Memory bandwidth has been the limiting factor for LLM inference for a while now, and anyone building out inference capacity is paying for it in power and in cost per token. @Qualcomm has been talking about High Bandwidth Compute as its answer to that problem, and today it showed first-generation HBC silicon working in its San Diego lab, running the full memory read-write path and near-memory compute at production-representative sizes. The numbers Qualcomm is sharing are big, with 18x the effective bandwidth of LPDDR5X and more than 5x the bandwidth per watt of HBM4. Those are Qualcomm estimates, normalized from ATE testing and compared against published competitor specs, so I'll want to see how they translate once HBC is sitting inside a full accelerator. That first accelerator will likely be Dragonfly AI250, which Qualcomm expects to sample in the first half of 2027 as part of its Dragonfly Rack platform. A data center product has already taped out and early bring-up of the bonded DRAM stack is apparently yielding well, which tells me this has moved past the research phase. Qualcomm has more than a decade of experience bonding DRAM onto logic from its mobile business, but HBC is the first time I've seen that work pointed directly at data center inference economics. If HBC delivers anything close to those efficiency numbers in a shipping system, the market impact could be significant. HBM supply has been one of the tightest constraints on AI infrastructure buildouts, and it is a big part of what makes today's accelerators (and basically everything else!) so expensive. An inference platform that gets its bandwidth from a different memory approach would give hyperscalers and cloud providers another lever on cost and supply, and it would put real pressure on NVIDIA and AMD in the inference tier, where tokens per dollar per watt matter more than peak training performance. Silicon is only part of what these customers are buying, though. Hyperscalers commit to a platform for years, and they need confidence in a multi-generation roadmap, a mature software stack, supply they can count on and support when things break at scale. Qualcomm walked away from its Centriq server CPU effort in 2018, and data center buyers have long memories. The HBC results are a strong technical step, and the next couple of years will determine whether Qualcomm can prove it is the kind of reliable, long-term partner these companies need.

Cloud growth is outrunning the cash that funds it. @awscloud hit its fastest growth in five years as Amazon's free cash flow falls to -$42B. @Oracle expands beyond @NVIDIA, while @AnthropicAI's S-1 raises the stakes on a $2T valuation. @PatrickMoorhead and @danielnewmanUV unpack the headlines on Ep. 325 of The Six Five Pod. $ORCL $AMZN Tune in: 00:00:00 - Introduction 00:03:42 - Anthropic S-1 Filing Discussion 00:10:30 - Oracle's AI World + Investor Day Highlights 00:19:48 - Gemini 4 Carbon + Other Models 00:22:24 - Intel's Quantum Ambitions 00:29:31 - The Flip: Neocloud Consolidation Debate 00:35:52 - Bulls and Bears: Microsoft Earnings 00:37:17 - Alphabet Earnings 00:39:35 - ServiceNow Earnings 00:41:11 - Amazon Earnings 00:43:52 - Intel's Earnings and Future

$MRVL TO ACQUIRE $LITE IN $115B ALL-STOCK DEAL Marvell has agreed to acquire Lumentum in an all-stock transaction valued at approximately $115B in enterprise value, combining two major suppliers of AI infrastructure and optical networking technology. Under the agreement: • Lumentum shareholders will receive 4.5 Marvell shares for each LITE share, implying roughly $1,132 per share. • The offer represents a 23.9% premium to unaffected closing prices on October 28. • Marvell shareholders will own approximately 67% of the combined company, with Lumentum shareholders holding 33%. The deal brings together Marvell's custom AI chips, networking switches and interconnect technology with Lumentum's lasers, optical transceivers and optical circuit switching capabilities. The bigger opportunity is the growing shift from copper to optical connectivity as AI data centers require faster data transfer, greater bandwidth and improved power efficiency. Marvell says the combination could expand its addressable market to $550B, allowing it to offer more integrated connectivity solutions across AI data centers and within advanced chip packages. The companies also expect: • More than $1B in annual run-rate cost synergies. • Improved long-term revenue growth and profit margins. • Accretion to Marvell's adjusted EPS in the first year after closing. Matt Murphy will remain CEO of the combined company, with the transaction expected to close in H1 2028, subject to shareholder and regulatory approvals. Separately, Marvell reaffirmed the midpoint of its fiscal Q3 revenue guidance while narrowing the expected range to ±2% from ±5%.

Good $INTC quarter, very challenging guide. We will have to wait until the call to get the details. Has to be from one or all of these: 1. weakening PC (see $MSFT comments) 2. ⁠scarcity of substrates 3. ⁠incident at Intel’s fab in Israel