Eye Test Capital

With $VPG (Vishay Precision Group) reporting earnings in less than 2 weeks, I’m laying out why I believe this is one of the most underappreciated ways to get early exposure to the humanoid robotics wave. VPG isn’t building the robots. It’s building the sensory nervous system they rely on to function. At its core, the company produces ultra-precise sensing solutions, specifically strain gauges and force sensors that deliver stable, repeatable measurements under extreme mechanical stress and high heat. That resistance to drift is not a small detail. It is the difference between a humanoid that can reliably interact with the real world and one that cannot. The moat here is real. Decades of materials science, proprietary manufacturing, and a deep patent base make this incredibly difficult to replicate. Even players like Tesla or Figure AI, who push hard on vertical integration, would struggle to match this level of precision at scale without losing years in the process. What gives me conviction is that this isn’t speculation. It’s coming directly from management commentary across earnings calls. This is a deliberate, documented progression: • Q1 2025: VPG disclosed that a humanoid project was progressing, with initial pre-production orders from one customer and prototype orders from a second. • Q2 2025: The signal strengthened as the lead customer placed follow-on orders totaling roughly $1.5M, shifting the narrative from experimentation to continuity. • Q3 2025: Both customers were active, with orders reaching $1.8M. Management explicitly addressed their capacity to support higher-volume production. • Q4 2025: A third humanoid customer emerged, a new entrant targeting home and warehouse environments. Meanwhile, one of the original customers placed another follow-on order in January 2026. Management has also confirmed they are in active dialogue with additional humanoid developers globally. It is a textbook funnel: prototypes evolving into follow-on orders, expanding from one customer to three, and moving toward production scale. While no customers have been named (NDAs), the order patterns for Customers #1 and #2 align closely with the development timelines of major players like Tesla and Figure AI. Going into this earnings call on May 12, I’m focused on one thing: confirmation of scaling or recurring orders. Because once these sensors are designed in and certified, they don’t get easily swapped out. If that signal shows up, VPG isn’t just participating in the humanoid wave. It becomes the primary external supplier for a critical layer of hardware inside robots that are much closer to real-world deployment than most people think. And if there’s a better name out there with a moat this difficult to replicate, especially one that can’t be easily vertically integrated, I’m open to being challenged. I’ve done a lot of work on this space, and so far, this is the strongest conviction I’ve found.

NYC weekends really do feel rainier... I ran more data and built a full data investigation to see if the pattern is real. Across 2,192 days (6yrs now!) of weather data, NYC rain rates by day of week look like this: Mon: 27.8% Tue: 32.9% Wed: 31.8% Thu: 34.5% Fri: 38.0% Sat: 35.8% Sun: 32.3% Friday is the rainiest day of the week. You are not imagining it. The interesting part is the possible chain reaction behind it. NYC’s PM2.5 air pollution appears to peak midweek, with Wednesday averaging 8.5 µg/m³, roughly 23% higher than Sunday’s 6.9. Those particles can act as cloud condensation nuclei, which may help clouds form and intensify under the right atmospheric conditions. With a 2–3 day lag, that points to a plausible pattern: Midweek pollution buildup → late-week cloud formation → Friday/Saturday rain risk. But the weather does not start in NYC. Storm systems often form or organize farther west, then move east with the prevailing flow. In the data, the rain pattern appears to travel city by city: Chicago: Mon, 33.2% Pittsburgh: Wed, 34.1% Philadelphia: Thu, 35.2% NYC: Fri, 38.0% The storm track takes roughly 3.5 days to travel about 790 miles. Which means it can arrive in New York right as the weekend begins. NYC also is not only dealing with its own emissions. A meaningful share of its PM2.5 can come from upwind sources. The I-95 corridor, including Philly, Trenton, Newark, and surrounding metro areas, sits directly southwest of NYC, which matters because prevailing winds often move pollution northeast. In other words, NYC may be the end of the pipeline. One of the most interesting signals came from COVID. During lockdowns, the weekly pollution rhythm weakened sharply as traffic collapsed. With far fewer vehicle crossings and less commuter activity, the normal 7-day aerosol cycle became much less pronounced. When traffic came back, the pattern returned. That does not prove tailpipes alone are making it rain every weekend. Weather is complicated. But the data suggests a real and testable relationship between traffic, pollution, atmospheric particles, storm timing, and late-week rainfall. The thesis: Our weekly human activity cycle may be helping shape NYC’s weekly rain cycle. Full interactive dashboard with 2,192 days of data, animated storm tracks, and live charts: valueaddvc.com/ny-rain-data

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