Every additional watt consumed inside a data center increases cooling requirements. That's why #OpticalInterconnects# are becoming essential for scaling AI infrastructure while improving energy efficiency. Discover how our DFB #LaserArrays# are powering the AI Infrastructure of tomorrow!

Breaking the "Memory Wall": Optical Interconnects Emerge in GPU–HBM Packaging As a solution to the "memory wall," one of the chronic challenges in AI semiconductors, the memory and packaging industries at home and abroad are weighing an approach that decouples the GPU and high-bandwidth memory (HBM) and packages them separately. The core idea is to move the HBM—until now mounted right next to the GPU—a certain distance away, and bridge the gap with light (optics), allowing several times more HBM to be installed than is possible today. On the 22nd, a researcher at a major domestic memory maker said, "We're currently struggling to expand HBM bandwidth and capacity, so we're discussing with customers a plan to overcome the GPU's shoreline limit through optical interconnects and mount more HBM." Shoreline refers to the length of the chip's perimeter. In today's AI computing environment, the key factor dragging down compute efficiency is the data transfer speed of memory chips. While GPU performance has grown by leaps and bounds with each generation, the speed at which memory stores and supplies data has failed to keep pace—creating a structural performance barrier, the memory wall. The arrival of HBM, with its wide data pathways, put out the immediate fire, but critics continue to point out that bandwidth and transfer speeds still fall short of handling the explosive growth in AI compute. Until now, the industry has focused on stacking HBM ever higher to increase memory capacity and bandwidth within a confined footprint. But as stack counts climbed past 12 and 16 layers toward 20 and beyond, process difficulty rose exponentially. The technology hit physical limits, including the growing difficulty of meeting fixed height specifications. Vertical stacking has reached an inflection point—so much so that the JEDEC standards body has relaxed its HBM height specifications. The bigger problem is that if stack counts can't be raised, the alternative is to add more HBM horizontally around the GPU—but that, too, is impossible. In the current 2.5D packaging structure, the GPU and HBM are mounted tightly together on a single substrate. Within this structure, the number of HBM units that can be placed is strictly limited by the finite length of the GPU chip's perimeter—its shoreline. Even when more HBM is desired, there is physically no room to place it, leaving the industry in a structural deadlock. The alternative now emerging across the semiconductor industry is to separate the GPU and HBM and package them independently. It overturns the conventional chip-design principle that components must sit close together to minimize data transfer time. Instead of keeping the two chips adjacent, the approach spaces them apart and links them with overwhelmingly fast optical signals to overcome the added physical distance. Placing the HBM slightly away from the GPU within the board frees the design from the GPU's shoreline constraint. With the spatial limitation gone, far more HBM can be spread out laterally and packed into the board—several times more than today—without having to push stack heights to extremes. This means the total memory capacity and data bandwidth of the AI accelerator system would expand dramatically, on a scale incomparable to current systems. "Discussing Placing HBM Beneath the GPU"… Form Factor Could Change The industry is now producing a range of architectural design proposals over where exactly to place the HBM within the GPU board. The same memory researcher said, "Options under discussion range from broadly utilizing the space immediately around the GPU to isolating the HBM beneath the GPU board." He added, "In the latter case—isolating it beneath the GPU board—the motherboard would have to be extended lengthwise, so we're discussing even an overall form-factor change with the GPU maker." Specifically, the HBM might surround the GPU from several centimeters away, or a separate HBM zone might be created in the center of the board. "We're keeping every possibility open as we discuss the optimal layout," he said. "Nothing has been confirmed as an official roadmap yet, but as part of preliminary research toward next-generation AI accelerators, we're in talks with our partners." The outsourced semiconductor assembly and test (OSAT) industry is also watching this trend closely. An executive at a global OSAT firm said, "Optical interconnects are a clear trajectory. The only question is timing," predicting that "rack-to-rack and server-to-server links will go optical first, and then chip-to-chip connections within the board will follow." He added, "The larger units will be connected by light first, but optical research is moving so fast that it may not be that far off." Technically, the optical-interconnect technology linking GPU and HBM shares the same underlying principle as the technology connecting server to server inside a data center. The difference is the high technical barrier of shrinking optical-conversion technology—once used for communication between large pieces of equipment—down to the microscopic scale of a single board and chipset. An executive at a domestic developer of co-packaged optics (CPO) components explained, "As HBM stack heights approach their limit, the industry is discussing spreading the memory out laterally to maximize how much can physically be mounted." He added, "The principle is the same as conventional data-center optical interconnects, but HBM optical links that have to operate within a confined board space require optical components to be miniaturized to far smaller sizes and far higher integration density—so the technical difficulty is greater."

