Alphabet and Taiwan Semiconductor: AI chip stocks at 36x earnings

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[1] Alphabet Vs. Taiwan Semiconductor: What Is The Better Stock To Buy Right Now (https://247wallst.com/investing/2026/07/07/al ...)[2] BIP Wealth LLC Reduces Stock Position in Taiwan Semiconductor Manufacturing Company Ltd. $TSM - MarketBeat (https://www.marketbeat.com/instant-alerts/fil ...)[3] What to Expect From Nvidia Stock in July 2026: Recovery or Another Leg Down? (https://beincrypto.com/nvidia-stock-price-for ...)[4] Meta: I'm Buying In The Drawdown (https://seekingalpha.com/article/4920092-meta ...)[5] Intel vs. AMD: Goldman Sachs Analyst Thinks the Answer Is Clear (https://finance.yahoo.com/technology/ai/artic ...)

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Jul 16 2026, 15:08

Morgan Stanley warns memory wall caps AI expansion at $418B by 2030

**Memory capacity and bandwidth constraints, not GPU compute, will determine how far artificial intelligence can scale.** Morgan Stanley warns the artificial intelligence industry is hitting a "memory wall," projecting cloud storage spending will reach $418 billion by 2030 as capacity constraints, bandwidth limits and rising costs threaten to cap AI expansion. "GPU determines how fast AI runs, but the memory system determines how far AI goes," the Morgan Stanley global technology team wrote in the report, which identifies six innovation directions to break the bottleneck. The bank estimates storage-related components now account for 73% of bill-of-materials costs in CPU servers, with DRAM per-gigabyte prices near three-decade highs. DDR5 single-channel bandwidth is expected to grow just 14% from 2024 to 2026, from 44.8 GB/s to 51.2 GB/s, while monthly AI inference token generation is projected to surge more than 320-fold over the same period, from roughly 10 trillion to 3.2 quadrillion tokens. The report points to a thematic rotation in AI-related investment from pure GPU plays toward the broader memory and storage ecosystem. Morgan Stanley projects the total addressable market for new memory technologies excluding HBM will expand from $1.2 billion in 2025 to $23 billion by 2030, and to $276 billion when including high-bandwidth memory. The share of cloud capital expenditure allocated to storage is expected to rise to 40% by 2027 from 12% in 2023. **The Six Innovation Vectors** Morgan Stanley's framework identifies advanced process technology, storage architecture innovation, advanced packaging, peripheral interconnect chips, processing-in-memory and new materials as the six areas where breakthroughs are needed. On the process front, DRAM has entered the 1-gamma node era with Samsung, SK Hynix and Micron all ramping production, though line-width shrinkage has fallen below 10% from the prior generation, indicating the physical limits of planar DRAM. In packaging, the HBM roadmap is advancing toward HBM4 and HBM4E, with 16-layer HBM4E expected to reach mass production by 2027, delivering single-stack bandwidth of 1.5 TB/s to 2 TB/s or more. SanDisk's high-bandwidth flash, which uses through-silicon vias to connect multiple 3D NAND arrays, offers up to 4 TB of memory capacity — 8 to 16 times that of HBM — with first samples expected in the second half of 2026. Wafer-on-wafer stacking is projected to grow from $10 million in 2025 to $9.8 billion by 2030, a compound annual growth rate of 322%. **The Supply Chain Squeeze** The structural nature of the memory shortage is visible across the semiconductor supply chain. High-bandwidth memory now consumes about 23% of total DRAM wafer capacity, up from roughly 19% in 2025 and single-digit percentages two years ago, according to TrendForce. Because each gigabyte of HBM produced removes approximately three gigabytes of conventional DRAM supply from the manufacturing pool, the AI buildout is simultaneously creating and constraining its own memory supply. The constraint extends beyond DRAM. Server CPU availability has tightened as vendors manufacture processors on both 3-nanometer and 5-nanometer nodes in parallel, with lower-than-expected yields on advanced nodes compounding the bottleneck. Enterprise server lead times for large DRAM orders have extended beyond 40 weeks, and CPU procurement backlogs have reached approximately 22 weeks, according to supply chain advisory firm SHI Insights. The competitive picture is shifting as chipmakers adapt their strategies for the inference era. Nvidia has incorporated Groq's language processing units into its CUDA ecosystem to reduce inference latency, while Cerebras Systems has developed wafer-scale chips that it claims are six times faster than Nvidia's LPUs and 15 times faster than its GPUs. Advanced Micro Devices, which acquired memory optimization software company MEXT, is using its chiplet design to offer cost-effective inference solutions as the ratio of GPUs to CPUs in data centers is expected to shrink from about 8-to-1 to roughly 1-to-1 with the rise of agentic AI. For investors, the implication is that the next phase of AI infrastructure spending will flow increasingly to memory and storage companies. Morgan Stanley estimates agentic AI alone could contribute 26% to 77% of global DRAM demand by 2030. Micron Technology, which reported fiscal third-quarter revenue of $41.5 billion — a 346% year-over-year increase — has committed more than $250 billion in US spending through 2035 to expand domestic DRAM production. SK Hynix's chief executive has described 2027 as potentially "the worst year in the industry's history from the supply perspective," while Intel's CEO has said no meaningful relief is expected until 2028. *This article is for informational purposes only and does not constitute investment advice.*

