suite you already use to test agents is one step away from a training set.
0:50ENGPU Prices, Memory Shortages and the Possibility of Older Nvidia CardsMatthew Berman · Forward FutureMatthew Berman discusses 2026 GPU price pressure and a possible return to older graphics generations.
1:24:44ENForward Future Live: Portable AI Infrastructure, Software and Formal ProofMatthew Berman, Nick Wentz, Tim Davis, Joseph Floyd, Carina Hong · Forward FutureTim Davis, Joseph Floyd and Carina Hong join Matthew Berman and Nick Wentz for a February 2026 discussion.
1:22:49ENBryan Cantrill: Why Software and Hardware Must Be Designed TogetherBryan Cantrill · Oxide Computer CompanyFrom a stubborn CPU reset to disappearing drives, Oxide’s cofounder makes the case for designing and debugging computing systems across the hardware–software boundary.
1:23ENAn xAI Engineer's Podcast Remarks and DepartureMatthew Berman · Forward FutureMatthew Berman reviews a former engineer's comments about data centers, AI agents and workplace incentives, while asserting a link to his departure.
2:12:31ENMost Caffeine users have no idea they are on a blockchainModeration: Nathan LabenzDFINITY's Dominic Williams tells Nathan Labenz why a tamper-proof, unstoppable cloud is the right backend for AI that writes software from a chat box.
12:13ENOpenAI’s Cerebras Deal and the Race for Faster AI InferenceMatthew Berman, Andrew Feldman, Greg Brockman · Forward FutureMatthew Berman explains why inference speed and computing capacity matter, while a closer look at the agreement and benchmark puts his 100-times-faster scenario in context.
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