BREAKING: The FTC cleared SpaceX to acquire Mesh Optical Technologies, a SpaceX-alumni startup making 1.6 terabit per second optical transceivers for AI data centers, Bloomberg reported (Source: Bloomberg, June 26, 2026). The FTC granted early termination of its antitrust review on June 25, 2026, with no significant competition concerns flagged. Mesh was founded in 2025 by 3 former SpaceX engineers. Travis Brashears, Cameron Ramos and Serena Grown-Haeberli built the laser communication system that connects thousands of Starlink satellites to each other in orbit. They left SpaceX to apply the same optical technology to data centers on the ground. Mesh's Alpha C1 chip converts electrical signals to light at 1.6 terabits per second. It replaces copper cables that currently connect GPUs inside AI data centers. Copper interconnects burn power and run hot. Optical interconnects are faster, cooler and more efficient. Mesh came out of stealth in February 2026 with a $50 million Series A led by Thrive Capital. Less than 5 months later it is being acquired. The acquisition fits into Musk's broader AI infrastructure stack. SpaceX bought Cursor for $60 billion this month. Now the optical layer is joining the portfolio. Financial terms were not disclosed.

$SPCX / Elon Musk acquires Mesh, an optical networking startup. Which is working on 1.6T OSFP (pluggable). It’s seems they own the optical engine/packaging side of things, but likely sources CW DFB lasers off merchant companies. $SIVE is one of the more startup friendly plausible merchant suppliers as seen with Ayar to $POET? Maybe $LITE and $MTSI that were have a little history too, but less so. Regardless it’s very positive a lot of startups recently like Celestial have been acquired by Marvell. For both merchant laser supplier revenue (working with startups -> having hyperscalers like SpaceX drive revenue after being designed in already). As well as valuations from M&A desirability. Goes to show how optical interconnects is the right direction if Elon Musk is directly buying these companies.

AMD AI Takeaways Note •AI accelerator market now seen at $1.4T by 2030 (up from $1T prior). We also raises forecast to $1T by 2028, backed by our bottom-up analysis •Server CPU TAM also boosted to >$220B by 2030. Agentic AI expected to be ~50% of TAM, with CPU:GPU ratio tightening toward 1:1. •MI455X is a major leap: 34x higher throughput & 18x lower token cost vs MI355X. Already outperforming Nvidia B200 in some LLM inference. •MI500 brings optical interconnects, ahead of Nvidia Rubin Ultra in key areas (HBM, 4-die package, scale-up domain). •Venice CPU strongest for AI workloads: 2.2x/2.0x higher throughput vs competitors. We estimate ~300k CoWoS builds expected in 2027 → big ASP uplift. 📈 No change to estimates and TP #AMD# #AdvancingAI#

Incase if you already forgot these news about $SIVE Nasdaq Nordic Listed Options 🇸🇪 July 6, 2026: Official trading begins for standardized call/put options on Nasdaq Stockholm. This instantly unlocks major institutional hedging capabilities and explosive retail volume. T-REX 2X Long SIVE Daily Target ETF 🇺🇸 A formal SEC 485A filing has been submitted for a dedicated 2x leveraged daily ETF tracking $SIVE. Wall Street is aggressively making pure-play AI optical interconnects tradeable with maximum leverage. Fully Funded to Nasdaq US Dual-Listing Fresh off a SEK 700M capital raise with negligible 3.3% dilution, CEO Vickram Vathulya confirmed Sivers has entered the execution phase for its Nasdaq New York dual-listing.

