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Lasers, ultrafast lasers, laser processing and laser applications.

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Items 1–3 of 3
Oct 14Wed
  1. optics.org (SPIE Industry News)Optics industryOptics and AI74

    Chip Demand Keeps Growing; ASML Studies Further Expanding Lithography Equipment Capacity

    ASML said its existing 2027 and 2028 supply plans cannot fully meet customer demand and that it is studying a further expansion of 2028 capacity beyond the previously planned 30% increase. Quarterly sales through September 27 were EUR 11.7 billion, up more than 50% year over year. The NXE:3800F EUV lithography system slated for introduction next year will raise productivity from 230 to 260 wafers per hour.

    Why we recommend it: Capacity expansion and productivity upgrades are proceeding in parallel, offering concrete industry clues on how AI demand translates into EUV lithography equipment supply constraints.

Oct 9Fri
  1. C114 Communications Network · Optical CommunicationsOptics industryOptics and AI67

    Lumentum CEO: 2029 Capacity Almost Fully Booked

    Lumentum CEO Michael Hurlston said in an interview in Tokyo that about 70% of demand for some products will remain unmet next year, while other products still face a 30% demand gap through 2028. The company's 2029 capacity is almost fully booked, and it is ramping production at full speed.

    Why we recommend it: The article provides specific demand gap percentages, directly reflecting the tightness of laser chips upstream in AI optical communications

Sep 30Wed
  1. Shanghai Institute of Optics and Fine Mechanics (SIOM) · Research UpdatesOptics industryOptics and AI59

    SIOM Uses Improved YOLOv8-seg for Intelligent Laser Spot Analysis in High-Power Laser Facilities

    The Joint Laboratory for High Power Laser and Physics at the Shanghai Institute of Optics and Fine Mechanics (SIOM) has proposed a laser spot analysis system based on an improved YOLOv8-seg to meet the need for rapid, precise alignment of optics along the full chain of high-power laser facilities, and has completed experimental validation.

    Why we recommend it: The original paper demonstrates a deep learning segmentation model for laser facility alignment, a case of AI entering optical assembly and adjustment