Key Takeaways from J.P. Morgan's Expert Discussion on AI Datacenters Industry Overview - The discussion focused on the **AI Datacenter** industry, particularly the scaling up of AI Datacenters and the evolving architecture for hyperscale AI workloads. Core Insights 1. **Shift in Compute Capex**: - There is a rapid shift in compute capital expenditures (capex) towards inference workloads, with techniques like distillation and multi-step optimization yielding significant near-term gains. By approximately **2027**, the share of compute dedicated to inference is expected to surpass that of training workloads [3][4][5]. 2. **Preference for Smaller Models**: - Enterprises are increasingly adopting smaller, fine-tuned models over larger ones, accepting slight quality trade-offs for reduced costs in inference workloads. This trend is exemplified by Cursor's new coding model [3][4]. 3. **Standardization in Hardware**: - The industry is witnessing a move towards standardization in inference-related networking hardware, with expectations for more rack-level standardization in the coming year. White-box solutions are gaining traction through Open Compute Project (OCP) initiatives [3][4]. 4. **Training Constraints**: - Training workloads are facing constraints primarily due to power supply issues, while inference workloads are less affected. The power demands for training are significantly higher, estimated at **5-10 times** that of inference [4][5]. 5. **Longer GPU Lifespan**: - Buyers are now planning for a useful life of **five to six years** for GPUs, an increase from the previous **four years**. This shift reflects a strategic move to repurpose GPUs from training to inference tasks [5]. 6. **Storage Solutions**: - The storage landscape remains hybrid, with HDDs maintaining cost leadership while Flash/NAND is preferred for high-performance needs. Advances in HDD technology, such as HAMR, are helping HDDs remain competitive [5]. 7. **Beneficiaries of Capex Shift**: - Companies like **Broadcom**, **Marvel**, and **Celestica** are expected to benefit from the shift towards inference workloads. Broadcom's work with custom ASICs for major players like Google and Amazon positions it favorably in this evolving market [5]. Additional Important Points - The discussion highlighted the growing comfort among operators in mixing branded and white box solutions, indicating a trend towards flexibility and cost-effectiveness in hardware choices [1][3]. - The preference for Ethernet and PCIe for inference workloads is driven by cost considerations and the ease of capacity expansion, contrasting with the continued use of InfiniBand for training clusters [3][4]. - The call emphasized the importance of co-packaged optics for high bandwidth requirements, particularly for workloads exceeding **1.6T** [3][4]. This comprehensive analysis provides insights into the current trends and future expectations within the AI Datacenter industry, highlighting key shifts in technology, investment strategies, and market dynamics.

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Financial Performance Highlights - The company reported a strong fiscal year 2025, with revenue reaching $5.81 billion, a 23% increase compared to $4.7 billion in fiscal year 2024[7] - Non-GAAP Earnings Per Share (EPS) significantly increased by 191%, from $1.21 in FY24 to $3.53 in FY25[7] - Gross margin improved by 358 basis points, reaching 37.9% in FY25 compared to 34.3% in FY24[7] Revenue Segmentation and Trends - Datacenter and Communications sector accounted for 51% of FY25 revenue[7] - Industrial sector accounted for 7% of FY25 revenue[7] - Instrumentation sector accounted for 5% of FY25 revenue[7] - Electronics sector accounted for 29% of FY25 revenue[7] - In Q4 2025, Networking segment revenue was $945 million, representing 62% of the total revenue distribution[10, 11] - In Q4 2025, Lasers segment revenue was $348 million, representing 15% of the total revenue distribution[10, 11] - In Q4 2025, Materials segment revenue was $236 million, representing 23% of the total revenue distribution[10, 11] Fiscal Year 2026 Q1 Outlook - The company anticipates revenue between $1.46 billion and $1.60 billion for the first quarter of fiscal year 2026[22] - Non-GAAP gross margin is projected to be between 37.5% and 39.5%[22] - Non-GAAP operating expenses are expected to range from $290 million to $310 million[22] - The non-GAAP tax rate is estimated to be between 18% and 22%[22] - Non-GAAP earnings per share are projected to be between $0.93 and $1.13[22]

Core Insights - Coherent Corp. presented its long-term growth strategy and financial model at the 2025 Analyst and Investor Day [1] - The company anticipates over 22% revenue growth and a 2.8 times increase in EPS year-over-year for FY25 [2] Group 1: Market Opportunities - Coherent is focusing on the optical transceivers and components market for AI Datacenters, highlighting its extensive optical technology portfolio [3] - The company sees significant growth potential in the industrial market, particularly in semi cap, display equipment, precision manufacturing, and instrumentation [4] Group 2: Financial Strategy - The CFO outlined key financial priorities, emphasizing the acceleration of profitable revenue growth and a refined investment strategy [5] - Coherent aims to achieve double-digit revenue growth in key markets while expanding gross margin and EPS [2][5]