AI Hardware Demand Growth and Representative US-Listed Companies June 2026 Executive Summary Nvidia’s transition to the Vera Rubin (VR200) platform marks a significant escalation in AI infrastructure complexity and cost. Our BOM teardown of the next-generation Rubin rack reveals a ~2x increase in total rack cost to approximately $7.8 million (vs. ~$4 million for GB300), driven not solely by the GPU/CPU but by sharp revaluations across the supply chain. Key highlights from downstream components include: • PCB content value +233% YoY, the largest increase. • MLCC +182%, reflecting higher density and count (e.g., ~600k MLCCs per VR200 NVL72 server, +30%+ vs. GB300). • ABF substrates +82%, power solutions +32%, and liquid cooling +12%. These upgrades align with broader AI scaling: 800G/1.6T optical transceivers ramping aggressively, glass-based technologies advancing for packaging and interconnects, and hyperscalers prioritizing performance, power efficiency, and thermal management. We expect sustained multi-year tailwinds for the AI hardware ecosystem into 2027+, with Rubin-driven demand accelerating in H2 2026. Investment Thesis: While Nvidia (NVDA) remains the core beneficiary, the supply chain offers diversified exposure. We favor companies with direct exposure to high-growth areas like advanced PCBs, high-speed optics, and glass substrates/optical interconnects. Risks include execution on new capacity, potential margin pressure from rapid scaling, and geopolitical supply chain factors. 1. PCB: Sharpest Value Uplift in Rubin BOM Morgan Stanley’s detailed analysis shows PCB content in the Rubin rack surging +233% versus GB300. This reflects needs for higher layer counts, advanced materials, better signal integrity, and larger formats to support increased power and interconnect density in AI servers. US Representative: TTM Technologies (TTMI) – Leading US PCB manufacturer with strong positioning in high-complexity boards for data center/AI applications. TTM has invested in capacity expansions (e.g., new facilities) to capture AI-driven demand for advanced HDI and high-layer PCBs. 2. MLCC: Density-Driven Surge Nvidia’s VR200 NVL72 platform requires ~600,000 MLCCs per server, over 30% more than GB300. Combined with the +182% value increase in the BOM, this underscores tightening supply for high-capacitance, high-reliability MLCCs in power delivery and decoupling for AI accelerators. Exposure Note: The MLCC market is dominated by Asian players (e.g., Murata, Samsung Electro-Mechanics, Yageo). US-listed indirect exposure may come through broader electronics or power solution providers, but direct pure-play opportunities are limited. Watch for capacity utilization tightness benefiting the ecosystem. 3. Optical Communication: 800G/1.6T Ramp Accelerating Chinese leader Zhongji Innolight reported Q1 2026 net profit +262% YoY, driven by strong 800G/1.6T shipments, with expectations of significant full-year growth. This mirrors industry-wide momentum as AI clusters shift toward higher-speed optics for reduced latency and power in scale-out/scale-up networking. Nvidia’s investments in photonics and CPO further validate the trend. US Representatives: • Coherent (COHR) and Lumentum (LITE): Key players in optical components and transceivers; Nvidia has made substantial equity investments to secure capacity. • Corning (GLW): Major beneficiary via optical fiber, connectivity, and glass technologies (detailed below). 4. Micro-LED/Glass Substrates & Optical Interconnects: Strategic Partnerships Accelerating On May 20, 2026, BOE announced a cooperation MOU with Corning covering glass-based encapsulation carriers, foldable glass, perovskite substrates, and optical interconnect applications. This aligns with industry shifts toward glass cores for superior flatness, thermal stability, and integration in advanced packaging and photonics—critical for next-gen AI as organic substrates hit limits. US Representative: Corning (GLW) – Central to Nvidia’s optical strategy with multi-billion partnerships, new US optical factories, and expansion in fiber/photonics for AI data centers. Recent deals position GLW for 10x+ capacity growth in key areas. AI Hardware Demand Growth & US-Listed Representative Companies Table Component Demand Growth (vs. GB300) Key Drivers US-Listed Reps Investment Rationale PCB +233% value Higher layers, HDI, signal integrity TTM Technologies (TTMI) Direct AI server/backplane exposure; US capacity expansion MLCC +182% value; +30%+ count Power density in servers Limited direct (ecosystem via power suppliers) Supply tightness supports pricing/volume Optical Comm (800G/1.6T) Strong ramp (e.g., +262% profit ex.) Scale-out networking, CPO transition Coherent (COHR), Lumentum (LITE), Corning (GLW) Nvidia investments; transceiver/fiber boom Glass Substrates/Interconnects Emerging (MOU-driven) Packaging, photonics, thermal/optical Corning (GLW) Nvidia factory deals; US manufacturing tailwinds Power & Liquid Cooling +32% / +12% Higher TDP (e.g., 2300W GPUs) Indirect (ecosystem) Secondary but critical for rack deployment Source: Morgan Stanley BOM analysis, company reports, industry data. Growth metrics approximate from Rubin teardown. Outlook & Risks We project robust 2026-2027 growth in AI capex, with Rubin shipments catalyzing another leg-up in component demand. Optical and advanced substrate shifts could extend the cycle beyond traditional GPU focus. Hyperscalers’ vertical integration and US onshoring (e.g., Corning/Nvidia factories) add resilience. Key Risks: Cyclical capex pauses, yield/execution challenges on new tech (glass/CPO), commodity volatility in passives, and intense competition in Asia-heavy segments. Valuation multiples in the space have expanded; selectivity is key. Recommendation: Overweight select supply chain names with strong Nvidia alignment (e.g., TTMI for PCBs, COHR/LITE/GLW for optics/glass). Monitor Q2 2026 earnings for confirmation of Rubin ramp momentum.

