Google and OpenAI staged an "AI peak showdown"! Three major investment themes run through this celestial battle: DCI, optical interconnection, and storage.

With the launch of ChatGPT developer OpenAI's "absurdly strong" GPT-5.2 in deep reasoning and code generation to counter Alphabet Inc. Class C's Gemini 3, the "AI pinnacle showdown" between Alphabet Inc. Class C and OpenAI reaches the climax of their confrontation. From an investment perspective, OpenAI and Alphabet Inc. Class C represent the two hottest investment themes in the global stock market - the "OpenAI chain" and the "Alphabet Inc. Class C AI chain." According to Wall Street financial giant J.P. Morgan, there are three major "super investment themes" in the stock market that could be considered the "most beneficial themes" in the ongoing potential years of conflict between Alphabet Inc. Class C and OpenAI. For these three themes, whether one side gains an absolute advantage in the confrontation between the two or they continue to compete, it is considered a long-term positive. J.P. Morgan recently released a research report stating that Data Center Interconnect (DCI), optical interconnection, and enterprise-level high-performance storage will be the three core investment themes that will benefit from the surge in AI training/inference power demand led by the two AI super giants, Alphabet Inc. Class C and OpenAI, amidst the tightness in the global AI computing industry chain from 2026 to 2027. J.P. Morgan also stated that the global demand for AI is still very strong, and their analysts have a generally positive outlook for the revenue realization path of Alphabet Inc. Class C, OpenAI, Microsoft Corporation, Amazon.com, Inc., and other leaders in AI and cloud computing from 2026 to 2027. Breaking down the "OpenAI chain" and the "Alphabet Inc. Class C AI chain," it can be found that the former corresponds to the "NVIDIA Corporation AI computing power chain" (with AI GPU technology as the core), while the latter corresponds to the "TPU AI computing power chain" (with AI ASIC technology as the core). Both NVIDIA Corporation led "InfiniBand + Spectrum-X/Ethernet" high-performance network infrastructure and Alphabet Inc. Class C led "OCS (Optical Circuit Switching)" high-performance network infrastructure rely on data center high-speed interconnectivity (DCI) and optical interconnection equipment suppliers. In addition, the storage product leaders focusing on enterprise-level high-performance storage systems in data centers will also follow the AI computing infrastructure and AI application ecosystem led by Alphabet Inc. Class C and OpenAI to advance towards an unprecedented "AI prosperity cycle." After all, whether it is the incredibly large TPU AI computing cluster of Alphabet Inc. Class C and the massive NVIDIA Corporation AI GPU computing clusters purchased by Alphabet Inc. Class C, OpenAI, Microsoft Corporation, and other AI giants, they all require fully integrated HBM storage systems carrying AI chips. Moreover, the rapid expansion of large-scale AI data centers by Alphabet Inc. Class C, OpenAI, and other AI giants necessitates the widespread purchase of high-performance DDR5 storage devices at the server level as well as enterprise-level high-performance SSDs. In its latest research report, J.P. Morgan has provided a list of specific stocks that it recognizes for the three key investment themes of DCI, optical interconnection, and storage, and has given these stocks a "overweight" rating: Arista (ANET.US), Cisco Systems, Inc. (CSCO.US), Coherent (COHR.US), Credo (CRDO.US), Fabrinet (FN.US), Hewlett Packard Enterprise Co. (HPE.US), Lumentum (LITE.US), Pure Storage (PSTG.US), Seagate (STX.US), and Teradyne (TER.US). Alphabet Inc. Class C vs. OpenAI is like a "battle of the gods": you play the Gemini 3 card, and I'll counter with GPT-5.2 Alphabet Inc. Class C's Gemini 3 has undoubtedly sparked a new wave of AI applications globally in recent times. The Gemini 3 series products have brought an incredibly huge amount of AI token processing, leading Alphabet Inc. Class C to significantly reduce the free access to Gemini 3 Pro and Nano Banana Pro, and temporarily restrict access for Pro subscription users. In addition, recent trade export data from South Korea showing a continued strong demand for HBM storage systems and enterprise-level SSDs further validates the "AI boom still in the early stage of infrastructure shortage" as emphasized by Wall Street. According to Wall Street giants like Morgan Stanley, Citi, Loop Capital, and Wedbush, the global AI infrastructure investment wave centered around AI computing hardware is far from over and is just beginning. With the unprecedented "AI inference computing power storm" driving the momentum all the way to 2030, this round of AI infrastructure investment wave is expected to reach a scale of $3 trillion to $4 trillion. OpenAI, not one to back down, has just launched the GPT-5.2 under an internal "red alert" in response to Alphabet Inc. Class C's Gemini 3. GPT-5.2 is OpenAI's most advanced artificial intelligence (AI) model to date, optimized for professional work scenarios and setting multiple industry benchmark records. The GPT-5.2 Thinking achieved the highest score in the history of SWE coding ability tests, surpassing or matching human expert levels. Additionally, GPT-5.2 excels in creating spreadsheets, making presentations, image recognition, code writing, and long-text comprehension compared to its predecessors, aiming to "create more economic value for people." In some scientific research areas focused on by AI researchers, GPT-5.2 Pro achieved a 93.2% accuracy rate in the GPQA Diamond test, with GPT-5.2 Thinking following closely behind at 92.4%. In expert-level math test FrontierMath, GPT-5.2 Thinking solved 40.3% of the problems, setting unprecedented records. OpenAI refers to GPT-5.2 Pro and GPT-5.2 Thinking as the "best scientist assistant models in the world." Benefiting from the surge in demand for the "OpenAI chain" and "Alphabet Inc. Class C AI chain": DCI, optical interconnection, and storage J.P. Morgan's research report shows that whether it is the "Alphabet Inc. Class C chain" (TPU/OCS) or the "OpenAI chain" (NVIDIA Corporation IB/Ethernet), they will ultimately converge on the same set of "hard constraints" - data center interconnect (DCI), data center optical interconnection, and data storage base (enterprise-level storage/capacity medium/memory testing), which is also the core logic that J.P. Morgan highly values stocks like Arista (ANET.US), Cisco Systems, Inc. (CSCO.US), Coherent (COHR.US), and other mentioned companies. If we view the "Alphabet Inc. Class C vs. OpenAI" as the peak showdown between two technical routes, it essentially aims to address the three hard thresholds in AI training/inference in the physical world: the first is DCI - when training clusters move from "one room" to "multiple buildings, multiple campuses, and even multiple regions," the speed and consistency of interconnection will force the network competition from port scale to "cross-domain scheduling capability" competition; the second is optical interconnection - Alphabet Inc. Class C deep integrates OCS and WDM in the Jupiter concept, embedding optical switching into the data center network architecture, and emphasizing its system benefits in performance, power consumption, cost, and evolvability; OCP (Open Compute Project) has also pushed OCS as an open subproject, indicating the industrialization of "light from devices to architecture" is accelerating. The third investment theme is storage: all the "computing power feasts" around AI eventually come down to the collection, cold storage, precipitation, back-feeding, and governance of data, with enterprise-level data storage platforms and mass capacity media becoming the foundation of the training-inference loop. This is why Wall Street financial giants like J.P. Morgan, Citi, and Morgan Stanley increasingly look positively at the future stock prices of Western Digital Corporation, Seagate, and the "new" SanDisk spun off from Western Digital Corporation. Seagate's HAMR platform (Mozaic 3+) has mass-produced shipments of 30TB-class near-line disks and is advancing towards higher capacity (>30TB) nodes; HAMR is leading in areal density, targeting the pain points of cloud vendors in "rack power consumption/per TB cost," making it a key beneficiary in AI data lakes and cold storage pools. From the accumulated agreements of nearly $1.4 trillion in AI computing power infrastructure signed by OpenAI and the progress of the "Stargate" AI infrastructure project, these super AI infrastructure projects urgently require enterprise-level high-performance storage in data centers (with HBM storage systems, enterprise-level SSD/HDD, server-level DDR5, etc. as the core), driving product demand, prices, and stock prices of storage giants like Seagate, Pure Storage, etc., to skyrocket. Alphabet Inc. Class C's exclusive Tensor Processing Units (TPU AI computing power clusters) production capacity ramp-up is very advantageous for Lumentum's performance growth. The current expansion of AI infrastructure can be described as intense, with super large-scale cloud giants like Alphabet Inc. Class C actively deploying OCS + high-speed optical modules as the "high-performance network infrastructure base" while building TPU/AI GPU computing power clusters. J.P. Morgan states that optical interconnection is not just a "supporting actor" in the AI narrative, but a clear "performance realization mainline" for the years 2026-2027 with supply-demand tightness and clear intergenerational upgrades. Lumentum is one of the biggest winners of the explosive growth in Alphabet Inc. Class C's AI, mainly because it precisely deals with the indispensable optical interconnection in the "high-performance network infrastructure system" deeply integrated with Alphabet Inc. Class C's TPU AI computing power cluster - the OCS (optical circuit switching) + high-speed optical devices. Every increase in TPU quantity by an order of magnitude leads to an increase in Lumentum's shipments. Undoubtedly, the entire optical communication industry chain, including optical modules, benefits from the training/inference of large-scale AI models using optical interconnection - essentially "weaving tens of thousands of computing chips into a machine with optical fibers." The rate of network bandwidth and port numbers growth is not inferior to that of AI chips themselves, which is why the recent surge in the Chinese A-share market optical modules has occurred. On the OpenAI side, NVIDIA Corporation's "InfiniBand and Ethernet" architecture, deeply integrated with the switches and data center network systems of companies like Arista, Cisco Systems, Inc., and Hewlett Packard Enterprise (HPE), does not exclude optical interconnection but complements it. NVIDIA Corporation's "IB+Ethernet" successfully packages "copper determinism + optical distance/density" into a standardized interconnection system: LinkX clearly covers DAC/AOC/multimode and single-mode optical and is used to connect Quantum InfiniBand and Spectrum Ethernet switches, network cards, DPUs, and DGX systems - as connections move from within a rack to cross-rack/cross-domain, the proportion of optical interconnection hardware systems naturally increases; key optical interconnection devices such as InP/EML upstream (such as Lumentum's high-speed InP EML capabilities, devices for 800G/1.6T routes) constitute the core consumables for "bandwidth upgrades." Therefore, the NVIDIA Corporation IB/Ethernet architecture is essentially equivalent to "copper cables for short distances + optical modules for cross-rack/inter-rack/longer distances and higher bandwidth densities." With the rising trend of optical proportion, J.P. Morgan states that companies like Lumentum, Coherent, and other upstream device manufacturers of optical interconnection are typically crucial parts of the IB/Ethernet benefiting chain.