Hyperscale Data

Cantor Fitzgerald: Intel & AMD

Intel ($Intel(INTC.US))

> Outlook: Cantor maintains a "Neutral" rating with a $150 price target, noting that the risk/reward profile into earnings is skewed to the upside.

> Drivers: The company is expected to see a "modest beat/raise" in its upcoming results, fueled by demand for agentic AI and expansion in average selling prices (ASP) within its Client segment.

> Key Focus: Analysts are closely monitoring Intel's ability to outperform in a supply-constrained environment and how a potential decline in Client unit sell-through during the second half of the year will impact the company.

> Foundry Progress: There is optimism regarding progress on 18A-P and 14A nodes, alongside developments with both current and new customers. This is expected to lead to a forecast for significantly higher capital expenditure (Capex) in 2027.

AMD ($AMD(AMD.US))

> Upcoming Event: AMD will host its third annual Advancing AI 2026 Event on July 22–23 in San Francisco.

> New Tech: The company is expected to launch its next-generation Instinct MI450-series GPUs and Zen 6-based EPYC "Venice" processors.

> Infrastructure Growth: AMD is anticipated to provide updates on the third-quarter ramp of its "Helios" rack-scale platform and offer more context on a "rapidly expanding pipeline" of large-scale AI infrastructure opportunities.

> Market Projections:

AMD is expected to raise its view on the Server CPU Total Addressable Market (TAM) for 2030 to over $150B (up from $120B).

There is anticipation for an updated view on the AI Accelerator TAM, with potential upside to $600B–$800B in the 2029/2030 timeframe.

> Financial Outlook: Cantor believes AMD is positioned to guide for data center revenues to at least double in 2027. AMD remains a "Top Pick" with an "Overweight" rating and a $700 price target.

📢 𝐉𝐔𝐒𝐓 𝐈𝐍: $Hyperscale Data(GPUS.US) Hyperscale Data Nears AI Compute Deal Worth Over $1 Billion

👉 𝐊𝐞𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:

➤ 𝐇𝐲𝐩𝐞𝐫𝐬𝐜𝐚𝐥𝐞 𝐃𝐚𝐭𝐚 is in advanced talks for a 𝐌𝐚𝐬𝐭𝐞𝐫 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 𝐀𝐠𝐫𝐞𝐞𝐦𝐞𝐧𝐭.

➤ Proposed deal would provide 𝐭𝐰𝐞𝐧𝐭𝐲 𝐦𝐞𝐠𝐚𝐰𝐚𝐭𝐭𝐬 of AI compute capacity at its Michigan campus.

➤ Initial agreement could generate 𝐨𝐯𝐞𝐫 $𝟏 𝐛𝐢𝐥𝐥𝐢𝐨𝐧 in revenue over 20 years.

➤ First 𝐭𝐞𝐧 𝐦𝐞𝐠𝐚𝐰𝐚𝐭𝐭𝐬 expected online within 90 days of execution.

➤ Additional 𝐭𝐞𝐧 𝐦𝐞𝐠𝐚𝐰𝐚𝐭𝐭𝐬 planned approximately 90 days later.

➤ Expansion to 𝐟𝐢𝐟𝐭𝐲-𝐭𝐰𝐨 𝐦𝐞𝐠𝐚𝐰𝐚𝐭𝐭𝐬 by 2028 could generate about 𝐝𝐨𝐥𝐥𝐚𝐫 𝟐.𝟓 𝐛𝐢𝐥𝐥𝐢𝐨𝐧.

➤ Company may phase out 𝐁𝐢𝐭𝐜𝐨𝐢𝐧 𝐦𝐢𝐧𝐢𝐧𝐠 to prioritize higher-margin AI services.

➤ Michigan campus has potential for 𝐨𝐯𝐞𝐫 𝟑𝟎𝟎 𝐦𝐞𝐠𝐚𝐰𝐚𝐭𝐭𝐬 of total power capacity.

➤ Proposed 52-megawatt deployment represents roughly 𝐬𝐞𝐯𝐞𝐧𝐭𝐞𝐞𝐧 𝐩𝐞𝐫𝐜𝐞𝐧𝐭 of potential campus capacity.

⚡ 𝐔𝐏𝐃𝐀𝐓𝐄: Nvidia Qualifies Samsung, SK Hynix, and Micron for 𝐇𝐁𝐌𝟒 Supply - Bloomberg - $NVIDIA(NVDA.US) $Micron Tech(MU.US)

👉 𝐊𝐞𝐲 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:

➤ Nvidia certifies 𝐒𝐚𝐦𝐬𝐮𝐧𝐠, 𝐒𝐊 𝐇𝐲𝐧𝐢𝐱, and 𝐌𝐢𝐜𝐫𝐨𝐧 to supply HBM4 memory.

➤ HBM4 will power Nvidia’s next-generation 𝐕𝐞𝐫𝐚 𝐑𝐮𝐛𝐢𝐧 AI platform.

➤ Jensen Huang confirms all three suppliers are 𝐪𝐮𝐚𝐥𝐢𝐟𝐢𝐞𝐝 and in production.

➤ Vera Rubin systems are in 𝐟𝐮𝐥𝐥 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧, with deliveries targeted for Q3.

➤ New platform combines Vera CPUs, Rubin GPUs, and terabytes of 𝐇𝐁𝐌𝟒 per server.

➤ Memory remains one of the industry’s most critical 𝐀𝐈 𝐬𝐮𝐩𝐩𝐥𝐲 𝐜𝐡𝐚𝐢𝐧 bottlenecks.

➤ Nvidia is expanding its presence in Korea, including plans for a new 𝐑&𝐃 𝐜𝐞𝐧𝐭𝐞𝐫.

💬 𝐄𝐱𝐩𝐞𝐫𝐭 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭:

“All three vendors have been qualified,” Huang told reporters in Seoul.

“All three vendors are in production, and they’re all racing to support Vera Rubin.”

Huang also noted that Nvidia’s Vera Rubin AI systems are now in full production and highlighted the importance of memory suppliers in supporting the next generation of AI infrastructure.

At #GoogleIO, NVIDIA and @GoogleCloud are celebrating a milestone: More than 100,000 developers have joined our joint developer community in just one year, and the platform is expanding.

In the past year, members have shipped RAG applications on GKE, built multi-agent pipelines, and prototyped hybrid inference for real-world use cases like sports analytics and enterprise data pipelines.

What's new this year:

→ JAX learning path for running and scaling workloads on NVIDIA GPUs

→ NVIDIA Dynamo on GKE codelab for large-scale inference optimization

→ Monthly developer livestreams with practical guidance on topics like Multi-agent app development with Gemma 4, NVIDIA Nemotron, and Google ADK on RTX PRO 6000 Blackwell GPUs

NVIDIA is also collaborating with @GoogleDeepMind on responsible AI, using SynthID to watermark outputs from NVIDIA Cosmos world foundation models.

Read more:

Source: NVIDIA_X

$NVIDIA(NVDA.US)

Jensen Huang at Nvidia’s GTC Event:

“We are in every cloud. Every ecosystem. We serve every single industry. Once you install Nvidia GPUs, the use for them is so large because of every sector we touch.”

Source: amit