$SIVE 2025 annual report analysis. TLDR: Extremely Bullish. Sivers main growth vector is CPO, but they've TAM expansioned to pluggable transcivers + multiple new qualifications/development. 1. "We are currently seeing great interest... testing our DFB lasers across multiple manufacturers in pluggable transceivers" For pluggable angle, we've seen this with $JBL 1.6T LRO already, but annual report hinted they're developing/qualifying with more hyperscaler suppliers. "Our serviceable markets have now been expanded to include pluggable optical interconnects as well as scale-up and scale-out architectures for co-packaged" (TAM expansion) 2. "Discussions with hyperscalers and pluggable transceiver suppliers indicate a shortage of CW lasers in the coming years" $LITE already signaled CW laser bottlenecks, and they had to buy externally from competitors. So we kinda guessed CW Laser was a bottleneck. And this confirmed it, so was wondering about Win semi. "The partnership announced with high-volume supplier Win Semiconductor in March 2025 now gives us a strong position to meet growing demand" $SIVE likely has capacity locked in with Win from this nuance, which is exactly what I wanted to know. This positions Sivers in the CW laser as both a bottleneck and CPO laser architectural leader. VOLUME PRODUCTION H2 INDICATIONS (BULLISH): 3. "The collaboration positions both companies to address the rapidly growing market for optical AI connectivity, with prototypes to be demonstrated to customers during the first half of 2026 and with the goal of scaling up production by the end of 2026" H1 is more preproduction, H2 production signaled starting with names like $POET. 4. "We are pleased that our largest LIDAR customer will increase production starting in the fourth quarter of 2026" $AEVA start of volume production Q4 with $SIVE = bullish for both. Revenue floor from LIDAR as their CPO scales. 5. Sivers announced a partnership with LIGHTIUM AG to integrate their CW lasers directly onto TFLN wafers. 3.2T+ cycle. (future proofing) FYI no decent investor cares about last year's 2025 financials from development contracts aside from Swedish Media/Locals. Especially when you're forward looking for the 2027-2028 CPO supercycle. But the hint from you can take away from financials + geography that is $NOK is now the high confidence customer of $SIVE. TLDR: -> Win Semi implied capacity lock in during CW laser bottleneck -> Hints of new group of hyperscaler suppliers testing/qualification for pluggable transcivers, which is massive TAM expansion. -> New customers for CW lasers -> Volume production scaling starting H2 for both photonics and lidar.

Just some TLDR news: - $CXMT IPO tomorrow if you like Chinese memory. - Samsung Electronics reportedly struggling to secure large FC-BGA substrates. Ibiden (4062) reportedly requested LTA guarantees, Samsung Electro-Mechanics sought prepayments. - Samsung + $AVGO sign memory + foundry AI framework through 2030, expected to exceed $200b - $SOI expects FY2027 silicon photonics revenue to double compared to the previous year, surpassing Morgan Stanley's 60% growth projection. Photonics thesis go brrr. - SK Group + $NVDA sign $500B+ partnership to build out AI DCs and HBM4 memory. - SKC Absolics glass core delay to 2027 from reports. Targeting final reliability testing EOY, mass production next year. So if you're curious, this does push back some ramps from $LPK and others (hence drop on ER). - $QCOM price hikes by double digits for smartphone processors, due to upstream supplier hike pricing. - $META expected to issue $12B in project-level/SPV financing for El Paso, Texas AI DC expansion - Naver announced a $10 billion investment from $NVDA and Brookfield to construct a 1GW-scale AI Factory. Near term plan is 200MW by 2028. (Nvidia $1B investment, Brookfield nonbinding $9B) - 64GB DDR5 server modules rises 146% versus end-June contract pricing - $INTC brought forward 14A process mass production by a year, risk production H2 2027 and volume production in 2028, vs. 2029 HVM expectations. - Samsung Electro-Mechanics wins $200m MLCC order (existing bottleneck). - $AMD (the Bandana bottleneck), announces Helios is in full production with shipments Q3 2026. Including an up to 2GW MI455X GPU deployment with Anthropic and a 6GW infrastructure rollout with OpenAI. Gave new >50% CAGR TAM to $220B by 2030 from $26b in 2025 for CPU market. Rolls out optical interconnects for Mi500 in 2027. From channel checks, AMD is heading down to the CPO route (seems likely to use Ayar). - $ORCL wins $7B Department of War enterprise software contract - JX metal doubles semi target capacity at its KR subsidary with a 4B yen investment, with operations to begin H2 2027, amid surging demand from major customers Samsung Electronics and SK Hynix - Tungsten hexafluoride spot prices surged 2.1-2.5x Y/Y following Japan's Kanto Denka and Chuo Gas announcing permanent production halts. Fluorinated liquid supply faces a vacuum as 3M plans to exit PFAS production. - From the four optical chipmaker earnings, Yuanjie/Eoptolink/TFC Optical/Dongshan Precision: no major order cuts, 1.6T shipments expected to accelerate into 2027. Optical chip suppliers expected to capture outsized margins from shortages. - Unitree Robotics Targets 30,000 Humanoid Robot Production Capacity by 2026. Read through on humanoid TAM scaling like $CCXI and others. - Energy storage lithium batteries orders increase first half orders by 2,900% apparently in China. Not as familiar with EVE Energy and other battery makers.