Salesforce and Anthropic launch Claudeforce as Marc Benioff and Dario Amodei explain the collaboration together on CNBC, AWS commits to 2 million more NVIDIA GPUs on top of its GTC pledge, plus six new earnings this week from NVIDIA, Salesforce, Synopsys, HP, Everpure, and Marvell test every bear thesis on AI infrastructure and software at once. Patrick Moorhead and Daniel Newman also cover Hot Chips 2026, the NVIDIA-Hugging Face acquisition rumor, and debate whether Anthropic's SaaS reassurances hold up on Ep. 317 of The Six Five Pod.

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Patrick Moorhead and Daniel Newman break down Marvell's $120 billion custom-silicon deal with Google, Qualcomm-owned Modular's open-source compiler push at ModCon 2026, and state-level pushback against AI data center construction in Texas and Pennsylvania. The hosts also flip roles to debate whether NVIDIA's reduced Ohio financing guarantee signals cracks in the AI infrastructure buildout.

Sovereign AI has moved from a compliance question to a matter of national autonomy, and enterprise leaders are now navigating it as a board-level infrastructure decision. Tom Shields and Russell Fishman of NetApp join Nick Patience of Futurum to unpack what's driving that shift, how sovereign strategy differs by region, and what data infrastructure requirements regulated organizations can no longer treat as optional.

NVIDIA mobilizes over $500 billion in third-party capital to finance AI infrastructure, Anthropic doubles down on data-center ownership and mandatory content watermarking, and Patrick Moorhead and Daniel Newman debate whether distributed AI at the edge is finally ready to accelerate, all on Ep. 315 of The Six Five Pod.

AI keeps getting framed as the disruption that finally sidelines the mainframe. Tom McPherson, General Manager of IBM Z and LinuxONE, joins Daniel Newman and Greg Lotko on The Main Scoop to explain why the opposite is happening, and what platform-native modernization delivers that lift-and-shift migration can't.

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Patrick Moorhead and Daniel Newman cover Tesla and SpaceX's $16.8 billion TerraFab chip factory, Samsung's zHBM debut at FMS 2026, a week of frontier model launches, and a simulated debate for “The Flip” over whether custom silicon will capture the majority of AI workload dollars by 2028. The episode closes with earnings from SpaceX, Palantir, AMD, Astera Labs, IonQ, and Lattice Semiconductor.

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AI infrastructure is running into a physical wall, and Samsung's answer is architectural. At FMS 2026, Samsung Semiconductor's Donovan Hwang and Eyal Pnini join Six Five to unveil zHBM and V10-BV, concept architectures designed to close the physical distance between memory and logic and keep pace with AI's growing demands.

As AI adoption accelerates, Zoho's Raju Vegesna argues enterprises must rethink sovereignty beyond data residency to include who owns the models processing that data. Vegesna joins Six Five to explain why retaining AI intelligence, not just information, determines whether a company remains a customer or becomes a hostage to its technology provider.

Mohamad Ali, SVP and Head of IBM Consulting, joins Daniel Newman to discuss how AI is transforming enterprise workflows, why consulting is becoming software, and what it takes to operationalize agentic AI at scale.

As enterprises move from AI experimentation to execution, data is emerging as the primary constraint on scale. Fragmented systems, unclear ownership, and weak governance are limiting outcomes.

This conversation explores why AI success depends on data discipline, orchestration, and treating data as a core enterprise asset.

Abe Dev, Vice President, Digital and Innovation at Riyadh Air, describes building a digital-native airline as "liberating" and "a bit terrifying" at once: no legacy systems to migrate off of, but also no working example to check decisions against. Daniel Newman gets into how orchestration became the discipline that replaced that missing benchmark.

Jason Kelley, GM and Managing Partner at IBM Consulting, and Tim Hatton, Vice President of Global Strategic Alliances at Oracle, tell Daniel Newman what it actually takes to make a multi-vendor AI partnership work: reward sharing, built-in failure prevention, and agreement on the outcome before any partner is assigned a role.