Jul 16 2026, 15:06

UK GDP returns to 0.1% growth in May, beating subdued forecasts

**UK GDP returned to growth in May, but the 0.1% expansion masks a fragile economy buffeted by supply-chain disruptions.** The UK economy eked out 0.1% growth in May, rebounding from April's 0.1% contraction but undershooting the pace needed to sustain the first quarter's momentum as supply-chain disruptions from the Iran conflict weighed on production and construction. "The growth outlook is further threatened by volatile energy costs, which will likely dampen economic activity in the near future," said Fergus Jimenez-England, associate economist at the National Institute of Economic and Social Research. Services drove the recovery with a 0.3% expansion, while production fell 0.5% and construction dropped 0.8%, the Office for National Statistics reported. In the three months through May, GDP rose 0.7%, easing from an upwardly revised 0.8% in the three months to April. The economy grew 0.6% in the first quarter but is tracking just 0.3% in the second quarter, according to Pantheon Macroeconomics. The data leaves the Bank of England in a bind ahead of its July 30 rate decision. Pantheon economist Rob Wood said solid growth makes a rate hike "more likely than a cut," while the Iran-driven energy shock threatens to squeeze households and businesses further. GBP/USD held firm above recent lows as softer US producer inflation weighed on the dollar, giving the pound some breathing room. The ONS said businesses across manufacturing, hospitality, travel and entertainment reported that the Middle East conflict had disrupted global supply chains. Nearly five months of fighting, with the US-Iran peace deal largely collapsed, are pushing fuel and energy costs higher, threatening to slow growth through the rest of the year. A Treasury spokesperson said the government has "the right economic plan, which has put the UK in a much stronger position than two years ago with the fastest growth in the G7 in the first quarter." Both the OECD and the International Monetary Fund recently upgraded their UK growth forecasts for 2026. **Rate Path Hangs on Data** The Bank of England's next decision on July 30 will be shaped by whether the second-quarter slowdown proves temporary or marks the start of a deeper deceleration. The last time the UK economy posted back-to-back monthly contractions was during the 2023 mini-recession, when GDP shrank 0.1% in September and 0.3% in October of that year. Markets are pricing a prolonged hold, with Wood noting that "solid growth is one reason that a hike is more likely than a cut." This article is for informational purposes only and does not constitute investment advice.

Jul 16 2026, 15:05

Super Micro expands liquid cooling lineup with 10 new RDHx models

**Super Micro's new liquid cooling lineup targets the rising heat density of AI factories, where Nvidia's latest GPUs can push rack power past 100kW.** Super Micro Computer Inc. on July 15 expanded its Rear Door Heat Exchanger portfolio with 10 new models, adding cooling capacities from 10 kilowatts to 120 kilowatts for systems-level to rack-scale AI deployments. The San Jose, California-based company's DCBBS liquid cooling line now covers the full thermal range of modern AI infrastructure, from single-server configurations to entire data center rows. "AI workloads are driving power densities that air cooling can no longer handle, and our expanded RDHx portfolio gives operators a drop-in solution that scales from 10kW to 120kW without redesigning their facility," Charles Liang, chief executive officer of Super Micro, said. The new models attach directly to server rack rear doors, using chilled water loops to absorb heat at the exhaust point before it enters the data center aisle. Super Micro claims the design simplifies deployment compared to traditional liquid cooling systems that require facility-wide plumbing changes — a key selling point as hyperscalers race to stand up AI capacity. The portfolio supports cooling for Nvidia's H100 and upcoming B200 GPU clusters, which can draw 700W to 1,000W per accelerator and generate heat loads that overwhelm conventional computer room air conditioning. The expansion arrives as AI data center operators confront a thermal bottleneck. A single rack of Nvidia DGX systems can exceed 40kW, and next-generation configurations are projected to push past 100kW per rack — levels where air cooling becomes physically impractical. Super Micro's 120kW-rated RDHx model targets exactly those deployments, offering a path to cool high-density AI factories without transitioning to more complex direct-to-chip or immersion cooling architectures. For Super Micro, the liquid cooling push represents a competitive differentiator against server rivals Dell Technologies and Hewlett Packard Enterprise, as well as cooling specialists like Vertiv Holdings. The company has positioned liquid cooling as a core growth driver, with management previously noting that liquid-cooled data center deployments could account for an increasing share of its revenue as AI workloads scale. Super Micro shares trade at roughly 22 times forward earnings, reflecting investor expectations that the AI infrastructure buildout will sustain demand for its integrated server and cooling solutions. This article is for informational purposes only and does not constitute investment advice.